NEW COURSE - Innovation in Ship Design

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Revision as of 13:22, 23 July 2012

1 Foreword (1pp)
2 Introduction & Background (2pp)
3 Definition of Terms
4 Existing Models
5 The Innovation Algorithm Morphology (10pp)
6 A menu of innovation opportunities in ship design
7 Techniques within each component of the generalized morphology (20pp)
- 7.1 Divergent thinking
  - 7.1.1 Lateral thinking and problem solving
  - 7.1.2 Method of focal objects
8 Application of the Invention Morphology to a Ship Design Task (10pp)
9 Workplace Barriers to Creativity and Innovation (4pp)
10 Future Research Opportunities (4pp)
11 Bibliography

Foreword (1pp)

"Imagine that you enter a parlor. You come late. When you arrive, others have long preceded you, and they are engaged in a heated discussion, a discussion too heated for them to pause and tell you exactly what it is about. In fact, the discussion had already begun long before any of them got there, so that no one present is qualified to retrace for you all the steps that had gone before. You listen for a while, until you decide that you have caught the tenor of the argument; then you put in your oar. Someone answers; you answer him; another comes to your defense; another aligns himself against you, to either the embarrassment or gratification of your opponent, depending upon the quality of your ally’s assistance. However, the discussion is interminable. The hour grows late, you must depart. And you do depart, with the discussion still vigorously in progress." —Kenneth Burke, The Philosophy of Literary Form

It is in the spirit of this image that I respectfully raise my hand and offer the following remarks, in this long-standing academic conversation.

Chris B. McKesson

Introduction & Background (2pp)

There has for some long time been an academic conversation on the nature of design, creativity, innovation, and invention. This conversation has embraced many technical disciplines and has been formative of many important practical contributions to engineering.

I have listened to this conversation for many years, throughout my career as a naval architect, and the time has now come for me to respectfully raise my hand and offer a contribution. This dissertation is that contribution.

This work was provoked by Dr. Paris Genalis, former Assistant Secretary of the Navy for Research and Development, now deceased. Paris asked me: “What is innovation in naval architecture, and can it be taught?” I can now state that I know the answer to this question:

Innovation is not the same as invention, in that it is focused on fielding a product
Innovation is a subset of Design, which is a subset of Creativity
Innovation requires expertise, there is a subtle connection between the Metaphysics of Innovation and the Metaphysics of Quality
Innovation requires specialized skills and aptitudes
Innovation is facilitated by the use of certain tools
The use of those tools does not guarantee innovation - tools don’t make the artisan, they only help him
The practice of using innovation tools can result in developing innovation skills

This summary sounds simple when distilled to this level, but then again Fermat’s last theorem is structurally simple too…and like Fermat, a margin is not large enough to hold my proof. I hope in this dissertation to properly expand and support the answers I have just given.

In order to present my results, I will first recap the background of the conversation, for the benefit of the reader who has not been in the room as long as I. This will include establishing a set of definitions of terms, and boundaries for the present work.

I next observe that many people have put forward techniques or algorithms for innovation. I observe that all of these techniques share a common architecture, and it is not clear to me that this commonality is apparent to their creators. My first contribution is to note this common architecture, and reduce it to a morphology.

Armed with this morphology, my second contribution is to use this framework to create a superset of the previously-published innovationalgorithms, putting each one's components in the appropriate niche of the morphological framework. The superset is thus an inclusive generic or omnibus innovationalgorithm, which embraces all or most of its forerunners.

My third contribution is to return to my roots and show the application of this set of tools to the specific challenges of ship design.

It is my sincere desire that this contribution will assist other participants in the conversation in realizing the common threads that seem to permeate so many of the tools in this discipline, and that this will also serve as an example or paradigm for demonstrating the application of formulaic innovation to other specific design disciplines.

Of course, I also hope that this will be a reference work for naval architects faced with a certain class of problems.

Innovation in naval architecture is today accomplished haphazardly or ad hoc. When innovation is needed in a design project, project manasgers will look for a known-successful innovator to join the project team. I, the author of this dissertation, have made a successful career as one of these in-demand individuals. But while this has been professionally and personally rewarding, it is not an ideally efficient model for including innovation in engineering design.

This ad hoc or individual-based model means that innovation can not be systematic applied. It is relegated to something close to good luck in hiring.

As will be seen below, innovation does require people with particular attributes, but now (as a result of this dissertation) we are able to identify those attributes without waiting for the individual's career to manifest itself. We also have tools that we can give to those individuals to increase their innovativeness, which tools were not issued to me. Indeed, if I may be permitted the first of many metaphors in this dissertation, I will liken this research to the difference between formal education and The School of Hard Knocks. Today we teach engineers, in a four year intensive process, many topics, rules and laws that took years to discover in centuries gone past. In the same way I hope that with this dissertation we can teach engineers the topics, rules, and tools of innovation, rather than hoping that they discover them for themselves.

This approach is unprecedented in naval architecture. There is a slowly emerging science of design which is beginning to be taught in the naval architecture curriculum, but this author knows of zero examples of such a discipline including specific teaching on innovation in ship design.

Engineering creativity is a subject receiving a substantial amount of attention today. Figure {} shows the number of publications, by year, found in the COMPENDEX database for keywords of "creativity" or "creativity AND engineering." The graph clearly shows the exponential growth of this subject, and even the narrower set of keywords still returns more than one new paper per day of the year.

This research was funded by the Office of Naval Research under grant [...]. I greatly appreciate the support and encouragement of ONR, and I sincerely hope that this dissertation will be a contribution of national value.

What is it about this subject that warrants the use of public monies for this study? The answer is that innovation is a powerful naval force multiplier. The Computer Science Department of the Naval Postgraduate School have on their website a description of the importance of innovation to military effectiveness.:

"Our graduates will deal constantly with two kinds of innovation in the world: sustaining and disruptive. Most of the technologies they will work with go through extended periods of continuous, incremental improvements -- a process of sustaining innovation. Armored battleships, for example, became prevalent in the 1870s and underwent continuous improvement for well over a century. Aviation appeared in the early 1900s and underwent continuous incremental improvements, maturing into an air transportation industry used by 700 million people each year. Each of these sustained periods produced enormous cumulative improvements.

"Sooner or later, these sustained periods of incremental improvements are disrupted by completely new technologies based on different principles and requiring new ways of thinking. For example, in the early 1920s aerial bombing proved devastating to the most heavily armored ships, leading to the innovation of naval air fleets and eventually to the aircraft carrier. Terrorists disrupted air travel by exploiting Internet technology to coordinate suicide terror operations that eluded US intelligence.

"The point of the distinction is that sustaining and disruptive innovations require different approaches. Sustaining innovations "improve the system". Disruptive innovations “change the system”; they occur when something external changes the system or forces people to move to a new system. Our graduates will meet both cases in their work. Our curriculum and research support both. "

Former United States Ambassador to the United Nations John Bolton said that he believed America should "never fight a fair fight" (cite). This is the philosophy that motivates finding and exploring innovations in naval design. Breakthrough, disruptive, game-changing innovations in naval engineering are force multipliers that enhance the deterrent power of a naval force. They do this by increasing the asymmetry in a naval engagement. Even the perception of that asymmetry should be a deterrent to foreign aggression.

The value of innovation is recognized by non-naval branches of DOD as well, as witness the fact that Hughes1994 was funded by the Department of the Army. This is yet another indication of the military relevance of an understanding of innovation generally.

This paper is not intended to be an essay on military policy, but it nevertheless seems clear to this author that innovation in naval engineering has a significant place in in defense policy.

The present dissertation is a milestone in innovation in ship design, but it is neither the last work on the subject, nor without risks. For example, it is developed below that innovation is a specialized cognitive skill that can be learned by certain types of engineers. The risk is that based on this I will unfairly restrict the types of people who can learn innovation, by wrongly claiming that a certain attribute is needed. But my claim will be explcicit, so a following research is welcome to challenge it.

Another risk is that I will overlook some extremely powerful tool, and thus do a relatively poor job of "teaching innovation" to my students. Again, my list of tools will be explicit, and following researchers are invited to expand upon them just as [[]] expands upon the work of [[]].

The payoff? What is the payoff of any attempt to formalize education? It is said "An Engineer is a man who can do for a dime what any fool can do for a dollar." In this spirit I hope by this work to be able to teach innovation, rather than waiting for it to grow by luck.

This dissertation was completed as the final product of Grant N... from the Office of Naval Research. ONR funding supported the author for a period of five years, and resulted in the production of two major deliverables (ref [[]] and [[]]) and numerous related papers and presentations.

This research has grown across several intermediate checkpoints, which in Heielmeiers metaphor might be considered "homework assignments." These assignments culminated in the thesis that formalized innovation methods exist, and can be applied to naval architecture. This idea was developed and defended as a dissertation proposal at the University of New Orleans in 2011. The proposal defense might be considered a sort of mid-term exam.

Following approval of the dissertation proposal, the author had one more major checkpoint during the summer of 2012 when the ideas contained herein were tested during a summer fellowship at the US Navy's Center for Innovation in Ship Design, in Washington DC. (ref: ONR fellowship reference...) This checkpoint modified some details of the work and provided valuable validation insights. The work was then revised in subsequent semesters.

The present dissertation represents the "final exam" for this research.

Footnote: This introduction follows the architecture commonly called the Heilmeier Catechism. Dr. George Heilmeier was a former director of DARPA, and is known for a set of structured questions he posed to persons proposing research. The Heilmeie Catechism is described on the wikipedia (http://en.wikipedia.org/wiki/George_H._Heilmeier) and is credited to G. Heilmeier, "Some Reflections on Innovation and Invention," Founders Award Lecture, National Academy of Engineering, Washington, D.C., Sept. 1992.

The full catechism is:

What are you trying to do? Articulate your objectives using absolutely no jargon.
How is it done today, and what are the limits of current practice?
What's new in your approach and why do you think it will be successful?
Who cares?
If you're successful, what difference will it make?
What are the risks and the payoffs?
How much will it cost?
How long will it take?
What are the midterm and final "exams" to check for success?

Definition of Terms

To frame the conversation we need a standard terminology. My topic is "innovation in ship design" but this begs the definition of many terms.

Design (2pp)

I define 'Design' as the creative component of engineering - by which I mean that component in which a new thing is created. A possible synonym for design is 'synthesis' as distinct from 'analysis.' In engineering analysis a system is described, and the system's performance is estimated or calculated by the application of engineering principles. By contrast, in synthesis - or by my definition in 'Design' - the system's performance is described (via the requirements) and it is the system characteristics that are determined by the engineer. Design thus means the engineering discipline of assembling the functional elements of the system into a coherent whole, to meet some set of performance requirements.

In some communities (yacht design and industrial design, in particular) the word 'Design' refers to the aesthetic or styling aspect of creation. While I do not wish to denigrate this aspect, this is not the meaning of Design in this study.

Design is also a uniquely anthropomorphic activity: Design requires a designer, the act of design is an act of the human, and not a feature of the product being designed. To this end I am attracted to Lamb's (Ship Design and Construction, SNAME) definition of design which is summarized as "design is decision-making." This definition succinctly captures the creative element, or the human input. Decisions are by their nature the product of something external to the design process - they are the actions of a Designer, not attributes of the design. To me this has parallel connotations to the word 'create', which similarly requires a creator.

Innovation (3pp)

Further, I define 'Innovation' to mean something close to "Design which has no forebears." Much engineering design is derivative. Indeed, my own teaching of design in Naval Architecture begins with a major unit on how to establish trends of best practice by studying other ships, and then developing your ship so that it lies within those trend lines. This approach is an inherently derivative or incremental improvement approach. By 'Innovation' then I mean something that is in some sense opposite: A design that does not follow where others have gone before. This definition is not perfect, because we will see that one of the techniques of formalized innovation is to simply broaden our set of candidate forebears, and return to the practice of derivative design while drawing on a more distant set of parents, but for purposes of this discussion this definition is sufficient to allow our conversation to proceed.

There exist myriad other attempts to define innovation, each sufficient for the work of each author. Examples may be found in Rowe and Boise (1974), Dewar and Dutton (1986), Rogers (1983), Utterback (1994), Afuah (1998), Fischer (2001), Garcia and Calantone (2002), McDermott and O’Connor (2002), Pedersen and Dalum (2004), Frascati Manual (2004). Afuah (1998) refers to innovation as new knowledge incorporated in products, processes, and services. Bers and Dismukes (2007) define innovation from a performance rather than process point of view, calling a product 'radically innovative' if it has a previously unknown functionality, or a fivefold increase in performance, or a 30-percent reduction in cost. While this appears to be a very different definition than the one I have offered, I submit that it is actually very similar: Bers and Dismukes are saying "level of performance which has no forebears," and the similarity to my own definition thus becomes obvious.

Within the innovation and invention community there is a rising clarity of the difference between the terms "innovation" and "invention." Consider the following from Popadiuk & Chao (IJIM 2006.pdf)

"In the research literature, the definition of innovation includes the concepts of novelty, commercialization and/or implementation. In other words, if an idea has not been developed and transformed into a product, process or service, or it has not been commercialized, then it would not be classified as an innovation."

The Wikipedia entry "Innovation" states: "Innovation differs from invention in that innovation refers to the use of a new idea or method, whereas invention refers more directly to the creation of the idea or method itself."

In light of this emphasis upon the commercial aspect of innovation, one might suggest that this dissertation is actually concerned with invention, rather than innovation. I choose to eschew this contention and stick with the term "innovation", because I am focused upon developing ships that will affect our defensive capability, and this effect can only exist if these ships exist. In other words I am concerned with developing real ships, in the same sense that the definition of innovation emphasizes real products. A naval engineering breakthrough that is not instantiated in a ship is not the subject of this dissertation. The topic of this dissertation is innovation because I want the ship to be created - delivered - the naval equivalent of commercialized.

An invention may be essential to innovation, but it is not equivalent to it. And, as will be seen below, some innovations (architectural innovations) do not require the sort of breakthrough that is usually recognized as an invention.

Sustaining versus Disruptive

Innovations are sometimes divided into two classes; “Sustaining” and “Disruptive.” Christensen (“The Innovator’s Dilemma”) provides a helpful discussion of the difference between these two types of innovation, by reference to a case history in the disk drive industry. In this case the sustaining innovations involved technologies yielding ever-increasing data storage density in the then-existing 5-inch disk format. The disruptive innovation was the introduction of hte 3-inch dis drive, which made laptop computers feasible.

A sustaining innovation helps an industry sustain a rate of growth despite the maturity of it’s constituent technologies. Most technologies follow an S-curve of development, wherein there is a low-growth tail during the item’s nascent phase, and a high-growth boom during which the technology rockets into prominence. After some period of time however the technology will begin to ‘plateau’ as it’s own development rate diminishes.

need illustration

The challenge is that the system, of which this item is a component, may wish to sustain a growth rate closer to the component’s ‘boom’ rate. And it is here that the concept of sustaining innovation comes into play.

If several S-Curves are overlayed, each subsequent one shifted slightly to the right of the one before it, it may be possible to build layer upon layer of innovation such that the envelope of the these curves resembles a straight line with high slope, running from one ‘boom’ to the next ‘boom’ ad infinitum.

In this situation these technologies are called ‘sustaining.’

By contrast, a disruptive innovation may be thought of as one which creates a whole new market, even perhaps eliminating the market which came before. Certainly the motorcar was a disruptive technology to the carriage-building industry, few are the carriage-builders who successfully transitioned to become motorcar coachwork factories. The cliche in this case is the proverbial buggy-whip maker.

In naval parlance a disruptive technology is called a “game changer”, and the advent of the submarine and aircraft carrier are two obvious examples of disruptive platform technologies. One may imagine others, taken from the realm of science fiction: An impenetrable missile shield, such that one could be the aggressor without fear of counter-attack, would be a disruptive technology.

Incremental versus Radical

Almost the same as the definitions of "Sustaining" and "Disruptive" innovations are the twin concepts of "Incremental" and "Radical" invention.

An incremental innovation is one which improves some component of the existing system, while leaving the system architecture and functionality basically unchanged. Thus, to create an example in ship design, the invention of the controllable-pitch propeller is an incremental innovation in improving ship propulsive efficiency and performance.

By contrast a Radical invention is one which results in, not an improvement of an existing capability, but a whole new capability. Again from the field of ship design the invention of the hovercraft, with it's amphibious capability, is a radical innovation in ship design.

Architectural Innovation

In file(Henderson%20R,%20Clark%20KB.,%20ASQ%201990.%2035%281%29%20pp9-30.pdf) Henderson and Clark argue that a third type of innovation needs to be defined: Architectural innovation. This refers to an innovation that does not require any new fundamental technology, but instead assembles existing technologies in a new way.

The crux of Henderson & Clark's formulation is to distinguish between the system and the system's components. They state "Successful product development requires two types of knowledge. First it requires component knowledge, or knowledge about each of the core design concepts and the way in which they are implemented in a particular component. Second, it requires architectural knowledge or knowledge about the ways in which the components are integrated and linked together into a coherent whole."

This comment of theirs touches upon the subject addressed later in this dissertation of the need for expert knowledge in order to make inventions. It is my opinion that there is also a need for expert architectural knowledge, required to make an architectural innovation.

Henderson et al use figure () to illustrate the result of their amplification. In this figure the horizontal axis represents the spectrum from incremental to radical innovation, while the vertical axis indicates which part of the system that innovation applies to. Thus, for example, innovations that apply to the components of the system, and leave the architecture of the system unchanged, occupy the top row of the graphic. Innovations that apply to the architecture rather than to the components, are grouped in the bottom row of the graphic.

This results in dividing the innovation landscape into four quadrants: Incremental innovations are those that are applied to the system's components, while leaving the core concept architecture unchanged. A Radical innovation, in their parlance, is one that employs a novel architecture and novel core concepts - a complete departure at the system and component level from the previous system. (A flat panel television in the palm of your hand (e.g. an iPhone) is such an innovation, when compared to a 1960s era CRT television set. Their components are extremely different, and their architecture is extremely different.)

Two new classes of innovation result from the Henderson & Clark definition. One is Modular innovation. Modular innovation applies to the use of a whole new core concept for some or all components of the system, while still assembling those components in the traditional architecture. Thus the invention of solid-state circuitry for televisions, to replace vacuum tube circuits, represents a modular innovation.

An architectural innovation then is one in which only the architecture is changed, while the components still represent the original fundamental concepts. An example the authors use is that of a room fan: The status quo ante involves a motor with a fan blade attached via a shaft. An architectural innovation would to replace this with a rim-drive motor - it is still an electric motor and fan blade, but they are assembled in a completely different relationship.

                                   Core Concepts
                           Reinforced       Overturned
                       -------------------------------------
                       |                 |                 |
             Unchanged |   Incremental   |     Modular     |
                       |                 |                 |

Architecture -------------------------------------

                       |                 |                 |
             Changed   |  Architectural  |     Radical     |
                       |                 |                 |
                       -------------------------------------

Note that although this is depicted as a distinct categorization, in actuality each axis is continuous.

Existing Models

This dissertation addresses the subject of engineering design innovation. Let us begin by positioning that subject within the spectrum of human creative activity.

The most general case of that activity - the highest level of a creativity taxonomy - is simply creativity itself. This level embraces all of the creative acts, whether these be artistic, philosophical, intellectual, or technical. While I do not intend to dwell very long upon the subject of creativity generally, I will in the section that follows present some informative background on attempts to compose a general model of human creativity. This superset includes creation in art, music, literature, etc., as well as encompassing creativity in the mechanical arts. Since this is a superset and not the main focus of the work, it will only receive a very light touch, but it provides an essential foundation for the study, which will drill down from general to particular.

Figure {} depicts the entire creative taxonomy.

Under creativity we find engineering design or product development. This is a specific class of creativity focused upon the creation of tangible objects or processes, under the constraints of physical laws, and in service of some purpose. A discussion of models of this process is found in Section {}

Finally, at the lowest level of the creativity taxonomy we find the existing models of engineering innovation. These are the models and algorithms for innovation that populate the literature in this field, and have informed my thesis that a common architecture or morphology permeates all of them.

The individual methods will be introduced in Section {}, and then I will combine these into a morphological superset in Section {}. I will use that superset in one or more applications in Section XX.

Models of Creativity (4pp)

What is Creativity? This question seems simple, but it has given rise to a vast body of literature. The literature of creativity is remarkable for the number of attempts simply to define this “I know it when I see it” term. I define creativity as follows:

A creative act is the conscious (purpose-driven) invention of a new work, with the goal of this work being better in some sense than the works that went before.

This definition hinges upon three attributes:

Purpose
Novelty
Quality

Let is observe the development of this definition:

Stahl's Overview

Professor Robert Stahl provides an interesting summary of definitions, drawn from publications in the education industry, which is understandably interested in identifying and encouraging creativity. In his paper "A Creatively Creative Taxonomy on Creativity: A New Model of Creativity and Other Novel Forms of Behavior" (Annual meeting of the American Educational Research Association, April 1980) he describes the development of many alternative definitions of creativity, with particular emphasis on student creativity in the classroom – an emphasis that is not far removed from engineering creativity.

Professor Stahl provides a list of possible definitions of creativity, supported by a separate list of possible descriptions of the steps taken in the creative process. Let us begin by considering his summary list of definitions, as follows:

Creativity is:

a)any activity which leads to the production of something new, whether it be a new technical invention, a new discovery in science, or a new artistic performance (DeHaan and Havighurst, 1957).

b)anything produced by a person which is new or unusual to him/her (Vance, 1976).

c)a process of becoming sensitive to problems, deficiencies, gaps in knowledge, missing knowledge, missing elements, or disharmonies (Torrance,1966).

d)the forming of associative elements into new combinations which either meet specified requirements or are in some way useful (Mednick, 1962).

e)an activity which possesses four types of response properties or features:

- 1-unusualness (i.e., the relative frequency of the product among all possible products);

- 2-appropriateness(i.e., the relation of the product to the demands of the situation);

- 3-transformation(i.e:, the development of new forms that involve overcoming the constraints of reality);

- 4-condensation(i.e., the degree to which the product manifests a unified and coherent relationship between simplicity and complexity) (Cronbach, 1968).

f)the power of the imagination to break away from a perceptual set so as to restructure new ideas, thoughts, and feelings into novel and meaningful bonds (Khatena and Torrance, 1973).

g)the intellectual operations relative to divergent thinking and re-definition abilities which are set in motion by a sensitivity to problems (Guilford, 1973).

h)thinking that includes some quality control of newly generated ideas including appropriateness (Crockenberg, 1972).

i)the intentionally entered into process whose final product is unknown with its originality or uniqueness providing the peak experience response (Gallagher, 1975) the display of an openness to new or unusual ideas, a rich sense of humor, an ability to come up with unique solutions to problems (GTGEA,1978)

Of these definitions, items d), and e) seem to the present author to have the greatest relevance to creativity in engineering. This is because they each include the aspect of novelty (as do the others) but the novelty is directed toward some design requirement (explicitly under 'requirements' and 'usefulness' in item d or under 'appropriateness' in item e.) This requirements-driven aspect is notably absent from some of the definitions (e.g. item a) which might be more applicable to artistic creativity.

This aspect of purposefulness is important, because otherwise random finger-painting and bad engineering design get labeled "creative." If the only litmus for creativity is novelty, then randomness is creative. And, indeed, if we consider the role of randomness in genetic evolution (including man-made genetic algorithms) then randomness is an element of creativity. But while novelty is a necessary condition for creativity, it is not a sufficient one.

Stahl goes on to cite several models of the creative process that is paired with the above definitions. Three such models are sufficient:

(a)the phases proposed by DeHaan and Havighurst (1957): 1-period of increasing sensitivity to a problem, 2-period of searching, 3-plateau stage, 4-moment of 'creative' insight, and 5-period of confirmation.

(b)the phases proposed by Wallas (1926) and Gallagher (1964): 1-preparation, 2-incubation, 3-illumination, and 4-verification

(c)the phases proposed by Torrance (1966): 1-identifying the difficulty or problem, 2-searching for solutions, 3-making guesses or formulating hypotheses, 4-testing and retesting these hypotheses, 5-verifying and consolidating these hypotheses, and 6-communicating the findings or results

The steps taken are interesting, because they have been put forward as a set of time-domain definitions. That is to say, the authors claim that if the steps are not followed, then the act is not creative.

But note here again that each of these three models includes some aspect of "quality control." This occurs as "confirmation" or "verification" in the models, but in each case it still contains the concept of comparing the "creative" result against some measure of goodness.

There are other important discussions of general models of creativity:

DeHaan, R. F. and Havighurst, R. J.Educating gifted children.Chicago:University of Chicago Press,-1957..

Vance, H."Creativity and the gifted. NCAGT Quarterly Journal, 1976, 2)

Torrance, E. Payl Creativity research in education:Still Alive.In I. A.

Mednick, Sarnoff A.The associative basis of the creative process.Psychological Review.1962, 69,220-232..

Cronbach, L. J.Intelligence?Creativity?'A parsimonious reinterpretation of the Wallach-Kogan data.American Educational -Research Journal, 1968,

Khatena, J. & Torrance, E. P.Thinking creatively with sounds and words:Norms technical manual.Lexington, MASS:Personnel-Fress, 1973.

Guilford, J. P.Creativity tests for children.Orange, CA:Sheridan Psychological Services, 1973.

Crockenberg, Susan B.Creativity tests:A boon or boondoggle for education?Review of Educational Research,, 1972, ILL (1, Winter), 27-44..

Gallagher, J. J.Teaching the gifted child. ,Boston:Allyn and Bacon,1975.

Gowan, J. E Gifted child education on utopia.Gifted Child Quarterly, 1978,

Gallagher, J. J.Teaching the gifted child. ,Boston:Allyn and Bacon,1964.

Wallas, G.The art, of thought. New York:Harcourt, Brace, 1926.

Torrance, E. Pau' Torrance tests of creative thinking:Norms-technical manual.Princeton, New Jersey:Personnel Press, 1966.

Rhodes' 4P model

\citet{4p} put forward a model of creativity that described creativity as a four-dimensional construct involving 'Person' 'Process' 'Product' and 'Press.' ('Press' is Rhodes' attempt to find a P-word to describe the climate or environment in which the creativity is expressed. The other four terms are straightforward.) Thus Person underscores the human constituent, the need for a Creator. Process is where the aspect of novelty comes in. Product indicates that creativity produces something - whether it be an art form or an object.

These same elements are present in engineering design. As stated earlier, design requires a designer, hence 'Person.' Design also produces an 'Product.' Design, engineering design properly executed, most certainly follows a 'Process', indeed it is a process that is steeped in and governed by the laws of physics, and is composed largely of a variety of engineering analyses. Finally, engineering design occurs within the framework of an industrial and economic infrastructure, which is Rhodes' 'Press.'

Lopez' 4P+N Model

\citet{lopez2006} expanded upon the Rhodes model to add a fifth dimension, 'N' for client needs. This is a helpful addition as it adds the crucial element of requirements pull, which is extremely relevant in naval ship design.

More importantly, let us note that Lopez felt it necessary to add this fifth parameter. She felt that creativity was not sufficiently defined if it was not required to be directed toward some goal. Here again we hear the same thought as discussed by Stahl, the need to close the door to random undirected "creativity."

The Cognitive Network Model

Santanen, Briggs, and deVreede, in "Toward an Understanding of Cognitive Solution Generation" pick up the 4-P model of creativity and use it as a basis for modeling problem-solving. This application is important because again "problem solving" contains an element of focus that is not implicit in, say, finger-painting, but is definitely needed in engineering innovation.

Santanen et al focus their discussion upon the solution-generation phase of engineering problem solving, and later in this dissertation the present author will also focus upon this aspect. These authors also develop a thesis that more research is needed into the cognitive processes associated with creativity. They state: "The above perspectives of creativity offer tremendous insights into creative problem solving. Many of the prescriptions for enhancing creativity (for example, following stage models, employing group support systems, creating a specific environment, or gathering people with certain abilities) are demonstrably effective and have yielded vastly useful insights drawn from extensive experiences. However, these prescriptions tend to imply a cause-and-effect relationship without addressing what actually causes the effect or explaining why the results obtained matter to creativity. Given this discussion, it is difficult to explain why one may be creative at some times and not at others, or why one person is more creative than another is. Without this causal explanation, it is difficult to know what parts of the various prescriptions are effective and which are superstitions."

Again, the present author will return to this topic when discussing the characteristics of the creative individual, in Section {{}} below.

The Cognitive Network Model (CNM) developed by these authors is founded upon simple principles which have a ring of empirical truth in the present author's experience. I can do no better than to submit a lengthy quote from the authors: (* Embedded citations have been removed)

"The Cognitive Network Model of creativity ... attempts to answer the research question “What is the configuration of a basic cognitive mechanism that is responsible for producing creative solutions to a problem?” This model derives from a synthesis of concepts from three bodies of research: organization of memory and knowledge, the role of cognition and knowledge in problem solving, and creativity.

"The CNM begins with the assumptions that human memory is organized into bundles of related knowledge. The most basic of these bundles is generally referred to as the concept that comprises semantic memory. Several models that account for the structure of concepts have been proposed. While various strengths and weaknesses exist for each of these structures that are hypothesized to represent our knowledge, each model proposes that memory is organized into concepts that contain related knowledge. Thus, human memory is not atomic in nature; rather, knowledge is represented by collections of related entities.

"The second major premise of the CNM asserts that the concepts which comprise human knowledge are highly associative in nature. That is, concepts are interconnected such that they form vast networks representing our knowledge and experiences. The concept models of memory introduced above serve primarily to help us classify and deal with object concepts (like cats, dogs, and chairs). However, human knowledge is clearly organized according to more sophisticated entities than objects alone. There are also relational concepts that indicate how the different objects interact with one another through temporal relations. Accordingly, researchers have proposed more complex and abstract forms of memory organization. Prevailing constructs used to account for the relational structure of knowledge include schemata and frames. A frame can thus be thought of as a network of nodes (concepts) and the relationships among them. Similarly, schemata are packages that represent all types of knowledge as well as information about how this knowledge is used. For example, schemata represent concepts stored in memory such as objects, situations, events, and sequences of events. Therefore, the CNM assumes that human memory exists as a complex network structure where frames interconnect with one another by associations (links).

"The two previous sections argue that human memory is organized into frames (bundles) that are highly associative in nature. This section considers the third major premise that underlies the CNM: when any particular frame becomes activated (for example, when we think about cats, dogs, or chairs), subsequent activation spreads to other frames which are closely related to the originally activated frame (for example, thinking about ‘cat’ may lead someone to think about their pet). The spreading activation model asserts that activation of one node activates the next most strongly associated node, which in turn activates the next most strongly associated node to that one. As activation spreads out in this fashion, the relative strength of activation for each successive frame decreases. Patterns of activation among associated frames involve two components. The first is an automatic spreading activation that is fast acting and occurs without intention or conscious awareness, while the second involves a limited- capacity processing mechanism that and cannot operate without intention and conscious processing. Evidence for spreading activation derives predominantly from priming experiments. In the simplest case, priming occurs when people that are shown the same stimulus on two separate occasions are faster to identify the stimulus on the second occasion due to “residual” activation. This repetition priming effect occurs even when there is no conscious awareness that the stimulus was previously presented.

"Together, the presentations in this and the previous two sections draw upon a vast body of research which concerns the organization of memory and knowledge. These findings represent major components of the foundation for the CNM. "

Based on this model of cognition, these authors then build a model of the creative process via a set of eight fundamental "Propositions" of the CNM, as follows:

Proposition 1: Conditions that increase the likelihood of forming new associations between distant frames from our knowledge network also increase the production of creative solutions.

Proposition 2: As the associative distance between salient frames increases, so too does the likelihood of forming new associations between those frames.

Proposition 3: As cognitive load increases, the likelihood of forming new associations between distant salient frames decreases.

Proposition 4: As the number of stimuli we are exposed to per unit of time increases, our corresponding level of cognitive load also increases.

Proposition 5: As the associative distance between salient frames increases, our corresponding level of cognitive load also increases.

Proposition 6: As the degree to which we are able to chunk salient frames increases, our corresponding level of cognitive load decreases.

Proposition 7: As the diversity of stimuli we are exposed to increases, the associative distance between salient frames also increases.

Proposition 8: As the diversity of stimuli we are exposed to increases, the degree to which we are able to chunk salient frames decreases.

From these proposition it is easy to see implications for creativity. For example, by Proposition 3 creativity should be relatively rare when cognitive load is high. By Proposition 4 we will increase our creativity by reducing the number of stimuli per unit time to which we are subjected.

Other implications abound. The point this is not to develop all of the implications of the CNM, but instead simply to provide the reader with this model and it's constituent concepts of associative distance, cognitive load, and so forth.

Creativity versus Novelty

Is creativity necessarily the result of a specified cognitive pattern - a certain 'algorithm' for thinking? name - from Stahl has suggest that it is. On the other hand, other authors need names - see Stahl have suggested that the entire definition lies in the product, and that any result that is "novel" is necessarily and by definition, "creative." We reject this broad definition.

Listen again to Stahl:

"The ambiguous nature of the meaning of creativity test scores is largely due to the way "creativity" has been defined by the test makers (Berelson and Steiner, 1964). If creativity requires the several prerequisite phases listed earlier, then true creative thinking probably never has occurred nor ever will actually occur during the course of a short, timed test of creativity. Subsequently, the argument that one's performance on such a test is a strong indicator of creativeness is suspect. Patrick (1937) provides some evidence that seriously questions the validity of the prerequisite phases.

"If, on the other hand, these phases are not really required and any unique, different or new performance or product is truly 'creative' in nature, then it would be logical to assume that a series of wrong answers on a given convergent test could reflect strong 'creative' tendencies. Yet, few people would feel comfortable equating 'wrong' answers with creativeness.

"Yet another perspective relative to the understanding of creativity should be considered. Stahl (1977) has argued that many behaviors and/or products are labeled "creative" merely because they represent something which is "personally different" from the perspective/experiences of the individual observer.Hence,people are likely to use the "creative" label to describe behaviors or products which are unique to their own thinking, experiences, expectations, or perceptual orientation.This labeling occurs regardless of the degree of actual originality or the intent which went into the behavior or product itself.

"A response which attracts the attention of and lies outside the personal experiences and/or capabilities of the teacher are very likely to be called "creative". A vivid example of this phenomenon is a doodled monster a second grade pupil drew for an art teacher. Upon seeing the monster the teacher immediately pointed it out as a beautiful example of a creative drawing. Later the teacher was disappointed by the news that a monster nearly identical to that doodled was observed by the child two days earlier on a Saturday morning cartoon show. Without that knowledge, the teacher to this day would still believe that that doodled monster was a result of creative thinking and behavior. Many an English composition has been labeled creative because the students used language (e.g., metaphors) in ways different from the teacher's expectations. In both cases the products are labeled "creative" merely because they appeared to be quite original and were out-side the frames of reference the teachers had for that situation and those students at that time (i.e., they were personally different experiences for these teachers). Interestingly, students who are more clever than their teachers are very likely to be identified as being the most creative students in the class -providing of course their cleverness is routed in positive directions.

"In terms of the "personally different" perspective, creativity is measured by the degree to which a person's new behavior or product falls outside the range of convergent-divergent responses already known by or predictable to the teacher or other outside observer. Elements such as attractiveness, functionality, cleverness, and appropriateness are often included or implied as criteria. In such situations, the assumption is made that the actual creativity is directly the result of internal thought processes which presumably caused the creative response or product development (Ebel, 1974): Rather, the real criteria used were externally applied standards which focused almost exclusively on the observable and measurable behaviors/products of the individual. These external standards frequently have little or no direct connection to the actual thought (or information processing which occurred at the time of the "creative" response.

"In short, we must be careful not to [...] associate [creativity] entirely with fluency, divergence or idea-generation. The author's concern for the external criteria of correctne accuracy, quality, appropriateness, etc., of a final 'creative' product or behavior is not a new one (Cronbach, 1971; Crockenberg, 1972; Ebel, 19744; Taylor,1975 a,b).

With our minds now full of this discussion of creativity, let us turn to that particular subset of creativity that is engineering design.

Models of Design (9pp)

Design is a subset of creation, but which subset? What are the discriminators that distinguish design from other creative acts? One might suggest that design is different from creation in the fact that design is constrained by physical laws or technological limitations, but then we note that music is constrained by the physics of sound and mechanics of the instruments, and that book writing is constrained by the limitations of typesetting and the laws of language (James Joyce's "Finnegan's Wake" notwithstanding.) So perhaps the distinction between creation in art and creation in engineering lies only in the author's definition of his sphere of endeavour? Is a physics-compliant science fiction author engaging in design or fantasy?

I believe that the answer is straight-forward: Design is an element of creation. A composer or a novelist may design their works even as they sit down to write them. A painter designs his painting - but he calls it composition. Design is the intelligent arrangement of the subcomponents as required to bring about the whole, which is the vision of the creator.

A science fiction novelist probably designs his book, but he doesn't design the spaceships and laser cannons within the book. This is because I choose to define 'design' as meaning 'establishing all the steps and components (at an appropriate level of detail) to bring the creation into existence.' In this way he does in fact design his book, but he does not design his fantasy inventions - that step is left to some future engineer.

There are many formalized methods for design, such as \citet{lang1968, eder2009, Hubka1967}. A comprehensive review of these models would be a dissertation in itself, and in the present work I subjugate this important set of models to the supporting role of foundation, touching upon enough of them to further outfit our mental furniture for the subsequent discussion of innovation. In addition, I restrict myself to those models which claim relevance to naval architecture. If design must by definition lead to instantiation, then this also limits some of the candidate models of the design process, because some of these models do not lead all the way to completion.

The Design Spiral

The most venerable model of ship design is the design spiral. One illustration of the design spiral (taken from []) is reproduced in Figure {}. The design spiral models design as an essentially iterative process, with increasing level of detail and convergence at each iteration.

There are many variations of the design spiral to be found in the literature, but their differences are matters of which order various modules come in - whether one should do structures before hull form, or vice versa. These differences in detail do not constitute different models of the process. In fact, the number of different versions of the design spiral may be taken as an endorsement that this model does indeed appear to capture the reality of design - at least to naval architects.

So if it is accurate, then in what way is it accurate? There are, as mentioned, two key attributes:

The process is iterative or repetitive. Calculations performed once may be expected to be repeated, because other subsequent calculations will change the input conditions to calculations already performed.
The process converges. The spiral depicts convergence as the radius decreases with time. Indeed, this is such a common belief that naval architecture jargon describes a failed design as "the spiral blows up." This means that convergence did NOT occur, but rather each subsequent iteration got progressively further away, rather than nearer.

The above description of the design spiral will "ring true" with many naval architects, but it fails one key element of design: It does not explicitly contain decision making and creativity. The words that I have used above suggest that design is a sequence of calculations, which could as well be performed by a machine as by a man. (And there are many attempts ot build such a machine.)

However the key to convergence lies in the human element and the aspect of decision making. The design spiral only converges because a human is able to look at the implications of subsequent turns of the spiral and can make decisions during _this_) turn that will help the results of _that_ turn be convergent and not divergent. And indeed those cases where the spiral blows up can very usefully be blamed on poor decision making, in the form of poor design leadership.

The design spiral won't converge by itself. It converges because clever people make clever decisions.

Dr. Tyson Browning

Browning has written on modeling of the design process, and it is interesting to note that he begins by responding to an apparent criticism that having a model of design will stifle a designer’s creativity. (Browning) If this were true for “design” as I have used the term, then it would certainly be even more damning for innovation. However Browning’s response is that a design process model is not only “not a hindrance” but is in fact _essential_ to establishing a design capability. Browning quotes W. Edwards Deming to the effect “If you can’t define what you do as a process, you don’t know what your job is.”

A major thrust of Browning’s work is that the most important aspect of the design process to model, is the interaction component. In other words the critical feature is usually not what happens within each node of the design process, but rather the interactions that occur between the nodes.

This insight is valuable and should inform more of our courses in naval architecture, but I don’t immediately see its applicability to the topic of innovation. That is because I am concerned primarily with the cognitive component of the invention – creating and capturing the Ah-Ha moment – rather than the implementation concern of fleshing out the invention via the design process. Thus Browning’s focus and McKesson’s focus are substantially different, and are not in competition. Indeed, the very 'conflict' herein discovered my be taken as further elucidation of the distinction between design (superset) and innovation (subset.)

footnote:[I do strongly agree that implementation of an innovation will involve many interactions, including the possibility of new and even disruptive interactions in the status quo ante design (development) process. This aspect, however, belongs more properly in my discussion of Barriers and Facilitators of Innovation.]

There is another interaction between Browning’s process modeling work and my own innovation modeling research. Browning rightly notes that the use of a process model can be an important step toward ensuring that knowledge is captured and stored. This takes the form of “lessons learned” on the best and worst ways to do things, and the interactions that resulted in more work, less work, more quality, less cost, more reliability, and so forth.

As we will see in subsequent sections, one of the major tools of formalized invention is the existence of a database of solutions. In TRIZ this is the patent database, in WordTree this is the lexical database, but in all cases this database can be populated, maintained, and grown as a byproduct of the use of a major design process during the product development phase. Thus Browning's process model again foreshadows elements of the present work.

Here we find an echo of the cognitive network model and its attention to associative distance and interactions between concepts. In fact, it would be interesting to apply Browning's philosophy by actively studying, not concepts, but the associations between concepts, explicitly. As a mental placeholder for this future research, imagine studying adjectives instead of nouns. If instead of studying "apples" what if we studied "red"? Whats would be the engineering benefit of design a research project based on interactions rather than components?

Modeling Design Processes Tyson R. Browning November 16, 2010 File: 03-Browning--Process-Modeling-(Navy--Nov 2010).pdf

C-K Theory

C-K design theory or concept-knowledge theory is another model of the design process. C-K theory defines the design process as a structured system of expansion processes, i.e. an algorithm that organizes the generation of unknown objects. The theory builds on several traditions of design theory, including systematic design, axiomatic design, creativity theories, general design theories, and artificial intelligence-based design models. Claims made for C-K design theory include that it is the first design theory that:

Offers a comprehensive formalization of design that is independent of any design domain or object
Explains invention, creation, and discovery within the same framework, as design processes.

The name of the theory is based on its central premises: the distinction between two spaces, a space of concepts C, and a space of knowledge K.

The process of design is defined as a double expansion of the C and K spaces through the application of four types of operators: C→C, C→K, K→C, K→K

The first draft of C-K theory was sketched by Armand Hatchuel, and then developed by Hatchuel and his colleague, Benoît Weil. C-K theory is a research field and a teaching area in several academic institutions in France, Switzerland, Israel, the UK, the USA, and Sweden.

C-K theory was a response to three perceived limitations of existing design theories, which it claims to have overcome:

Design theory did not account for innovative aspects of design.
Classic design theories were tailored to specific knowledge bases and contexts. Without a unified design theory these fields experience difficulties over cooperation in real design situations.
Design theories and creativity theories have been developed as separate fields of research. But design theory should include the creative, surprising and serendipitous aspects of design; while creativity theories have been unable to account for intentional inventive processes common in design fields.

Note in particular that the third point echoes our foregoing discussion of the need for there to be purpose, or requirements, in the engineering innovation process.

<ref>Hatchuel, A and Weil, B 2003, A new approach of innovative design: an introduction to C-K theory. Proceedings of the international conference on engineering design (ICED’03), Stockholm, Sweden, pp 109–124</ref>

<ref>Hatchuel, Armand, Le Masson, Pascal, and Weil, Benoit. (2008) Studying creative design: the contribution of C-K theory. Studying design creativity: Design Science, Computer Science, Cognitive Science and Neuroscience Approaches, Aix-en-Provence, France, 10–11 March 2008</ref>.

<ref>ref name="RED2009">Hatchuel A. and Weil B., C-K design theory: An advanced formulation, Research in Engineering Design, 19(4):181–192, 2009</ref>

<ref>Template:Cite book</ref>

<ref name="RED2009" />.

C-K theory defines a brief as an incomplete description of objects that do not exist yet and are still partly unknown. The first step in C-K theory is to define a brief as a concept, through the introduction of a formal distinction between concept and knowledge spaces; the second step is to characterize the operators that are needed between these two spaces.

The knowledge space is defined as a set of propositions with a logical status, according to the knowledge available to the designer or the group of designers. The knowledge space (i.e. K-Space) describes all objects and truths that are established from the point of view of the designer. Then K-Space is expandable as new truths may appear in it as an effect of the design process. Conversely, the structure and properties of the K-Space have a major influence on the process. Thus in ship design there is a large body of knowledge touching upon, say, hull form, stability, and hydrodynamics, and the status or values of each of these items affect the values of the others.

A concept is then defined as a proposition without a logical status in the K-Space. A central finding of C-K theory is that concepts are the necessary departure point of a design process. Without concepts, design reduces to standard optimization or problem-solving. Concepts assert the existence of an unknown object that presents some properties desired by the designer. In ship design the concept might be a hull having a specified metacentric height and a specified resistance.

Building on these premises, C-K theory shows the design process as the result of four operators: C→K, K→C, C→C, K→K.

The initial concept is partitioned using propositions from K: K→C The laws of hydrodynamics add certain implications from the conepts stability.
These partitions add new properties to the concepts and create new concepts: C→C The concept (ship) takes on form and / or spawns variants.
Thanks to a conjunction C→K this expansion of C may in return provoke the expansion of the K space: K→K The generation of some variants, say for an example a multihuhll, will require additional knowledge of the laws of stability and resistance.

The process can be synthesized through a design square. One design solution for a first concept C0 will be a path in the C-space that forms a new proposition in K. There may exist several design paths for the same C0.

600px|center|The C-K Design Square

The following graphical representation summarises the design process using C-K theory. center|border|500px

Crazy concepts

Crazy concepts are concepts that seem absurd as an exploration path in a design process. Both C-K theory and practical applications have shown that crazy concepts can benefit the global design process by adding extra knowledge, not to be used to pursue that "crazy concept" design path, but to be used to further define a more "sensible concept" and lead to its eventual conjunction. The following image is a graphical representation of this process. border|500px|center

Design creativity

The creative aspect of Design results from two distinct expansions: C-expansions which may be seen as "new ideas", and K-expansions which are necessary to validate these ideas or to expand them towards successful designs<ref name="RED2009" />.

Unification of design theories

Domain dependent design theories are built on some specific structure of the K-space, either by assuming that some objects have invariant definitions and properties (as in all engineering fields), or by assuming that the K-space presents some stable structure (e.g. that the functions of an object can be defined independently from its technical realization, as in systematic design theory).

Theory of design

At The Design Society's 2009 International Conference on Engineering Design, an awarded-paper<ref>Shai, O; Reich, Y; Hatchuel, A; and Subrahmanian, E. (2009) Creativity Theories and Scientific Discovery: a Study of C-K Theory and Infused Design., International Conference on Engineering Design, ICED'09, 24–27 August 2009, Stanford CA.</ref> links scientific discovery and design process using C-K theory as a formal framework. It is suggested that a science of design is possible, and complementary to the more traditional bounded rationality.<ref name="simon">Hatchuel A. & Weil B. (2002), C-K Theory: Notions and Applications of a Unified Design Theory, Proceedings of the Herbert Simon International Conference on " Design Sciences ", Lyon: 22</ref>Template:Lopsided

Mathematical modelling

Mathematical approaches to design have been developed since the 1960s by scholars such as Christopher Alexander, Hiroyuki Yoshikawa, Dan Braha and Yoram Reich. They tended to model the dynamic co-evolution between design solutions and requirements. Within the field of engineering design, C-K theory opens new modelling directions that explore connections with basic issues in logic and mathematics; these are different from the classic use of scientific models in design. It has been argued<ref name="forcing2007">Template:Cite book</ref> that C-K theory has analogies with forcing in set theory, and with intuitionistic mathematics<ref name="kazakci2009">Kazakci, Akin, and Hatchuel, Armand,Is "creative subject" of Brouwer a designer? – an Analysis of Intuitionistic Mathematics from the Viewpoint of C-K Design Theory?, International Conference on Engineering Design, ICED'09, Stanford CA, 24–27 August 2009.</ref>.

Industrial applications

C-K theory has been applied in several industrial contexts since 1998, mainly in France, Sweden and Germany. It is generally used as a method that increases the innovative capacity of design and R&D departments.Template:Lopsided Template:Citation needed C-K theory has also inspired new management principles for collaborative innovation, with the aim of overcoming the limitations of standard design management methods.<ref>Hatchuel, A. ; Le Masson, P. and Weil, B. (2009) Design Theory and Collective Creativity: a Theoretical Framework to Evaluate KCP Process. International Conference on Engineering Design, ICED'09, 24–27 August 2009, Stanford CA.</ref><ref>Elmquist, M. and Segrestin, B. (2009). "Sustainable development through innovative design: lessons from the KCP method experimented with an automotive firm."</ref>

Models of Creative People (4pp)

We have seen what creativity is, and we have seen design through procedural and cognitive lenses. What, then, are the kinds of people who are capable of creativity and / or innovation?

Separate from models of creativity are studies of the types of individuals who show aptitude for creativity - and here again I will restrict this to engineering innovation.

Many engineers remember a bifurcation of their personal universe which took place in their teen years, when they discovered that their friends didn't share their love for math and science. We each learned that not every body could, or would, do math.

In the years that followed I have observed that even of those who can do math, not everybody can apply that math in the way that is needed for engineering analysis.

Continuing, it appears that there are a lot of excellent engineers, excellently skilled in engineering analysis, who can't do the problem backward and do engineering synthesis, which is what design is.

And of those who can do design, there are some who can't do the design-without-forebears that is innovation.

I hasten to state that this is not a value judgement, merely an observation. As an innovator myself, I am not a great mathematician. As an engineering designer myself, I greatly need good engineering analysts in my team. I am not saying that innovation is some sort of “higher” skill, just that it is a different skill.

My observation is that there exist individual differences in the aptitude for innovation, and this appears to be supported by the literature on this subject. Let me explore just a few of these.

Creativity versus Intelligence

First is the relationship between creativity and intelligence. It seems clear that there IS such a relationship, but it turns out that this relationship can not be described by the classic terms of necessary or sufficient.

Stahl (creativity) provides a discussion of this relationship when he analyzes student performance on a battery of creativity tests: "According to the literature, the relationship between intelligence and creativity is not a direct one (Getzels, 1969; Ebel, 1974). The creativity-gifted person is seen as being different from the intellectually- or academically-gifted-person (GTCEA, 1978; Torrance,' 1975). Torrance (1975) argues that to equate intellectual-giftedness with creativeness is to exclude nearly 3/4 of all highly creative children. And, while creativity may be a factor of intellectual giftedness, it is certainly not a prerequisite (Torrance, 1963).

"In view of the above, the finding that 70 percent of the children rated high in creativity would not have been selected as being intellectually-gifted should be perplexing to many educators. If creativity is loosely defined as "doing anything which is personally different and unique", then it is difficult to believe that 70 percent of the intellectually-gifted children do little that is new or unique. Furthermore, a liberal definition of creativity would require one to acknowledge that nearly three-fourths of the children who are highly creative are not very "smart". Both explanations seem somewhat absurd.

"In much the same vein, the relationship between intelligence (i.e., I.Q.) and creativity test scores is not a clear-cut one (Crockenberg, 1972; Torrance,1975; Ebel, 1974; Getzel, 1969). Low test scores and correlations provide no evidence that being intelligent disqualifies a person from being creative, or vice versa (Ebel, 1974). As long as I.Q. tests stress the measurement of convergent factual abilities and creativity tests are believed to reflect primarily divergent, non-factual recall responses, the controversy connected with the relationship between intelligence and creativity will continue.

Some authors have suggested that creativity is the inevitable result of a certain process. We have already rejected this hypothesis in our definition thus far. Stahl is again helpful to us:

"It seems appropriate to examine some consequences of adhering to the position that creativity is caused by distinct creative thinking processes. If such processes actually do exist, then we must accept the fact that inherent creativity rather than developed ability, opportunity, effort, intentions, task or career requirements, or circumstances, accounts for the unique behaviors and products achieved by so-called creative people. Efforts to explain the creativity of individuals in such divergent areas as art, science, architecture, literature, directed at identifying a single "cause" of all these creative behaviors have not been successful (Berelson and Steiner, 1.964; Taylor, 1975a,b). Interesting, there has yet to be identified a distinct activity, attribute, or process that is commonly shared by all recognized 'creative, persons which sets them all significantly(and I don't mean in the statistically hallowed sense of .05) apart from less-creative people.

"That these distinctions do not exist is supported by a list of characteristics or distinguishing features and attributes of gifted and talented individuals published by the Council for Exceptional Children - CEC (1978). (See Figures 1 and 2). In reference to the "creative characteristics" of gifted/talented children, the CEC points out that these characteristics "constitute observable behaviors that can be thought of as clues to more specific behaviors" to identify the creative person. Even in Figure 1 there is an implied cause-effect relationship between a type of thinking (e.g., 'fluent', 'flexible') and the described behaviors which follows. Here again, even the research and literature review by the CEC did not identify clearly distinguishable characteristics of either creative behaviors or so-called creative thinking processes."

What Stahl is thus giving us is that creativity is not the unavoidable offspring of intelligence. Cropley, in "Fostering Creativity in Engineering Undergraduates ()" states: "Apparently, creativity adds something to intelligence."

What we are being told is that there is an additional "something" that is added to intelligence to yield creativity. But what is that "something?" Let us continue to explore.

Figure 2

Creative Characteristics of The Gifted and Talented

Few gifted children will display all of these characteristics, while characteristics do not necessarily define who is a gifted child. They do constitute observable behaviors that can be thought of as clues to more specific behavior characteristics are Signals to indicate that a particular might warrant closer observation and could require specialized education & attention.

They are fluent thinkers, able to produce a large quantity of possibilities, consequences, or related ideas.

They are flexible thinkers, able to use many different alternatives and approaches to problem solving.

They are original thinkers, seeking new unusual, or unconventional associations and combinations among items of information.They also have an ability to see relationships among seemingly unrelated objects, ideas, or facts.

They are elaborative thinkers, producing new steps, responses, or other embellishments to a basic idea, problem, or situation.

They show a willingness to entertain complexity and seem to thrive in problem situations.

They are good guessers and can construct hypothesis or "what if" questions readily

They often are aware of their own impulsiveness and the irrationality within themselves and show emotional sensitivity.

They have a high level of curiosity about objects, ideas, situations, or events.

They often display intellectual playfulness, fantasize, and imagine readily.

They can be less intellectually inhibited than their peers, expressing opinions and ideas and often exhibiting spirited disagreement.

They have a sensitivity to beauty and are attracted to aesthetic dimensions

Taken from fact sheet prepared by the, Center for Exceptional Children (1978) pursuant to a USOE grant.

Creativity and Quality

In section 4.1.5 we argued that creativity is more than novelty. But again if it is more than "mere" novelty, then what is the "delta"? What is the element that must be added to "novelty" to yield "creativity?" We opine that this element is "quality." Quality is an essential component of creativitity.

Consider again Stahl's discussion of creativity tests. He says:

"An alternative interpretation would state that creativity tests measure a different dimension of convergent behavior which is one step removed from what the average or 'non-creative' person might provide in the same situation.

"This last explanation raises some intriguing possibilities. If some degree of correctness or quality is involved, then there must exist 'right' or 'proper' external criteria to assess what is supposed to be an internally produced divergent response. Current creativity tests measure a person's responses according to a predetermined scale or criterion for divergence. Hence, as it is currently viewed by many educators and researchers, high creativity test performance is the achievement of a different 'convergent response pattern' than that given by most other people.

"Crockenberg (1972) warns that educators too often (and all too rapidly) mistakenly equate the mere frequency of new and different responses or products with high levels of creativity. She strongly suggests that we avoid being heavily influenced by the mere multitude, elaborativeness, and/or attractiveness of so-called 'creative products' which so often have nothing to do with genuine creative thinking.

"Unless these ambiguities are clarified, then, carried to the extreme, class-room teachers, curriculum developers, and teacher educators will continue to believe that anything a person does in response to a problem or situation which is different, new and attractive, is to be judged 'creative'. If this loose definition is rejected, then some degree of correctness, accuracy, and/or quality is implied but rarely stated in most conceptualizations of creativity. If correctness or quality is involved, then there must exist a right or appropriate externally determined and measurable criteria for what is supposed to be a 'divergent' activity. Again, logic would suggest that creativity may be an extension or the next step beyond the convergent responses expected in the situation. This phenomenon may help to explain why many very new, "creative" responses are met by rapid acceptance by individuals on the brink of the same discovery.

"The fact that other people not only must recognize but also determine whether one's products are creative poses an interesting dilemma. It may well be that individuals have no problem whatsoever in generating new and unique behaviors and products. Rather, the problem arises when we find so little support and favor from others in connection with those novel things that we actually can do. As Ebel (1974) suggests, nearly all of our unique behaviors and products are ignored because few other people value them enough to mention them. Hence, built into the uniqueness must be externally demonstrable elements such as excellence, quality, appropriateness, and usefulness. The emphasis that promoters of creativity put on suspension of critical judgement, on complete openness to new ideas however bizarre; and mere numbers of novel alternatives may need to be reconsidered in light of these external criteria.

If creativity requires quality, and it is built upon a foundation of intelligence, thet it seems clear that expertise is included in the recipe as well. The final remark above pointed out that much of the creative quality requires recognition before it can be fruitful. Thus there is something more than expertise, it is recognized expertise.

This latter point was touched upon in UNO coursework on the nature of power in an organization. In this course we learned that innovation requires “swimming upstream", bucking the norms. How then does the innovator get the credibility to be listened to? One key is technical excellence, as per p. 292 "he's so blasted smart we have no choice.” Another aspect not mentioned in the text is for the innovator to show that he does under stand the corporate norms, but that he is suggesting to willfully and knowingly violate them, for some higher purpose. Too often I see young innovators whose ideas may be good, but who by their brashness communicate that they disrespect the corporate norms. These folks rarely suceed while they work in this mode. By contrast the seasoned innovator shows that he does understand, but that we ought to put aside those norms this time, for this reason… Indeed, often this seasoned innovator understands those norms better than her colleagues, because she has pulled them out of the background and studied them explicitly. We will see this principle again, under the label "metacognition."

[find my aside about expertise]

Creativity as a social product

We have seen that creativity, expecially engineering innovation, esists in a social or societal context. Further, it is well known that most engineering innovation takes place as the result of teamwork. Dr. Brian Uzzi has conducted interesting studies of the nature of successful and unsuccessful teams. In his work "Collaboration and Creativity: The Small World Problem" Briuan Uzzi & Janet Spiro, AJS Volume 111 no. 2 September 2005. ...

A very interesting discussion of a wide range of creativity was embodied in the New Yorker article "Brainstorming Doesn't Work" http://www.newyorker.com/reporting/2012/01/30/120130fa_fact_lehrer  This article includes a discussion of the right "chemistry" required in the creative team.  I'm not sure whether this fits into this present location in the dissertation, but in order to capture it I paste here a large excerpt from the article:

"Brian Uzzi, a sociologist at Northwestern, has spent his career trying to find what the ideal composition of a team would look like. Casting around for an industry to study that would most clearly show the effects of interaction, he hit on Broadway musicals. [...]"

"Uzzi sees musicals as a model of group creativity. “Nobody creates a Broadway musical by themselves,” he said. “The production requires too many different kinds of talent.” A composer has to write songs with a lyricist and a librettist; a choreographer has to work with a director, who is probably getting notes from the producers.

"Uzzi wanted to understand how the relationships of these team members affected the product. Was it better to have a group composed of close friends who had worked together before? Or did strangers make better theatre? He undertook a study of every musical produced on Broadway between 1945 and 1989. To get a full list of collaborators, he sometimes had to track down dusty old Playbills in theatre basements. He spent years analyzing the teams behind four hundred and seventy-four productions, and charted the relationships of thousands of artists, from Cole Porter to Andrew Lloyd Webber.

"Uzzi found that the people who worked on Broadway were part of a social network with lots of interconnections: it didn’t take many links to get from the librettist of “Guys and Dolls” to the choreographer of “Cats.” Uzzi devised a way to quantify the density of these connections, a figure he called Q. If musicals were being developed by teams of artists that had worked together several times before—a common practice, because Broadway producers see “incumbent teams” as less risky—those musicals would have an extremely high Q. A musical created by a team of strangers would have a low Q.

"Uzzi then tallied his Q readings with information about how successful the productions had been. “Frankly, I was surprised by how big the effect was,” Uzzi told me. “I expected Q to matter, but I had no idea it would matter this much.” According to the data, the relationships among collaborators emerged as a reliable predictor of Broadway success. When the Q was low—less than 1.7 on Uzzi’s five-point scale—the musicals were likely to fail. Because the artists didn’t know one another, they struggled to work together and exchange ideas. “This wasn’t so surprising,” Uzzi says. “It takes time to develop a successful collaboration.” But, when the Q was too high (above 3.2), the work also suffered. The artists all thought in similar ways, which crushed innovation. According to Uzzi, this is what happened on Broadway during the nineteen-twenties, which he made the focus of a separate study. The decade is remembered for its glittering array of talent—Cole Porter, Richard Rodgers, Lorenz Hart, Oscar Hammerstein II, and so on—but Uzzi’s data reveals that ninety per cent of musicals produced during the decade were flops, far above the historical norm. “Broadway had some of the biggest names ever,” Uzzi explains. “But the shows were too full of repeat relationships, and that stifled creativity.”

"The best Broadway shows were produced by networks with an intermediate level of social intimacy. The ideal level of Q—which Uzzi and his colleague Jarrett Spiro called the “bliss point”—emerged as being between 2.4 and 2.6. A show produced by a team whose Q was within this range was three times more likely to be a commercial success than a musical produced by a team with a score below 1.4 or above 3.2. It was also three times more likely to be lauded by the critics. “The best Broadway teams, by far, were those with a mix of relationships,” Uzzi says. “These teams had some old friends, but they also had newbies. This mixture meant that the artists could interact efficiently—they had a familiar structure to fall back on—but they also managed to incorporate some new ideas. They were comfortable with each other, but they weren’t too comfortable.”

"Uzzi’s favorite example of “intermediate Q” is “West Side Story,” one of the most successful Broadway musicals ever. In 1957, the play was seen as a radical departure from Broadway conventions, both for its focus on social problems and for its extended dance scenes. The concept was dreamed up by Jerome Robbins, Leonard Bernstein, and Arthur Laurents. They were all Broadway legends, which might make “West Side Story” look like a show with high Q. But the project also benefitted from a crucial injection of unknown talent, as the established artists realized that they needed a fresh lyrical voice. After an extensive search, they chose a twenty-five-year-old lyricist who had never worked on a Broadway musical before. His name was Stephen Sondheim. "

insert 2 figures from Uzzi

Measuring Innovation Aptitude

In the research completed thus far I have found one explicit attempt to measure innovation aptitude.

The Kirton Adaptor - Innovator Inventory (KAI) \citep{kirton1994, lopez2006} is a psychological test which returns a numerical indicator of where a person falls on a spectrum from Adaptor to Innovator. It is conceptually similar (but narrower in focus) to the popular Myers Briggs Type Indicator \citep{MBTI} that is already extensively used in DOD.

Kirton KAI inventory tool Michael Kirton, a renowned British psychologist, has developed an instrument known as the KAI (Kirton Adaption–Innovation) Inventory (4), which measures individual styles of problem definition and solving. An adaptor uses existing knowledge and procedures to solve problems by time-honoured techniques, while an innovator tends to look beyond what is given to solve problems in new ways. Style, in this case, refers to an adaptive, building, or analogic problem-solving style versus an innovative or pioneering style. Both skills are needed for organizational problem solving, but the differences often are not recognized or measured. One way to look at the KAI is as a measure of individuals’ relation to their problem-solving style, whereas the MBTI is more of a measure of individuals’ relation to their problem-solving style and social environment. In the list, “Characteristics of adaptors and innovators”, we summarize the two groups and how each group is viewed by its opposites.

Characteristics of adaptors and innovators

Adaptor Innovator Efficient, thorough, adaptable, methodical, organized, precise, reliable, dependable Ingenious, original, independent, unconventional Accepts problem definition Challenges problem definition Does things better Does things differently Concerned with resolving problems rather than finding them Discovers problems and avenues for their solutions Seeks solutions to problems in tried and understood ways Manipulates problems by questioning existing assumptions Reduces problems by improvement and greater efficiency, while aiming at continuity and stability Is catalyst to unsettled groups, irreverent of their consensual views Seems impervious to boredom; able to maintain high accuracy in long spells of detailed work Capable of routine work (system maintenance) for only short bursts; quick to delegate routine tasks Is an authority within established structures Tends to take control in unstructured situations

How the “other side” often sees extreme adaptors and innovators

Dogmatic, compliant, stuck in a rut, timid, conforming, and inflexible

Unsound, impractical, abrasive, undisciplined, insensitive, and one who loves to create confusion

A 32-item questionnaire is used to measure an individual’s problem-solving style on a scale from 32 to 160. A person with an adaptive style will usually score in the 60–90 range, whereas a person with an innovative style will score between 110 and 140. In reality, whether an individual portrays the characteristics of an adaptor or an innovator depends on context—where they are on the continuum relative to those with whom they interact. Persons with scores in the middle of a group have some of both characteristics, and under some circumstances, they can function as “bridgers”. This inventory has been found to be extremely accurate and has been globally validated across many cultures over decades (4, 5).

Hughes {hughes1994} conducted a limited scope correlation of MBTI scores with KAI scores, using a class of military officer students at the National Defense University. This study concluded that persons scoring EN_P on the MBTI were more innovative than others. However it is worth noting that the correlation with _N__ was substantially higher than the correlation with E___ or ___P. Thus I would restate Hughes conclusion as that Jungian Intuitives are more likely to be innovators than are the Jungian Sensors.

Characteristics of Team Leaders

NASA engineers Michael Ryschkewitsch,Dawn Schaible,and Wiley Larson, tackled this question directly in their 2009 paper "The Art and Science of System's Engineering"(file: Art_and_Sci_of_SE_LONG_1_20_09.pdf). This paper is an entire textbook in Systems Engineering in 22 pages, covering the systems engineering process, the procedural keys to success, and - relevant to our topic at hand - the required characteristics of a good systems engineering leader.

Their list of characteristics - reproduced in the list below - resonate strongly as the characteristics of a good inventor / innovator as well. Consider...{fill in}

Intellectual curiosity. This reflects the inventor's passion for asking "Why?" "Why" is a very important question in the context of invention and innovation - indeed I nearly titled this dissertation as "Engineering by asking "Why?"" "Why" is the question that provokes the engineer to even dream in the first place that there might be an answer other than the one that will be found by simple derivative evolution. "Why" is the question that provokes revolution.

Ability to see the big picture. This foreshadows the need to remember the real goal of the device being invented, and not to fall into the trap of sub-optimization. We will see this concept recur in many guises in the innovation algorithms in Section [[]]

Ability to make system-wide connections.
Exceptional two-way communicator. These two skills may relate to the ability to look far afield for solutions, such as using a patent database as a window into diverse industries, rather than sticking with the comfort of the 'home turf.

Strong team member and leader. Unfortunately this skill is not common among inventors, it is only common among _successful_ ones.

Comfortable with change.
Comfortable with uncertainty.

Proper paranoia. To my mind the most important aspect of this 'proper paranoia' is the important question "What could go wrong with this?" This question is a fundamental in all of engineering, but it becomes even more important when one is digressing from the tried-and--proven into a higher-risk solution. Just what _are_ those risks?

Diverse technical skills. Here again we see a skill related to breadth of knowledge, and the ability to incorporate solutions from other applications, finding the similarities to those applications and mapping them into the task at hand.

Self confidence and decisiveness.
Appreciate the value of process.

I ALSO BELIEVE THat the cognitive style of the person will affect his choice of preferred tool at each step of the process. I can imagine visual thinkers enjoying the visual analogies method, while lexical thinkers enjoy WordTree. This is a fruitful avenue of future research

Expertise as a Cognitive Skill

In Krathwohl (2002) there is proposed a two-dimensional tazxonomy of learning, that embraces a Knowledge axis and a Cognition axis. Krathwohl posits that progress along the dimension of the axis is related to maturity or experience or expertise - each simpler category being prerequisite to the next more complex one.

The Krathwohl taxonomy may explain some of the fundamental skills needed for engineering invention. As I have repeatedly stated "not everybody can do it." It seems to me - and this would be a fruitful avenue for future research - that one has to have progressed pretty far on the knowledge axis in the metacognitive realm, and pretty far along the Cognition axis into the Creative realm, for invention to be easy. This would be a fruitful topic for statistical study.

Krathwohl's Educational Taxonomy

Structure of the Knowledge Dimension of the Revised Taxonomy

A. Factual Knowledge - The basic elements that students must know to be acquainted with a discipline or solve problems in it.
- Aa. Knowledge of terminology
- Ab. Knowledge of specific details and elements
B. Conceptual Knowledge - The interrelationships among the basic elements within a larger structure that enable them to function together.
- Ba. Knowledge of classifications and categories
- Bb. Knowledge of principles and generalizations
- Bc. Knowledge of theories, models, and structures
C. Procedural Knowledge - How to do something; methods of inquiry, and criteria for using skills, algorithms, techniques, and methods.
- Ca. Knowledge of subject-specific skills and algorithms
- Cb. Knowledge of subject-specific techniques and methods
- Cc. Knowledge of criteria for determining when to use appropriate procedures
D. Metacognitive Knowledge - Knowledge of cognition in general as well as awareness and knowledge of one's own cognition.
- Da. Strategic knowledge
- Db. Knowledge about cognitive tasks, including appropriate contextual and conditional knowledge
- Dc. Self-knowledge

Structure of the Cognitive Process Dimension of the Revised Taxonomy

1.0 Remember - Retrieving relevant knowledge from long-term memory.
- 1.1 Recognizing
- 1.2 Recalling
2.0 Understand - Determining the meaning of instructional messages, including oral, written, and graphic communication.
- 2.11nterpreting
- 2.2 Exemplifying
- 2.3 Classifying
- 2.4 Summarizing
- 2.5 Inferring
- 2.6 Comparing
- 2.7 Explaining
3.0 Apply - Carrying out or using a procedure in a given situation.
- 3.1 Executing
- 3.2 Implementing
4.0 Analyze - Breaking material into its constituent parts and detecting how the parts relate to one another and to an overall structure or purpose.
- 4.1 Differentiating
- 4.2 Organizing
- 4.3 Attributing
5.0 Evaluate - Making judgments based on criteria and standards.
- 5.1 Checking
- 5.2 Critiquing
6.0 Create - Putting elements together to form a novel, coherent whole or make an original product.
- 6.1 Generating
- 6.2 Planning
- 6.3 Producing

Characteristics of Innovators

Conclusion: Innovators are experts. They are expert not only in their field, but in the field of metacognition and in the field of analyzing and critiquing.

The innovator understands the old system, and he can show that he respects its origins.

The innovator works in a team that is neither too isolated nor too cohesive.

The innovator is probably a Myers-Briggs "N" type.

Properly blended, these skills result in an engineer who can say "I understand why the old way works, but here is a new way that will work better."

Existing Models and Tools for Design Innovation (20pp)

The distinction between 'models of innovation' and 'algorithms for innovation' is difficult to find, because it appears that most authors who have studied innovation have done so with the goal of capturing an algorithm for it. The sole exception I have found thus far is \citet{myths}, who's express purpose was to define what innovation is {\it not} and thus what algorithms must fail.

Because of this melding I propose to combine the presentation of models of innovation and tools for innovation into a single component of the dissertation. This component will form the core of the eventual textbook, comprising say 60 to 70 percent of its volume.

Morris Kline, writing in Scientific American in March of 1955, wrote: {\it "The creative act owes little to logic or reason. In their accounts of the circumstances under which big ideas occurred to them, mathematicians have often mentioned that the inspiration had no relation to the work they happened to be doing. Sometimes it came while they were travelling, shaving, or thinking about other matters. The creative process cannot be summoned at will or even cajoled by sacrificial offering."}

Mr. Kline expresses a common belief about innovation and creativity. But a rigorous acceptance of this position might lead us to conclude that it is a fool's errand to attempt to teach creativity.

By contrast there is a growing body of work that disputes this conclusion, and that offers various explicit tools and algorithms for creativity. The following is a preliminary list of such techniques. Each of these techniques will be incorporated in teachable form into the Dissertation.

Note again that at this point I have narrowed down to discussing only engineering design innovation, and not art, literature, etc.

Good morning. I am overdue for a status report to you, so here goes:

Last semester I, frankly, got very little accomplished as I struggled with some math classes. This semester promises to be much more productive. Dr. David Singer at the University of Michigan gave me some excellent advice when he said “make a habit to write two hours a day, every day.” I have followed that advice and it is bearing fruit.

My task at this point is mostly to read, and digest the reading for its relevance to my thesis. I have a list of several hundred essays articles and books, and I am making my way through them. As I read each one, I generate notes on what it means to me, and I am collecting these notes in a modicum of order in a sort of ‘virtual manila folder.’

The virtual manila folder is actually on my website as : http://www.mckesson.us/mckwiki/index.php?title=NEW_COURSE_-_Innovation_in_Ship_Design (Note: Yahoo is having some SQL problems. If the website doesn’t open just check back later.) You are welcome to look at it, but please understand it as being little more than a pile of 3x5 cards at this point, which have not been woven together into a coherent work.

With that as the background, there is also some technical progress to report. I am homing in on what my contribution to the academic conversation is: Defining a taxonomy of invention algorithms. What I find is that invention algorithms (of which there are many) all share a certain architecture:

Define the ‘real’ problem Break the problem down Search left and right for parallel problems Inventory solutions to those parallel problems Map those solutions back to your domain Evaluate, Integrate, Iterate.

Each of the various algorithms uses it’s own terms and it’s own techniques for the steps. For example TRIZ uses the patent database to search for parallel solutions. WordTree uses a lexical technique, etc. But by understanding that each of the techniques is nevertheless adhering to a common meta-architecture, we gain tool flexibility:

Remember those toys for little children – toddlers – where you can flip pages and put, say, the head of a donkey upon the legs of a Kangaroo with the feet of a chicken? In similar fashion we may in some cases wish to put Martin Gardner’s problem breakdown techniques atop a biomimetic solution inventory. This would not be possible if we did not realize that the parts were functionally similar, and to some extent interchangeable.

Well, this is enough for one status report. AS always, this is only a snapshot of today’s thoughts. My reading continues and I’m sure my thoughts will continue to evolve. Your comments are MOST WELCOME, and I appreciate your interest and guidance.

Sincerely,

Chris McKesson

Osborn-Parnes Creative Problem Solving Process

Verbatim from the wikipedia:

The Creative Problem Solving Process (CPS), also known as the Osborn-Parnes CPS process, was developed by Alex Osborn (the inventor of brainstorming) and Dr. Sidney J. Parnes in the 1950s.<ref> Template:Cite web</ref> CPS is a structured method for generating novel and useful solutions to problems. CPS follows three process stages, which match a person's natural creative process, and six explicit steps:<ref>What is CPS?. Creative Education Foundation, 2010. Retrieved on 2010-06-13.</ref>

Process Stage	Steps
Explore the Challenge	Objective Finding (identify the goal, wish or challenge)
	Fact Finding (gather the relevant data)
	Problem Finding (clarify the problems that need to be solved in order to achieve the goal)
Generate Ideas	Idea Finding (generate ideas to solve the identified problem)
Prepare for Action	Solution Finding (move from idea to implementable solution)
Prepare for Action	Acceptance Finding (plan for action)

CPS is flexible, and its use depends on the situation. The steps can be (and often are) used in a linear fashion, from start to finish, but it is not necessary to use all the steps. For example, if one already has a clearly defined problem, the process would begin at Idea Finding.

What distinguishes the Osborn-Parnes CPS process from other "creative problem solving" methods is the use of both divergent and convergent thinking during each process step, and not just when generating ideas to solve the problem. Each step begins with divergent thinking, a broad search for many alternatives. This is followed by convergent thinking, the process of evaluating and selecting.

This method is taught at the International Center for Studies in Creativity,<ref> Template:Cite web</ref> the Creative Problem Solving Institute,<ref> Template:Cite web</ref> and CREA Conference.<ref> Template:Cite web</ref> It is specifically acknowledged as a key influence for the Productive Thinking Model.<ref>Template:Cite book</ref>

\subsubsection{The need for expert knowledge}

In learnbydoing the authors tell the story of a machine that failed when a certain part came through that happended to be light yellow in color. THis light yellow color was known by the operators to be a possibility, within the range of acceptable colors for the part in question, but it caused problems for the functioniing of the machine. It turns out that the machine builders had not know that light yellow was a possibility, and one of the machine's systems depending on the parts being greener in color.

While this is a negative example it might have some relevance in invention: Had the machine builders known that yellow was a possibility, they would have designed for it. In similar fashion I can imagine (need example) a situation where the inventor could have come up with something new, had he realized that ... was a possiblity. Öh if I'd only know that the widget was flexible I could have ..."

This might suggest that expert knowledge is essential - because how else can the inventor be expected to know everything there is to know about the widget? This of course is not a guarantee of inventive success, in fact the aurhors go on to cite several cases where "having all the knowledge" did not lead to success.

On the other hand the authors do suggest the user-knowledge is essential: At some level, and inventor needs to have done the task manually or used the process himself, in order to invent an improvement. This is apparently because some of the interactions in the design task are too complex to be explicitly stated, and must be learned by the cognitive neural network by experience and training, rather than by algorithmic education (my terms). The authors describe three methods to capture this complex information: Build a complex simulation, build a complex what-if tree, rely on human experience.

The authors also have a section in which they discuss the new problems that are created by the invention, but I am going to suggest that this (important) topic is outside the scope of this dissertation.

But what sor t of expert knowledge is needed? Popadiuk & Choo state: "Alavi and Leidner (2001) suggest different classification of knowledge depending on its use or usefulness. For example, according to Zack (1998), knowledge could be classified as procedural (know-how), causal (know-why), conditional (know-when), and relational (know-with). "

\subsubsection{Quintillian's Seven Questions}

Perhaps the earliest 'algorithm' for innovation was Quintillian's seven questions, published in the first century A.D. These were actually put forward as an algorithm for understanding, but understanding is clearly the first step in invention. (Einstein is quoted as saying "if you give me 20 days to solve a problem, I will spend the first 19 of them in problem definition.")

Quintillian's seven questions are: \begin{itemize} \item Who \item What \item Where \item With what \item Why \item How \item When \end{itemize}

\subsubsection{Mathematical Problem Solving:}

Martin Gardner, in "aha! Insight" \citep{aha} identified the following tools and techniques, writing about mathematical problems:

   Can the problem be reduced to a simpler case?
   Can the problem be transformed to an isomorphic one that is easier to solve?
   Can you invent a simple algorithm for solving the problem?
   Can you apply a theorem from another branch of mathematics?
   Can you check the result with good examples and counterexamples?
   Are there aspects of the problem that are actually irrelevant for the solution, and whose presence in the story serves to misdirect you?

Gardner's list of techniques resonates very strongly with me personally, perhaps because I first read Gardner's book when I was a boy of 13 years. And I note a great similarity between his list and my own tool box of techniques. For example Gardner's last point about 'irrelevant details' leads naturally to McKesson's embracing of Very Simple Models \citep{mckessonvsm2011a, mckessonvsm2011b}. And indeed, 'simple models' is Gardner's first rule. Further, Gardner's isomorphism rule leads naturally to the tool of teleological decomposition, discussed below.

\subsubsection{Teleological Decomposition}

Teleological decomposition is my own term for the principle of stepping back to remember the real purpose of the thing being designed. Consider the design of a ship rudder. In derivative design I start by looking at prior art and finding out what ship rudders look like. But if I start with teleology I would start by studying the purpose…: What is the purpose of a rudder? It is to give a ship Direction. Well, what are some of the other ways that things are given direction?

I look at airplanes and I see that they use things that look like rudders

I look at some recreational boats driven by outboard motors. They don'’t have rudders, they have combined rudder/propellers. But I looked also at the porpoise out in Monterey Bay, and they don'’t have a vertical fin. (Sharks do, fish do, porpoise don'’t). They have horizontal rudders. …I wonder why?

But there are still other methods: I once went on a VIP sea trial of a new ship, and watched as the Captain put her through her paces. Finally we docked at the pier and I complimented him on his shiphandling skills. His reply surprised me: "She'll do even better next week when we install the rudders." He had accomplished the entire outing steering only by differential thrust.

But my teleological study doesn't end there. Tired of the waterfront I go to the park and watch a boy throw a curve ball. …He simply generated boundary layer forces right on the body, with no appendage at all! Gee that might make a very interesting rudder, with no power requirement(?), with no “aft steering compartment”, no Special Sea and Anchor Detail. In fact, if I'’m trying to eliminate rudder-related systems, how about this one: …How about I just point the ship in the right direction to begin with?

My point isn'’t to lecture about how to steer ships. It is to lecture about how to decompose the problem by “peeling it back” from what we think the problem is, to what it really is. This is the technique that I call 'Teleological Decomposition.'

\subsubsection{ARI - Accelerated Radical Innovation}

One 'brand name' technique is "Accelerated Radical Innovation" \citep{ari2007} which provides methods aimed at shortening the innovation time, and thus avoiding loss of innovative momentum and initiative.

\subsubsection{TRIZ}

TRIZ \citep{triz} is a very interesting technique. It is the life work (40 years in development) of Genrik Altshuller. TRIZ is a Russian acronym for "Theory of Inventive Problem Solving." TRIZ includes the ARIZ, or Algorithm for Inventive Problem Solving.

Altshuller developed TRIZ by studying inventions - both successful and unsuccessful ones. His goal was to find out what made the difference.

In brief, the crux of TRIZ is that every invention is faced with some paradox: Make it stronger but lighter, make it transparent but bullet-proof, make it small but comprehensive. TRIZ states that the first key step is to identify the particular conflict(s) that dominate the problem at hand. Once a conflict is identified TRIZ then guides the inventor to express this conflict in terms that are not specific to any industry. Finally, by a lengthy analysis of successful inventions, Altshuller has assembled a stunning menu of candidate ways to resolve each type of generic conflict. The inventor then 'paws through' this menu of candidates until he makes his breakthrough.

"Method of Focal Objects" ref TRIZ book page 28

Brainstorming - see also TRIZ book page 27: Lateral Thinking and Synectics may be considered as special implementation of brainstorming.

TRIZ relies on the hypothesis that "the key to the solution to problems lies in the discovery and elimination of contradictions in the system," and "tactics and methods for solutions to problems can be created by analyzing important inventions."

Altshuller found that both the conflicts inherent in the problems and the "tactics and methods for solutions" could be simplified to a few dozen items of each sort. The inventor's task then is to correctly classify the contradiction in his particular problem, and then to find suitable solutions from the menu created by "analyzing important inventions."

The following text is taken verbatim from the Wikipedia and must be extensively edited before using the dissertation: [begin wikipedia excerpt]

TRIZ (Template:IPAc-en; Template:Lang-ru, Template:Transl) is "a problem-solving, analysis and forecasting tool derived from the study of patterns of invention in the global patent literature".<ref name="Hua">Template:Cite journal</ref> It was developed by the Soviet inventor and science fiction author Genrich Altshuller and his colleagues, beginning in 1946. In English the name is typically rendered as "the theory of inventive problem solving",<ref name="whatistriz">Template:Cite web</ref><ref name="Sheng1">Template:Cite journal</ref> and occasionally goes by the English acronym TIPS.

Following Altshuller's insight, the theory developed on a foundation of extensive research covering hundreds of thousands of inventions across many different fields to produce a theory which defines generalisable patterns in the nature of inventive solutions and the distinguishing characteristics of the problems that these inventions have overcome.

An important part of the theory has been devoted to revealing patterns of evolution and one of the objectives which has been pursued by leading practitioners of TRIZ has been the development of an algorithmic approach to the invention of new systems, and the refinement of existing ones.

The theory includes a practical methodology, tool sets, a knowledge base, and model-based technology for generating new ideas and solutions for problem solving. It is intended for application in problem formulation, system analysis, failure analysis, and patterns of system evolution.

There are three primary findings of this research. The first is that problems and solutions are repeated across industries and sciences, the second that patterns of technical evolution are also repeated across industries and sciences, and the third and final primary finding is that the innovations used scientific effects outside the field in which they were developed. In the application of TRIZ all these findings are<ref>http://www.triz-journal.com/whatistriz.htm</ref> applied to create and to improve products, services, and systems.

History

TRIZ in its classical form was developed by the Soviet inventor and science fiction writer Genrich Altshuller and his associates. He started developing TRIZ in 1946 while working in the "Inventions Inspection" department of the Caspian Sea flotilla of the Soviet Navy. His job was to help with the initiation of invention proposals, to rectify and document them and prepare applications to the patent office. During this time he realised that a problem requires an inventive solution if there is a unresolved contradiction in the sense that improving one parameter impacts negatively on another. He later called these “technical contradictions".

His work on what later resulted in TRIZ was interrupted in 1950 by his arrest and sentencing to 25 years in the Gulag. According to one source the arrest was partially triggered by letters which he and Raphael Shapiro sent to Stalin, ministers and newspapers about certain decisions made by the Soviet Government, which they believed were erroneous.<ref name="dotrubiog">Template:Cite web</ref> Altshuller and Shapiro were freed following Stalin's death in 1953<ref name=Salon1 /> and returned to Baku.

The first paper on TRIZ titled "On the psychology of inventive creation" was published in 1956 in "Issues in Psychology" (Voprosi Psichologii) journal.<ref name="1956VP">Template:Cite journal</ref>

By 1969 Altshuller had reviewed about 40,000 patent abstracts in order to find out in what way the innovation had taken place and developed the concept of technical contradictions, the concept of ideality of a system, contradiction matrix, and 40 principles of invention. In the years that followed he developed the concepts of physical contradictions, SuField analysis (structural substance-field analysis), standard solutions, several laws of technical systems evolution, and numerous other theoretical and practical approaches.

In 1971 Altshuller convinced The Inventors Society to establish in Baku the first TRIZ teaching facility called the Azerbaijan Public Institute for Inventive Creation and the first TRIZ research lab called The Public Lab for Inventive Creation. Altshuller was appointed the head of the lab by the society. The lab incubated the TRIZ movement and in the years that followed other TRIZ teaching institutes were established in all major cities of the USSR. In 1989 the TRIZ Association was formed, with Altshuller chosen as President.

Following the end of the cold war, the waves of emigrants from the former Soviet Union brought TRIZ to other countries and drew attention to it overseas.<ref name="Webb1">Template:Cite journal</ref> In 1995 the Altshuller Institute for TRIZ Studies was established in Boston, USA.

Basic principles of TRIZ

TRIZ presents a systematic approach for analysing the kind of challenging problems where inventiveness is needed and provides a range of strategies and tools for finding inventive solutions. One of the earliest findings of the massive research on which the theory is based is that the vast majority of problems that require inventive solutions typically reflect a need to overcome a dilemma or a trade-off between two contradictory elements. The central purpose of TRIZ-based analysis is to systematically apply the strategies and tools to find superior solutions that overcome the need for a compromise or trade-off between the two elements.

TRIZ process for creative problem solving

By the early 1970s two decades of research covering hundreds of thousands of patents had confirmed Altshuller’s initial insight about the patterns of inventive solutions and one of the first analytical tools was published in the form of 40 inventive principles, which could account for virtually all of those patents that presented truly inventive solutions. Following this approach the “Typical solution” shown in the diagram can be found by defining the contradiction which needs to be resolved and systematically considering which of the 40 principles may be applied to provide a specific solution which will overcome the “contradiction” in the problem at hand, enabling a solution that is closer to the “ultimate ideal result”.

The combination of all of these concepts together – the analysis of the contradiction, the pursuit of an ideal solution and the search for one or more of the principles which will overcome the contradiction, are the key elements in a process which is designed to help the inventor to engage in the process with purposefulness and focus.

One of the tools which evolved as an extension of the 40 principles was a contradiction matrix in which the contradictory elements of a problem were categorized according to a list of 39 factors which could impact on each other. The combination of each pairing of these 39 elements is set out in a matrix (for example, the weight of a stationary object, the use of energy by a moving object, the ease of repair etc.) Each of the 39 elements is represented down the rows and across the columns (as the negatively affected element) and based upon the research and analysis of patents: wherever precedent solutions have been found that resolve a conflict between two of the elements, the relevant cells in the matrix typically contain a sub-set of three or four principles that have been applied most frequently in inventive solutions which resolve contradictions between those two elements.

The main objective of the contradiction matrix was to simplify the process of selecting the most appropriate Principle to resolve a specific contradiction. It was the core of all modifications of ARIZ till 1973. But in 1973, after introducing the concept of physical contradictions and creating SuField analysis, Altshuller realized that the contradiction matrix was comparatively an inefficient tool and stopped working on it. Beginning ARIZ-71c contradiction matrix ceased to be the core of ARIZ and therefore was not a tool for solving inventive problems that Altshuller believed should be pursued. Physical contradictions and separation principles as well as SuField analysis, etc. became the core. Despite this, the 40 principles has remained the most popular tool taught in introductory seminars and has consistently attracted the most attention amongst the tens of thousands of individuals who visit TRIZ-focused web sites in a typical month. Therefore, many of those who learn TRIZ or have attended seminars are taught quite wrongly that TRIZ is primarily composed of the 40 principles and contradiction matrix, the truth is ARIZ is the core methodology of TRIZ.

ARIZ is an algorithmic approach to finding inventive solutions by identifying and resolving contradictions. This includes the "system of inventive standards solutions" which Altshuller used to replace the 40 principles and contradiction matrix, it consists of SuField modeling and the 76 inventive standards. A number of TRIZ-based computer programs have been developed whose purpose is to provide assistance to engineers and inventors in finding inventive solutions for technological problems. Some of these programs are also designed to apply another TRIZ methodology whose purpose is to reveal and forecast emergency situations and to anticipate circumstances which could result in undesirable outcomes.

One of the important branches of TRIZ is focused on analysing and predicting trends of evolution in the characteristics that existing solutions are likely to develop in successive generations of a system.

Essentials

Basic terms

Ideal final result (IFR) - the ultimate idealistic solution of a problem when the desired result is achieved by itself;
Administrative contradiction - contradiction between the needs and abilities;
Technical contradiction - an inverse dependence between parameters/characteristics of a machine or technology;
Physical contradiction - opposite/contradictory physical requirements to an object;
Separation principle - a method of resolving physical contradictions by separating contradictory requirements;
VePol or SuField - a minimal technical system consisting of two material objects (substances) and a "field". "Field" is the source of energy whereas one of the substances is "transmission" and the other one is the "tool";
FePol - a sort of VePol where "substances" are ferromagnetic objects;
Level of invention;
Standard solution - a standard inventive solution of a higher level;
Laws of technical systems evolution;
Algorithm of inventive problems solving (ARIZ), which combines various specialized methods of TRIZ into one universal tool;

Identifying a problem: contradictions

Altshuller believed that inventive problems stem from contradictions (one of the basic TRIZ concepts) between two or more elements, such as, "If we want more acceleration, we need a larger engine; but that will increase the cost of the car," that is, more of something desirable also brings more of something less desirable, or less of something else also desirable.

These are called technical contradictions by Altshuller. He also defined so-called physical or inherent contradictions: More of one thing and less of the same thing may both be desired in the same system. For instance, a higher temperature may be needed to melt a compound more rapidly, but a lower temperature may be needed to achieve a homogeneous mixture.

An inventive situation which challenges us to be inventive, might involve several such contradictions. Conventional solutions typically "trade" one contradictory parameter for another; no special inventiveness is needed for that. Rather, the inventor would develop a creative approach for resolving the contradiction, such as inventing an engine that produces more acceleration without increasing the cost of the engine.

Inventive principles and the matrix of contradictions

Altshuller screened patents in order to find out what kind of contradictions were resolved or dissolved by the invention and the way this had been achieved. From this he developed a set of 40 inventive principles and later a matrix of contradictions. Rows of the matrix indicate the 39 system features that one typically wants to improve, such as speed, weight, accuracy of measurement and so on. Columns refer to typical undesired results. Each matrix cell points to principles that have been most frequently used in patents in order to resolve the contradiction.

For instance, Dolgashev mentions the following contradiction: increasing accuracy of measurement of machined balls while avoiding the use of expensive microscopes and elaborate control equipment. The matrix cell in row "accuracy of measurement" and column "complexity of control" points to several principles, among them the Copying Principle, which states, "Use a simple and inexpensive optical copy with a suitable scale instead of an object that is complex, expensive, fragile or inconvenient to operate." From this general invention principle, the following idea might solve the problem: Taking a high-resolution image of the machined ball. A screen with a grid might provide the required measurement. As mentioned above, Altshuler abandoned this method of defining and solving "technical" contradictions in the mid 1980's and instead used SuField modeling and the 76 inventive standards and a number of other tools included in the algorithm for solving inventive problems, ARIZ

Laws of technical system evolution

Template:Main

Altshuller also studied the way technical systems have been developed and improved over time. From this, he discovered several trends (so called Laws of Technical Systems Evolution) that help engineers predict what the most likely improvements that can be made to a given product are. The most important of these laws involves the ideality of a system.

Substance-field analysis

One more technique that is frequently used by inventors involves the analysis of substances, fields and other resources that are currently not being used and that can be found within the system or nearby. TRIZ uses non-standard definitions for substances and fields. Altshuller developed methods to analyze resources; several of his invention principles involve the use of different substances and fields that help resolve contradictions and increase ideality of a technical system. For instance, videotext systems used television signals to transfer data, by taking advantage of the small time segments between TV frames in the signals.

SuField analysis produces a structural model of the initial technological system, exposes its characteristics, and with the help of special laws, transforms the model of the problem. Through this transformation the structure of the solution that eliminates the shortcomings of the initial problem is revealed. SuField analysis is a special language of formulas with which it is possible to easily describe any technological system in terms of a specific (structural) model. A model produced in this manner is transformed according to special laws and regularities, thereby revealing the structural solution of the problem.

ARIZ - algorithm of inventive problems solving

ARIZ (Russian acronym of алгоритм решения изобретательских задач - АРИЗ) (algorithm of inventive problems solving) is a list of about 85 step-by-step procedures to solve complicated invention problems, where other tools of TRIZ alone (Sufield analysis, 40 inventive principles, etc.) are not sufficient.

Various TRIZ software (see invention machine, ideation international) is based on this algorithm (or an improved one).

Starting with an updated matrix of contradictions, semantic analysis, subcategories of inventive principles and lists of scientific effects, some new interactive applications are other attempts to simplify the problem formulation phase and the transition from a generic problem to a whole set of specific solutions.

(see External links for details)

Use of TRIZ methods in industry

It has been reported that car companies Ford and Daimler-Chrysler, Johnson & Johnson, aeronautics companies Boeing, NASA, technology companies Hewlett Packard, Motorola, General Electric, Xerox, IBM, LG, Samsung, Procter and Gamble and Kodak have used TRIZ methods in some projects.<ref name="Salon1">Template:Cite news</ref><ref name="BBW1">Template:Cite news</ref><ref name="BBW2">Template:Cite news</ref><ref name="CNN1">Template:Cite news</ref>

Books on TRIZ by Altshuller

cite book

| last = Altshuller
| first = Genrich
| year = 1999
| title = The Innovation Algorithm: TRIZ, systematic innovation, and technical creativity
| location = Worcester, MA
| publisher = Technical Innovation Center
| isbn = 0964074044

cite book

| last = Altshuller
| first = Genrich
| year = 1984
| title = Creativity as an Exact Science
| location = New York, NY
| publisher = Gordon & Breach
| isbn = 0-677-21230-5

cite book

| last = Altshuller
| first = Genrich
| year = 1994
| title = And Suddenly the Inventor Appeared
| others = translated by Lev Shulyak
| location = Worcester, MA
| publisher = Technical Innovation Center
| isbn = 0-9640740-1-X

[end wikipedia excerpt]

I would be interested to research objections to TRIZ. My initial reading of the TRIZ literature has left me very enthusiastic for this method as both model and technique of invention. But if it is as good as all that, why isn't it more widely known?

\subsubsection{Brainstorming}

The reader may have thought of the topic of brainstorming while reading my summary of TRIZ. The techniques do have some similarities. The major difference is that TRIZ is very focused and formalized, while Brainstorming is very loose and general-purpose. However they have an essential similarity in that Brainstorming offers a technique for looking far and wide for solutions to a given challenge.

from: http://www.newyorker.com/reporting/2012/01/30/120130fa_fact_lehrer?currentPage=all

"In the late nineteen-forties, Alex Osborn, a partner in the advertising agency B.B.D.O., decided to write a book in which he shared his creative secrets. At the time, B.B.D.O. was widely regarded as the most innovative firm on Madison Avenue. Born in 1888, Osborn had spent much of his career in Buffalo, where he started out working in newspapers, and his life at B.B.D.O. began when he teamed up with another young adman he’d met volunteering for the United War Work Campaign. By the forties, he was one of the industry’s grand old men, ready to pass on the lessons he’d learned. His book “Your Creative Power” was published in 1948. An amalgam of pop science and business anecdote, it became a surprise best-seller. Osborn promised that, by following his advice, the typical reader could double his creative output. Such a mental boost would spur career success—“To get your foot in the door, your imagination can be an open-sesame”—and also make the reader a much happier person. “The more you rub your creative lamp, the more alive you feel,” he wrote.

“Your Creative Power” was filled with tricks and strategies, such as always carrying a notebook, to be ready when inspiration struck. But Osborn’s most celebrated idea was the one discussed in Chapter 33, “How to Organize a Squad to Create Ideas.” When a group works together, he wrote, the members should engage in a “brainstorm,” which means “using the brain to storm a creative problem—and doing so in commando fashion, with each stormer attacking the same objective.” For Osborn, brainstorming was central to B.B.D.O.’s success. Osborn described, for instance, how the technique inspired a group of ten admen to come up with eighty-seven ideas for a new drugstore in ninety minutes, or nearly an idea per minute. The brainstorm had turned his employees into imagination machines.

The book outlined the essential rules of a successful brainstorming session. The most important of these, Osborn said—the thing that distinguishes brainstorming from other types of group activity—was the absence of criticism and negative feedback. If people were worried that their ideas might be ridiculed by the group, the process would fail. “Creativity is so delicate a flower that praise tends to make it bloom while discouragement often nips it in the bud,” he wrote. “Forget quality; aim now to get a quantity of answers. When you’re through, your sheet of paper may be so full of ridiculous nonsense that you’ll be disgusted. Never mind. You’re loosening up your unfettered imagination—making your mind deliver.” Brainstorming enshrined a no-judgments approach to holding a meeting.

Brainstorming was an immediate hit and Osborn became an influential business guru, writing such best-sellers as “Wake Up Your Mind” and “The Gold Mine Between Your Ears.” Brainstorming provided companies with an easy way to structure their group interactions, and it became the most widely used creativity technique in the world. It is still popular in advertising offices and design firms, classrooms and boardrooms. “Your Creative Power” has even inspired academic institutes, such as the International Center for Studies in Creativity, at Buffalo State College, near where Osborn lived. And it has given rise to detailed pedagogical doctrines, such as the Osborn-Parnes Creative Problem Solving Process, which is frequently employed by business consultants. When people want to extract the best ideas from a group, they still obey Osborn’s cardinal rule, censoring criticism and encouraging the most “freewheeling” associations. At the design firm IDEO, famous for developing the first Apple mouse, brainstorming is “practically a religion,” according to the company’s general manager. Employees are instructed to “defer judgment” and “go for quantity.”

The underlying assumption of brainstorming is that if people are scared of saying the wrong thing, they’ll end up saying nothing at all. The appeal of this idea is obvious: it’s always nice to be saturated in positive feedback. Typically, participants leave a brainstorming session proud of their contribution. The whiteboard has been filled with free associations. Brainstorming seems like an ideal technique, a feel-good way to boost productivity. But there is a problem with brainstorming. It doesn’t work.

The first empirical test of Osborn’s brainstorming technique was performed at Yale University, in 1958. Forty-eight male undergraduates were divided into twelve groups and given a series of creative puzzles. The groups were instructed to follow Osborn’s guidelines. As a control sample, the scientists gave the same puzzles to forty-eight students working by themselves. The results were a sobering refutation of Osborn. The solo students came up with roughly twice as many solutions as the brainstorming groups, and a panel of judges deemed their solutions more “feasible” and “effective.” Brainstorming didn’t unleash the potential of the group, but rather made each individual less creative. Although the findings did nothing to hurt brainstorming’s popularity, numerous follow-up studies have come to the same conclusion. Keith Sawyer, a psychologist at Washington University, has summarized the science: “Decades of research have consistently shown that brainstorming groups think of far fewer ideas than the same number of people who work alone and later pool their ideas.”

"In 2003, Charlan Nemeth, a professor of psychology at the University of California at Berkeley, divided two hundred and sixty-five female undergraduates into teams of five. She gave all the teams the same problem—“How can traffic congestion be reduced in the San Francisco Bay Area?”—and assigned each team one of three conditions. The first set of teams got the standard brainstorming spiel, including the no-criticism ground rules. Other teams—assigned what Nemeth called the “debate” condition—were told, “Most research and advice suggest that the best way to come up with good solutions is to come up with many solutions. Freewheeling is welcome; don’t be afraid to say anything that comes to mind. However, in addition, most studies suggest that you should debate and even criticize each other’s ideas.” The rest received no further instructions, leaving them free to collaborate however they wanted. All the teams had twenty minutes to come up with as many good solutions as possible.

The results were telling. The brainstorming groups slightly outperformed the groups given no instructions, but teams given the debate condition were the most creative by far. On average, they generated nearly twenty per cent more ideas. And, after the teams disbanded, another interesting result became apparent. Researchers asked each subject individually if she had any more ideas about traffic. The brainstormers and the people given no guidelines produced an average of three additional ideas; the debaters produced seven.

Nemeth’s studies suggest that the ineffectiveness of brainstorming stems from the very thing that Osborn thought was most important. As Nemeth puts it, “While the instruction ‘Do not criticize’ is often cited as the important instruction in brainstorming, this appears to be a counterproductive strategy. Our findings show that debate and criticism do not inhibit ideas but, rather, stimulate them relative to every other condition.” Osborn thought that imagination is inhibited by the merest hint of criticism, but Nemeth’s work and a number of other studies have demonstrated that it can thrive on conflict.

According to Nemeth, dissent stimulates new ideas because it encourages us to engage more fully with the work of others and to reassess our viewpoints. “There’s this Pollyannaish notion that the most important thing to do when working together is stay positive and get along, to not hurt anyone’s feelings,” she says. “Well, that’s just wrong. Maybe debate is going to be less pleasant, but it will always be more productive. True creativity requires some trade-offs.”"

The article goes on to show that suspending the "no criticism" rule actually makes the brainstorming much more productive.

It is my opinion that this increased productivity is because it allows the brainstorming team to do more of the steps of the full creative process. THe morphology described in this dissertation includes "generate ideas" followed by "apply ideas" and "evaluate implementation." In effect the criticism step in modified brainstorm will result in attempts to apply and evaluate the idea, not merely generate them. THus, in my opinion, rather than pursuing the asymptote on a single step of the process, it is more worthwhile to get the 80% solution to multiple steps of the process - i.e. to include the apply and evaluate steps.

ALso need: Rotational brainstorming

Also need: 6-3-5

Morphological Analysis

Template:COI Morphological Analysis or General Morphological Analysis is a method developed by Fritz Zwicky (1967, 1969) for exploring all the possible solutions to a multi-dimensional, non-quantified problem complex.<ref name = "GMA">Ritchey, T. (1998). General Morphological Analysis: A general method for non-quantified modeling.</ref>

General Morphology was developed by Fritz Zwicky, the Bulgarian-born, Swiss-national astrophysicist based at the California Institute of Technology. Among others, Zwicky applied Morphological Analysis (MA) to astronomical studies and the development of jet and rocket propulsion systems. As a problem-structuring and problem-solving technique, MA was designed for multi-dimensional, non-quantifiable problems where causal modeling and simulation do not function well, or at all. Zwicky developed this approach to address seemingly non-reducible complexity: using the technique of cross-consistency assessment (CCA) (Ritchey, 1998), the system allows for reduction by identifying the possible solutions that actually exist, eliminating the illogical solution combinations in a grid box rather than reducing the number of variables involved. A detailed introduction to morphological modeling is given in Ritchey (2002, 2006).

Consider a complex, real-world problem, like those of marketing or making policies for a nation, where there are many governing factors, and most of them cannot be expressed as numerical time series data, as one would like to have for building mathematical models.

The conventional approach here would be to break the system down into parts, isolate the vital parts (dropping the 'trivial' components) for their contributions to the output and solve the simplified system for creating desired models or scenarios. The disadvantage of this method is that real-world scenarios do not behave rationally: more often than not, a simplified model will break down when the contribution of the 'trivial' components becomes significant. Also, importantly, the behaviour of many components will be governed by the states of, and their relations with, other components – ones that may be seen to be minor before the analysis.

Morphological Analysis, on the other hand, does not drop any of the components from the system itself, but works backwards from the output towards the system internals.<ref>Modelling Complex Socio-Technical Systems Using Morphological Analysis (Ritchey 2003-06)[1]</ref> Again, the interactions and relations get to play their parts in MA and their effects are accounted for in the analysis.

Ritchey, T. (2011) Wicked Problems/Social Messes: Decision support Modelling with Morphological Analysis. Berlin: Springer.
Zwicky, F. (1969). Discovery, Invention, Research - Through the Morphological Approach. Toronto: The Macmillian Company.
Zwicky, F. & Wilson A. (eds.) (1967). New Methods of Thought and Procedure: Contributions to the Symposium on Methodologies. Berlin: Springer.

\subsubsection{Muda}

Muda is a Japanese word made popular by Dr. Amory Lovins of the Rocky Mountain Institute \citep{rmi}. Muda is often defined as “waste” but it is actually something much more subtle than that.

Muda is “that for which there is no customer.”

Pause for a moment and reflect on how that'’s different from waste. From an engineering point of view the big difference is that this definition introduces new ways of dealing with it. With “waste”, we want simply to minimize the waste. But with muda we get a second choice. We can get rid of it, or we can find a customer for it. We can redefine it so that it’s not waste any more.

Waste-heat recovery systems are a well-proven example of eliminating muda - the heat is no longer 'waste.'

Marcus Aurelius, in the "MEDITATIONS" 4.24, writes: "The majority of things being unnecessary, always ask yourself 'is this one of the necessary things?'"

The lightest piping system, or machinery component, or choice of deck machinery, is the one that is absent. And in many cases (but not all!) these will also be the cheapest systems too - the cheapest anchor is none at all....unless the cost of beaching the ship is high.

So when trying to remove weight or cost (or carbon footprint or human resources or...) from a ship, a very powerful tool for that reduction is to entirely eliminate components of the ship.

Incremental improvements in such components go the other direction: Reducing the weight of a piping system can dramatically INCREASE the cost of the pipe. But eliminating the pipe completely certainly eliminates the cost of the pipe. The remaining question is whether it raises the cost of something else.

A more radical image of ship-muda might be to consider the crew. Unlike in the days of sail the propulsion of a modern ship does not require human muscle. And if the ship is a cargo ship then her mission is to carry freight, not people. Transporting 20 seamen on a tour of the planet is Muda - That for which there is no customer.

So can we eliminate the muda? Can we eliminate the crew? With satellite datalinks and redundant software could we not build a remotely operated ship? Having done so we would find a cascade of benefit: Eliminating the crew eliminates the galley, the stores, the sewage plant, the potable water plant, much of the HVAC system... It might even change the hull design and structural loads, since the machine's tolerances may be very different from the man's.

Eliminating the Muda of 'world tours for sailors' might result in a radically innovative ship.

\subsubsection{Multitasking}

In a 10,000 teu container ship, there is more steel in the containers than there is in the ship.

To me this says raises the question, as long as all those tons of containers are there anyway, can'’t I use them to hold the ship together?” What would it take to re-design the container ship paradigm such that it relied on the container itself for strength? I have a lot of ideas on this one, but let'’s just take it as an example. How about something less exotic:

How about using the pipes in the ship in a structural role. Why don't I rely on the firemain, bilge and ballast system, heating ventilating and air conditioning ducts, and other distributive systems to contribute to a ship'’s longitudinal bending strength?

In a ship design, taking advantage of those tons of pipes and ducts might take a few tons of steel out of the structure elsewhere, and those few tons of steel can be replaced by a few tons of bullets, bombs, or beans.

But this doesn'’t have to be just about structure, or just about weight. It is about reliability redundancy and cost too.

Fo’r instance, what if I used the conductive steel structure of the ship to carry data? Or power? Before you laugh remember that that'’s how your car is wired. The DC return leg in your car is the structural frame itself. This, in one fell swoop, cuts in half the number of wires that are run.

\subsubsection{Design By Analogy}

MOVE THIS TO THE DISCUSSION OF "BASIC" DESIGN METHODS

Design by analogy is properly a class of techniques, and not a single technique.

Design by analogy refers to the process of finding analogs to the present problem, wither within the present domain or outside it. When defined in this way it may be noted that conventional design - non-inventive design - is design by analogy, where the analog lies quite close to the project at hand. Indeed, conventional derivative design may be considered as design by analogy.

The task then in our sense of inventive design is to cast the net of analogy wider, and take in analogs that are not close to our particular problem, and potentially not even within our design domain.

Linsey \citep{linsey} (2008 - filename: DTM08_WordTree_Cntrl_Linsey.pdf) describes this very nicely:

"design. Professional designers often use analogies [3,4,5]. Unlike biologists who mainly use analogies within their domain, engineers employ cross-domain analogies in their design process [5]. This finding is based on protocol analysis of design team’s conversations during conceptual design. Design teams also frequently use close-domain analogies in the form of references to past designs [6]. Eckert, et al. found designers use references to previous designs for more than just conceptual design. Designers also use past designs in a number of other phases of the design process including process planning, cost estimation, and evaluation of concepts for a new product.

"A few controlled experiments have explored the use of analogy within design. Casakin and Goldschmidt [3] found that visual analogies can improve design problem solving for both novice and expert architects. Visual analogy had a greater impact for novices as compared to experts. Ball, Ormerod, and Morley [7] investigated the spontaneous use of analogy with engineers. They found experts use significantly more analogies than novices do. The type of analogies used by experts was significantly different from the type used by novices. Novices tended to use more case-driven analogies (analogies where a specific concrete example was used to develop a new solution) rather than schema-driven analogies (more general design solution derived from a number of examples). This difference can be explained because novices have more difficulty retrieving relevant information when needed and have more difficulty mapping concepts from disparate domains due to a lack of experience [8]."

There are several tools for this.

In \citep{linsey} Linsey develops a particular case of design by analogy using semantic analogs. Linsey's most entertaining example is the challenge of designing a self-cleaning cat litter box, where the analogies were panning for gold, and dump trucks. These analogies then serve as seed for the engineer to study, say, gold panning, and see if its principles can be applied to the cat box problem. Linsey goes on to develop a lexical technique for finding these analogies, by creating what she calls a 'word tree.' Word tree is sufficiently mature to deserve its own entry in this list, as follows.

WordTree

First, let us note that the WordTree method is a method specifically for finding analogies, and not for the full scope of inventive design. IT thus addresses only one portion of the invention morphology that will be developed below. However, this is a mature and well-documented method in its own right and deserves to be considered in this foundational discussion.

Linsey describes WordTree as follows: file: DTM08_WordTree_Cntrl_Linsey.pdf

"The WordTree Design-by-Analogy Method systematically re-represents a design problem, assisting the designer in identifying analogies and analogous domains. Figure 1 overviews the method’s steps. For a detailed example illustrating the method see [24]. The method begins by identifying the “problem descriptors” which are the key functions and customer needs. These are then linguistically rerepresented in a diagram know as a WordTree (Figure 2). Next potential analogies and analogous domains are identified. The potential analogies are researched and the analogous domains are used to find solutions in distant domains. New problem statements ranging from very domain specific in multiple domains to very general statements are written. Finally the analogies, patents, analogous domains and new problem statement are implemented in a group idea generation session. This session further refines the method’s results into conceptual solutions to the design problem and provides additional inspiration for the designers."

"This WordTree method begins by defining the Key Problem Descriptors. The key problem descriptors are single word action verbs derived from the functions and customer needs for the design problem. Prior research found that transitive verb, which are action verbs, are more effective stimulus for idea generation [27]. The Key Problem Descriptors are defined from the customer needs, mission statement, function structure and black box model. Key Problem Descriptors fall into a few categories. One set describes the overall function of the device with a single word. The next category is the critical or difficult functions to solve, and the final category is the important customer needs transformed into single action verbs. Normally the customer needs are a combination of an adjective and a noun. To be used in the WordTree Method, they must be converted to equivalent verbs. For example, the verb form of the customer need of “easy to repair” is “repair”.

The next step is to re-represent the key problem descriptors using WordTrees. This step facilitates the identification of analogies and analogous domains. The first, the design team uses rotational brainstorming to create sticky note WordTrees. Rotational brainstorming is very similar to 6-3-5 except that each team member receives three separate sheets of paper and develops one WordTree on each sheet. A rotational brainwriting method was chosen since a prior group idea generation experiment showed this type of approach results in a greater number of ideas [28].

After potential analogies and analogous domain have been identified, the analogies are researched along with searching for solutions in analogous domains. Google Image© is an effective and efficient tool for finding information about a potential analogy. Patents in analogous domains should be searched for also. Design fixation is a potential risk anytime a solution is presented to a designer. The search results have the potential to cause fixation but prior experimental results suggest it is unlikely for this method. Searching for analogies and patents in analogous domains can be completed prior to the teams attempting idea generation because it has been shown that uncommon solution, which is the type of solutions analogies should provide, tend to increase the number of ideas generated and not cause fixation [29,30]. Common solutions were defined as the solutions designers think of most frequently for a given problem.

Finally the teams use the results to generate more ideas. Two separate teams of designers are recommended to base their idea generation sessions on the results from the WordTree Method. The first team is the original team who generated the WordTree and knows the details of the design problem. The second team is unfamiliar with the problem and is given the general and alternative domain problem statements along with general and alternative domain words. When using analogies, individuals tend to focus too much on the surface and unimportant features of the problem rather than the causal structure [31,32]. It is believed, the second team will be less likely to focus on unimportant features of the original design problem since they will be shown a series or analogous problems which will tend to focus them on the deep structure and not the surface information. After team idea generation, the results are summarized using any number of methods such as morph matrixes or mind maps. The team then continues with the design process and moves to idea selection. "

WordTree rings true in a personal anecdote: I have a daughter who has an uncanny aptitude to taking things apart and fixing them. This is not a result of any formal training, indeed her field of study is social history. In conversation with her she has told me that her aptitude is the result of a family habit during her childhood: We took words apart at the dining room table. When in her childhood her college-educated parents would use a word that was not in her vocabulary, we would not then tell the kids the meaning of the word, but we would work with them to dissect the word, finding it's roots, finding its similarities to other words that they did know.

Kate tells me that she learned to fix machines via this same principal.

Taking this as a sort of primitive experiment in engineering skills suggests an interesting relation between lexical and mechanical thinking.

Note also that the word tree identifies the opportunity for analogy by a method very similar to the next item on my list.

\subsubsection{Synonyms, Antonyms and Homonyms}

The simple act of defining a problem's synonyms, antonyms, and homonyms can be a very powerful tool for identifying analogies and alternative solutions.

As mentioned, this is very close to the Word Tree method documented by Linsey et al \citep{linsey}.

The synonyms component helps to identify alternative solutions that are used in other industries, such as pursuing the similarlities between a ship rudder and a car's steering axle.

Antonyms can shed light on the problem in a reverse sort of way: The antonym of course identifies what the problem is not. But if we then attend to people attempting to design the anti-solution, we may find that their challenges are our opportunities. To continue the rudder analogy - the antonym of a rudder is directional stability. So perhaps a study of those things that are a problem for directional stability would identify a few candidates that might be made into ship-steerers?

Homonyms are those things that 'sound like.' The use of homonyms is two fold: It provokes wild-hare brainstorming ("Is there anything similar between Rudders and Udders? I doubt it!") and it may also help to identify other red herrings: Just because something sounds like a rudder doesn't necessarily mean it has relevance to our problem.

Personally I find the homonyms the least useful of these methods, but I take that as a result of my novitiate, and not as a limitation of the method.

Visual Analopies

Synectics

Verbatim cut from Wikipedia:

Synectics is a problem solving methodology that stimulates thought processes of which the subject may be unaware. This method was developed by George M. Prince (April 5, 1918 - June 9, 2009)<ref name="obit">George Prince, consultant who sparked innovation, founded international firm, Boston Globe, June 21, 2009</ref> and William J.J. Gordon, originating in the Arthur D. Little Invention Design Unit in the 1950s. They set up Synectics Inc. (now Synecticsworld) in 1960<ref>Synecticsworld</ref> and the methodology has evolved substantially in the ensuing 50 years.

History

The process was derived from tape-recording (initially audio, later video) of thousands of meetings, analysis of the results and experiments with alternative ways of dealing with the obstacles to success in the meeting. "Success" was defined as getting a creative solution that the group was committed to implement. This history of sustained research and development provides a scientific foundation for the Synectics body of knowledge.

The name Synectics comes from the Greek and means "the joining together of different and apparently irrelevant elements."<ref> Gordon, William J.J. Synectics: The Development of Creative Capacity. (New York: Harper and row, Publishers, 1961), 3). </ref>

Gordon and Prince named both their practice and their new company Synectics, which can cause confusion as people not part of the company are trained and use the practice. While the name was trademarked, it has become a standard word for describing creative problem solving in groups.<ref> Nolan, Vincent. "Whatever Happened to Synectics?" Creativity and Innovation Management, v. 21 n.1 (2003): 25. </ref>

Synectics as a practice continues to evolve.

Theory

Synectics is a way to approach creativity and problem-solving in a rational way. "Traditionally, the creative process has been considered after the fact... The Synectics study has attempted to research creative process in vivo, while it is going on." <ref> Gordon, 3 </ref>

According to Gordon, Synectics research has three main assumptions:

The creative process can be described and taught;
Invention processes in arts and sciences are analogous and are driven by the same "psychic" processes;
Individual and group creativity are analogous.<ref>Gordon, 5.</ref>

With these assumptions in mind, Synectics believes that people can be better at being creative if they understand how creativity works.

One important element in creativity is embracing the seemingly irrelevant. Emotion is emphasized over intellect and the irrational over the rational. Through understanding the emotional and irrational elements of a problem or idea, a group can be more successful at solving a problem.<ref> Gordon, 6.</ref>

Prince emphasized the importance of creative behaviour in reducing inhibitions and releasing the inherent creativity of everyone. He and his colleagues developed specific practices and meeting structures which help people to ensure that their constructive intentions are experienced positively by one another. The use of the creative behaviour tools extends the application of Synectics to many situations beyond invention sessions (particularly constructive resolution of conflict).

Gordon emphasized the importance of Template:"'metaphorical process' to make the familiar strange and the strange familiar". He expressed his central principle as: "Trust things that are alien, and alienate things that are trusted." This encourages, on the one hand, fundamental problem-analysis and, on the other hand, the alienation of the original problem through the creation of analogies. It is thus possible for new and surprising solutions to emerge.

As an invention tool, Synectics invented a technique called "springboarding" for getting creative beginning ideas. For the development of beginning ideas, the method incorporates brainstorming and deepens and widens it with metaphor; it also adds an important evaluation process for Idea Development, which takes embryonic new ideas that are attractive but not yet feasible and builds them into new courses of action which have the commitment of the people who will implement them.

Synectics is more demanding of the subject than brainstorming, as the steps involved mean that the process is more complicated and requires more time and effort. It is also much more rewarding because the end product is action not just ideas.

Books

The Practice of Creativity by George Prince 1970 (out of print)
Synectics: The Development of Creative Capacity by W.J. Gordon (possibly out of print)
Design Synectics: Stimulating Creativity in Design by Nicholas Roukes, Published by Davis Publications, 1988
The Innovators Handbook by Vincent Nolan 1989 (out of print)
Creativity Inc.: Building an Inventive Organization by Jeff Mauzy and Richard Harriman 2003

Inspiration from Nature - Biomimetics

Function and Flow

Places for tool application

I have presented in the section above a sparse introductory list of tools that can be used to facilitate innovation. But the reader may have noted that there are two different domains for the application of these tools: They may be applied either during Problem Formulation, or during Problem Solving (or both.) Innovation takes place during both phases. This may be most clearly seen via a negative example: It is abundantly clear that one might formulate a problem in such a manner as to close the door to innovation. Indeed, avoiding this over-specification of the problem is one of the goals of the teleological approach to innovation.

Thus we must employ innovation tools both during problem formulation and during the 'design phase' of problem solution.

Under this heading in the textbook I, at present, envision something like a matrix or an X-Y graph depicting, for each of the tools presented, whether that tool applies to problem formulation or to problem solution.

I am not firmly committed to this path as I can also see that it might be valuable to move the discussion of 'definition versus solution' to an earlier position in the work, and then have each tool's subsection talk about the phase of application of that tool. I therefore wish to withhold the final decision on this architecture until the research is further advanced. At the present time please let it suffice that the topic will be addressed, but it remains to be seen {\it where} that will take place.

The Innovation Algorithm Morphology (10pp)

It is my observation that the models or algorithms for innovation discussed above share a common structure or morphology, but this shared structure is not recognized across developers. In this section I will present this overarching morphology, and then I will show the mapping of the previously-cited innovation algorithms into this common structure.

A morphology is a system for describing the structure or form of an entity, by dividing it into common components. Thus all insects have a common morphology of exoskeleton, head, thorax, abdomen. This is different from a taxonomy, where the taxonomy is a hierarchical or family-tree type structure, which is used for classifying and differentiating between members of a set. Perhaps our most familiar introduction to taxonomy is in biology, where organisms are classed according to Kingdom, Phylum, Class, Order, Family, Genus, and Species.

Both Morphologies and Taxonomies are important for myriad purposes. Bloom and Krathwohl cite the value of a taxonomic system as an aid to measurement, but also as an establishing a common language about the subject, and as a means for finding congruence among different elements of the group being classified. In the case of Bloom and Krathwohl the items being classified are educational objectives, and not animals, but this is an apt paradigm for my use of a morphology to classify invention algorithms, and for suggesting that this act of classification will have value both as a means for understanding those various algorithms, but also as a means for comparing and contrasting them, and finding their points of commonality or congruence.

The morphology of innovation algorithms is as follows:

Define Problem
Generalize Problem
Search for solutions
Apply Solutions
Implement Application
Learn

Define Problem

The first step in the morphology - the first common component in the innovation methodologies - is the problem statement. Problem definition is, in naval engineering terms, approximately equivalent to stating design requirements.

There are well known guides for stating requirements. The most important of these is that the requirements should be stated in a manner that describes a function or relationship, and not in a manner that describes a solution. Thus if we state the problem as "staple the two pieces of paper together" we have already specified the solution (staples) and closed the door to a range of innovative solutions, including glue, straight pins, paper-clips, and the like. If the problem were formulated as "fix the two pieces of paper together" then these choices would be available.

Requirements may be stated in one of two ways - as component requirements or as architectural requirements. Equivalently we may say as runctional requirements or as relational requirements. Of course, in many cases requirements are (badly) stated as both - e.g. "The requirement is for a missile armed patrol vessel." In this case we say that the requirement is badly stated because it has been posed in the form of a solution, rather than as a problem.

Architectural requirements are relational requirements that describe the ways in which system components must interact. Thus, in an obvious architectural example, the garage must be accessible directly from the kitchen. A naval engineering example might describe interactions of systems on the ship, or it might describe interactions between the ship and the super-system of which it is a part. Such an example would be "shall operate as an element of the Carrier Battle Group." The super-system or external architectural requirements are frequently of very great importance in naval design.

Component requirements are functional requirements imposed upon all or part of the ship. Thus a component requirement would be a statement of the requirement for maneuverability, or firefighting, or other similar performance aspect. Generally the whole-ship functional requirements are actually stated as a large number of smaller component requirements.

The proper statement of the problem, or requirements, is important. I have already spoken of the need to state requirements without positing their solution. Another aspect is the breakdown of the problem into chunks. Von Hippel (1990) discusses the way that the problem is broken down, and the role that this breakdown architecture can have upon the invention / innovation outcome. Von Hippel is discussing innovation in an industrial context, wherein the innovation task is of necessity broken down into subtasks and distributed across the enterprise. The nature of the breakdown will open and close certain doors to innovation, by the simple act of defining the boundaries of inquiry of those tasks.

He offers the measure of “task interdependence” as the metric of whether problem solving in one task will require a complementary effort in another task. He then posits that the innovation will be more successful if the interdependence among tasks is minimized, and goes on to give guidance for how to specify tasks to minimize the interdependence, and also to reduce the cost of unavoidable interdependence.

In terms of facilitating innovation, von Hippel is saying that component requirements should avoid interdependence, and that this independence should also be reflected in the make up of the design team to whom the task is assigned.

This explanation has the potential for an interesting study in naval design: Based on von Hippel we may consider that specialists working on one part of a design problem don't actually need the full capability of the interfacing tasks, but might be able to get away with using relatively simple surrogate models for those tasks. Thus for example does the hull form designer really need to know the characteristics of the propeller, or is it sufficient to know merely the diameter? As on can see by this example, the interface between design tasks is already streamlined in accordance with this philosophy.

von Hippel then focuses upon this task partitioning aspect, and seeks out tools and models in a manner similar to the present author's search for tools and models of innovation. As a tool for stating requirements in an independent manner von Hippel mentions QFD. It is interesting to read von Hippel's discovery of the QFD method, and to listen to the similarity with the TRIZ concept of "contradiction." von Hippel:

"QFD encourages the placing of customer requirements, engineering requirements and manufacturing requirements with respect to a proposed project onto a common matrix, so that interactions and possible conflicts can be identified and discussed by project team members at an early stage. Thus, the method might highlight the following interaction: "The better an auto door is at tightly sealing out noise and dirt (a desirable characteristic), the harder it is to close (an undesirable characteristic) given that conventional sealing technology is applied". Such information can be used as an aid to improving task partitioning. Thus, if project specifications require improvements in door closing or door sealing, the presence of the interaction with respect to these two matters suggests that arranging task partitions so that both are included in a single "improve door closing and door sealing" task would reduce task problem-solving interdependence in this instance. ”

Up to this point von Hippel has been arguing that one should state problems in terms of their interactions, and perhaps in terms of their contradictions. Finally, in addition to careful problem definition, von Hippel states:

"A second approach to managing task problem-solving interdependence involves reducing the cost of engaging in problem-solving across task boundaries. This approach is complementary to the one discussed above: It regards existing task partitions as given, and seeks ways to minimize the costs of any associated cross-boundary problem-solving. Therefore, both approaches can be applied simultaneously when attempting to manage the effects of task problem-solving interdependence.

This suggests that classic project management disciplines of communication, integration, gatekeeping, and so forth are all contributors to innovation success.

What we see in von Hippel then is that we are enjoined to carefully define the problem, and we are invited to do so in a language of interface and contradiction. Further, we are shown that any single problem can be decomposed into subsidiary interface or contradiction problems. We are then offered some tools to manage those problems that can't be separated from their interdependencies - such as the whole set of architectural requirements.

Let us now consider what some of the other innovation methodologies say.

Brainstorming takes the problem statement for granted, and dives straight into ideation. But hte grand tenet of brainstorming - to withhold judgment - has the effect of constantly exposing the problem to reformulation.

In a brainstorming session it is common for a participant to say "But wait, what if instead of pushing, we were to pull?" Ideas such as this are back-handed ways of restating the problem. In the push/pull example the proposer is actually starting down the path of restating the requirements at a higher level of abstraction. This is explicitly the goal of the method called teleological decomposition.

One of the casual ways of referring to teleological decomposition was discovered written on a conference room white board. In what appeared to be graffiti was written:

Begin by asking "why?"
Then ask "why" again.
Then ask "why" again.
Then ask "why" again.
Then ask "why" again.
Then ask "why" again.

Is it not obvious what the point of this is? Each statement of a requirement begs to be restated as the solution to a requirement one level higher. Even a military mission can be restated as a cascade from a level such as "enforce the political will of the nation."

And each time a statement of requirement is thus elevated, it introduces entirely new branches of a solution tree, and entirely new opportunities for game-changing innovation.

Synectics attempts to force this same teleological expansion by creating metaphors for the original problem. If we then take the metaphor into the foreground, separating it from its origin, this can be a tool for the principle "make the familiar strange, make the strange familiar." Simply put: See in a new way.

" See in a new way" is language that might be expected of Quintillian. The seven ancient questions can easily be described as tools to help observer "see anew."

One is reminded of Sherlock Holmes' oft-repeated statement to Dr. Watson "You see, but you do not observe." Had Watson methodically applied Quintillians seven questions, his observation might have been greatly increased.

Holmes' wisdom is also found in Martin Gardner's algorithm for solving mathematical puzzles. He begins "Are there aspects of the problem that are actually irrelevant for the solution, and whose presence in the [statement] serves only to misdirect you?"

I suggest therefor that in addition to the previously sketched tools for peeling the problem to its essentials, that a separate effort is called for specifically to identify distractions and irrelevancies.

FOOTNOTE: In may ways this is similar to the graphic artist's technique of drawing the negative space, and the reader is invited to consider McKesson's separately-distribute essay on negative design.

The final technique to be included in the morphological step of problem definition is the technique of multitasking.

Multitasking is in some fashion the inverse of "removing distractions." Whereas the foregoing techniques were attempts to simplify and focus the requirement, the discipline of multitasking suggests combining requirements.

A classical example can be found in the design of shipboard heating and cooling systems: It is common to have some systems that require cooling (e.g. electronics) and other systems that require heating (e.g. working spaces.) To what extent can these functions be combined? Current practice is to sea-water cool a generator, and then use the generator's electrical power to heat a space. Can this process be streamlined? Certainly the use of waste-heat is one step in this direction, but could we go further?

An example of "going further" in multitasking would be to exploit the electrical conductivity of the ship's shell and piping systems. Let us recall that in a 12VDC car the car's structural frame constitutes one half of the electrical circuit, effectively halving the number of conductors in the wiring harness.

Finally, the technique of Muda elimination falls in similar category. Muda calls for us to eliminate "that for which there is no customer." This is very similar to Gardner's "distractions and irrelevancies." If the real goal is to heat the pace, then why go through the steps in Figure [[]]. Who are the customers for the intermediate products?

burn fuel
create heta
use heat to expand gas
convert expansion to torque
convert torque to electricity
distribute electricity
convert electricity to heat

Dr. Amory Lovins is credited with introducing the concept of Muda in the USA. Dr. Lovins has exploited this concept (along with multitasking) to build a home in the Colorado Rockies that maintains a comfortable year-round climate despite having no identifiable heating or cooling plant.

As a 'teaser' of the power of Muda and multitasking together, consider that the weight of the steel in a shipload of containers exceeds the weight of steel in the ship. The opportunity leaps to mind to exploit these containers as part of the ship's structure, with a concomitant weight and cost savings.

[Put unmanned ships in the Muda chapter.]

In conclusion for this step of the morphology ("Define Problem") we see that all of the stated tools address the same truths about problem definition:

The statement of the problem constrains the opportunity for innovation
Expanding the problem statement "teleologically upward" expands the solution spcace, thus opening the door to innovation
The problem must be stated in a scope that is within the technical domain of the design team (this from von Hippel.)
Eliminating distractions, irrelevancies, and Muda
Combining related problems to allow multitasking.

In the next stages of the innovation/invention process this language of requirements continues. The steps are:

List the requirements without prejudice
Genericize the requirements
Search for alternate paradigms for meeting these requirements

Generalize Problem

Search for solutions

Apply Solutions

Implement Application

Learn

A menu of innovation opportunities in ship design

As a result of prosecution this dissertation the author has identified a number of opportunities for innovation in ship design.

Some of these opportunities are huge, with potentially dramatic impacts. Some of them are smaller component-level ideas.

And some of them are probably bad ideas.

In this section I will present these ideas. (Some of them have been introduced previously. For completeness sake I repeat them here.) I will present these ideas as future research topics -- projects that somebody else could complete. I have not myself tackled them - yet.

In my presentation I will attempt to show how each of the proposed innovation flows from the principles above. My purpose in this dissertation is not to create a menu of innovations, but rather to put forward a lesson in cooking which can yield many and diverse menus. The examples in this section are merely "serving suggestions."

Techniques within each component of the generalized morphology (20pp)

Include a graphic that shows the whole morphology as a tree, with at each level of the process a long horizontal array of choices of technique.

Divergent thinking

Lateral or Deviregent thinking is solving problems through an indirect and creative approach, using reasoning that is not immediately obvious and involving ideas that may not be obtainable by using only traditional step-by-step logic.

Critical thinking is primarily concerned with judging the true value of statements and seeking errors. Lateral thinking is more concerned with the movement value of statements and ideas. A person uses lateral thinking to move from one known idea to creating new ideas. Edward de Bono defines four types of thinking tools:

Idea generating tools that are designed to break current thinking patterns—routine patterns, the status quo
Focus tools that are designed to broaden where to search for new ideas
Harvest tools that are designed to ensure more value is received from idea generating output
Treatment tools that are designed to consider real-world constraints, resources, and support<ref>Lateral Thinking: The Power of Provocation manual: Published in 2006 by de Bono Thinking Systems</ref>

Random Entry Idea Generating Tool: The thinker chooses an object at random, or a noun from a dictionary, and associate that with the area they are thinking about. For example, if they are thinking about how to improve a web site, an object chosen at random from the environment around them might be a fax machine. A fax machine transmits images over the phone to paper. Fax machines are becoming rare. People send faxes directly to phone numbers. Perhaps this could suggest a new way to embed the web site's content in emails and other sites.

Provocation Idea Generating Tool: The use any of the provocation techniques—wishful thinking, exaggeration, reversal, escape, distortion, or arising. The thinker creates a list of provocations and then uses the most outlandish ones to move their thinking forward to new ideas.

Movement Techniques: The thinker develops provocation operationsTemplate:Huh? by the following methods: extract a principle, focus on the difference, moment to moment, positive aspects, special circumstances.

Challenge Idea Generating Tool: A tool which is designed to ask the question "Why?" in a non-threatening way: why something exists, why it is done the way it is. The result is a very clear understanding of "Why?" which naturally leads to fresh new ideas. The goal is to be able to challenge anything at all, not just items which are problems. For example, one could challenge the handles on coffee cups. The reason for the handle seems to be that the cup is often too hot to hold directly. Perhaps coffee cups could be made with insulated finger grips, or there could be separate coffee cup holders similar to beer holders.

Concept Fan Idea Generating Tool: Ideas carry out concepts. This tool systematically expands the range and number of concepts in order to end up with a very broad range of ideas to consider.

Disproving: Based on the idea that the majority is always wrong (as suggested by Henrik Ibsen and John Kenneth Galbraith), take anything that is obvious and generally accepted as "goes without saying", question it, take an opposite view, and try to convincingly disprove it. This technique is similar to de Bono's "Black Hat" of the Six Thinking Hats, which looks at the ways in which something will not work.

Lateral thinking and problem solving

Problem Solving: When something creates a problem, the performance or the status quo of the situation drops. Problem solving deals with finding out what caused the problem and then figuring out ways to fix the problem. The objective is to get the situation to where it should be.

For example, a production line has an established run rate of 1000 items per hour. Suddenly, the run rate drops to 800 items per hour. Ideas as to why this happened and solutions to repair the production line must be thought of, such as giving the worker a pay raise.

Creative Problem Solving: Using creativity, one must solve a problem in an indirect and unconventional manner.

For example, if a production line produced 1000 books per hour, creative problem solving could find ways to produce more books per hour, use the production line, or reduce the cost to run the production line.

Creative Problem Identification: Many of the greatest non-technological innovations are identified while realizing an improved process or design in everyday objects and tasks either by accidental chance or by studying and documenting real world experience.

Method of focal objects

The technique of focal object for problem solving involves synthesizing the seemingly non-matching characteristics of different objects into something new.

Another way to think of focal objects is as a memory cue: if you're trying to find all the different ways to use a brick, give yourself some random "objects" (situations, concepts, etc.) and see if you can find a use. Given "blender", for example, I would try to think of all the ways a brick could be used with a blender (as a lid?). Another concept for the brick game: find patterns in your solutions, and then break those patterns. If you keep finding ways to build things with bricks, think of ways to use bricks that don't involve construction. Pattern-breaking, combined with focal object cues, can lead to very divergent solutions. (Grind the brick up and use it as pigment?)

Application of the Invention Morphology to a Ship Design Task (10pp)

During the summer of 2012 I was given the opportunity to serve as ONR Summer Faculty in support of the Naval Research Enterprise Intern Program (NREIP.) During this summer program eleven teams of student interns were presented with technological (design) challenges of real interest to the US Navy. My task during this time was to serve as a resource to all of the teams, including as a resource in ideation.

I used this opportunity to explore the application of the various formalized invention methodologies, for application in naval architecture.

As mentioned, there were eleven summer projects. These were:

1 Missile launcher re-arming at sea

2 LNG Security

3 AAAV

4 MANA

5 UxV Ship Impact

The nature of my tasking was that this was not a controlled experiment. In many scientific processes we are not able to design and control experiments in the manner that we might wish, constructing nicely arranged grids of data along uniformly spaced intervals and the like. Instead, many studies must make do with naturally occurring data, that leaves gaps and questions. (An example of this type of data would be any medical study that uses mortality data. We certainly do not intentionally kill patients in order to fill in a data space, no matter how mathematically appealing that might be.)

Thus in the present case the 'experiment' consists of ad hoc applications of the various invention methods found here, to an unstructured array of opportunities.

While this is not necessarily the mathematically optimum design of experiments, it is however the real world of engineering invention.

In this section I will present the application of the preceding generic invention morphology to a particular task in ship design.

The experiment...design...

Note that no attempt was made to force individuals to use one or another analogy-generation technique. THis was left up to individual preference, allowing each to select a tool that suited his question and personality.

What did they pick?

What worked best?

Quantitative metric on number of analogies found...

Past examples:

Oceanography evolution WTA Fuel Cell Ferry architecture Mobility Frigate for 05R

The Task

As mentioned above, I attempted to apply multiple different ideation methods at Carderock. One of the Carderock CISD conference rooms was equipped with a post entitled "brainstorming" as depicted in Figure {}. I added to this wall additional posters, including the most important (in my opinion) of the ideation methods.

It was intersting to me that the very clever innovators at the CISD were not aware that there were formalized ideation methods, other than Brainstorming.

First attempt: 8 June 12.

Unstructured discussion of missile re-arming at sea. This was a very short and unstructured meeting. After an introduction to the task we (Jack Offutt, Colen Kennel, and myself) spent about 30 minutes in ideation. We were first equipped with a short menu of already-defined solution concepts.

I applied design by analogy to identify analogies with reloading a pistol, from the one-bullet-at-a-time model for a revolver to a model including the concept of plastic magazine reloader for an automatic.

I tried to apply TRIZ, we were able to get as far as the problem being defined as "should move / shouldn't move": The weapons are brought over on a crane (they move) but when the get to the combatant it is important that they should not move, so that the missile tube can be reloaded. This turned out to be a pretty good technique because Colen quickly came up with the idea of using an inflated bag to grab the missile and immobilize it.

I identified one industrial analog - how are eggs loaded into a cardboard dozen box? - but this avenue was not pursued.

I still feel like there is probably a biomimetic parallel but we didn't find one (we didn't try, either.)

Wordtree, visual analogs, and other techniques were not attempted

AAV

One of the CISD teams is working on the perennial problem of providing decent hydrodynamics to an amphibious armored vehicle. Previous attempts at this lead to the "planing brick" of the AAAV. [2]

The current task, as I understand it, is for a more modest speed goal of only about 12 knots. However, early hydrodynamic studies suggest that 12 knots for a vehicle of this size is a very poor choice of Froude Number, and thus the wavemaking drag is high. The CISD team is investigating means of increasing the hydrodynamic length, in order to change the operational Froude Number.

I applied the menu of Innovation techniques to this problem, unfortunately in a one-man process.

The Problem Definition

The problem is to make a vehicle like the EFV go 12 knots in water, on a minimum level of power, safely.

The Problem Generalized

The problem may be generalized in many ways:

The task is to build a 34.5 tonne 12 knot boat...how much does this differ from the EFV?
Can we make the EFV "look like" the boat defined above?

TRIZ:

What is the inherent conflict in the project? The design team has taken length as the contradiction: That the "boat" 'wants to be' twice as long as the EFV 'wants to be.' Presumably the EFV length is driven by transport and maneuverability requirements. The desired boat length is driven by hydrodynamics.

Lexical Techniques:

Keywords that are relevant:

Planing Brick

Synonyms:

Skipping stone

Antonyms:

sink

These techniques did not return any obviously fruitful paths for investigation. Of course, this is only a superficial use of the technique.

MUDA:

Similar to TRIZ's use of contradiction, can I define any aspect of the problem as "muda" - that for which I have no customer?

In this case one definition is of the length increment required: We need to make the craft longer as a boat, but then we need the length to 'go away' ashore - because we have no customer for length, once in land-vehicle mode.

QUINTILLIAN'S SEVEN QUESTIONS:

Who? - The fighting vehicle
What? - Needs to cross water at 12 knots. To do this, we think it needs to be longer or at least more hydrodynamically shaped.
When? - Time is not a factor, except in the desired speed
Where? - must function in deep water
With What? - Must only use systems or components that can be easily carried on the vehicle
How? - TBD

MARTIN GARDNER:

Martin Gardner's method emphasizes simplifying the problem, and searching for solutions to the simpler problem. So in this case, what is the simpler problem that is equivalent to teh AAV problem? Several possibilities exist:

What if we didn't need it to go 12 knots, but only 10? or 8? or 2? What if we didn't need it to be self propelled, but could instead be towed? What if it were designed as boat first, and then made to be a land vehicle after?

VISUAL ANALOGS:

I did not find any visual analogs, perhaps due to my inability to find suitable keywords to describe the problem in an image search. I did get many images in response to the phrase "skipping stone" and many of these images were interesting, but they were not directly provocative of solution ideas for this problem.

SYNECTICS:

" An EFV is like an Alligator because they are both amphibious."
" An EFV is like s tug boat because they are both in unfavorable Froude Numbers."
" An EFV is like a snow shovel because they both plow water."
" An EFV is like a bull in a china shop, because it is blunt."
" An EFV is like a half-tide rock, because the water flows around it much faster than one might wish."
" An EFV is like

BIOMIMETICS

The obvious biomimetic parent is an Alligator. The alligator has two separate forms of propulsion, but it does not attempt to move at high speed while waterborne, except in bursts. Is a burst speed an option for an EFV, or does it need 12 knots continuously?

MULTITASKING:

Are there any functions that are logically similar and could thus be combined into a single multitasked component or subsystem? I am unable to find any on this problem.

The Search for Solutions

No that we have generalized the problem in a variety of terms, let us attempt to find concept level solutions in those same terms.

First, a quick look at the naval architectural task. The task is to build a 34.5 tonne 12 knot boat...how much does this differ from the EFV?

A good 12 knot 34.5 tonne boat will be as follows:

Expected TF = 34.5

Thus expected power = 60 kW

It appears that at this speed the displacement / length ratio should lie in the range 1 to 3. This yields lengths of 22 to 32 meters, where the EFV is 10 meters. In fact, this quick look confirms that the team's current path is a reasonable one.

Now let's look at the ideation methods:

TRIZ:

The team is focusing on a TRIZ-like resolution of the contradiction, by pursuing the design of a variable-length vehicle. Their particular focus is on the implementation of this variable-length concept. They have developed several concepts, and the most fruitful is a form of telescoping structure that pushes out an inflatable ship's bow, but retracts (and deflates) for overland mode. This is a classic TRIZ transformation.

MUDA:

1: Is there some gear that is needed ashore that can be brought by the EFV as "cargo" in the length-augment? 2: Can we simply add a second or third EFV in train configuration? In fact, the choice of optimal length / weight / speed converges such that a train of 4 EFV's does in fact have the length and displacement of an optimized 12 knot ship.

QUINTILLIAN'S SEVEN QUESTIONS:

Who? - The fighting vehicle
What? - Needs to cross water at 12 knots. To do this, we think it needs to be longer or at least more hydrodynamically shaped.
When? - Time is not a factor, except in the desired speed
Where? - must function in deep water
With What? - Must only use systems or components that can be easily carried on the vehicle
How? - TBD

The final question - "how" - is in this case the Quintillian equivalent of the search for solutions. The foregoing six questions were useful in understanding the task, but they have not given rise immediately to any proposed solutions.

MARTIN GARDNER:

What if we didn't need it to go 12 knots, but only 10? or 8? or 2? A hydrodynamic investigation suggests that the EFV length and weight are not suited to a 12 knot speed, but perhaps they match at a lower speed? Unfortunately, this turns out not to be the case, with no match found down to 2 knots.

What if we didn't need it to be self propelled, but could instead be towed? I am unable to visualize a means of using this idea.

What if it were designed as a boat first, and then made to be a land vehicle after? There may be some merit to this idea. A 12 knot 34 tonne boat is about 33 meters long. Upon reaching the shore this boat could 'break apart' and become....what? An EFV plus three HMMVs?

Note also the relationship between this idea and the MUDA idea.

SYNECTICS:

" An EFV is like an Alligator because they are both amphibious."
" An EFV is like s tug boat because they are both in unfavorable Froude Numbers."
" An EFV is like a snow shovel because they both plow water."
" An EFV is like a bull in a china shop, because it is blunt."
" An EFV is like a half-tide rock, because the water flows around it much faster than one might wish."

The alligator analogy is one that catches the attention, because of the obvious similarities. Also, not that both vehicles have separate marine and land propulsion systems. It is also noticeable that the alligator is not fast in water, but does have a sprint capability - a burst speed. Would the EFV benefit in anyway from a burst speed? Could this burst capability be used to justify a lower (and thus easier to attain) sustained speed?

Following the lizard analogy, I wonder if the EFV has to make more than one trip? If not, can the lizard drop its tail when it reaches shore?

Finally, turning to the other synectic analogies, I notice the number of them that dwell on the bluntness of the vehicle. I am not able to see how this could translate into a possible solution, but it nags at my mind that there is something in this observation. This may be an analog that awaits a shower epiphany.

BIOMIMETICS

UxV Launch & Recovery

One of the CISD teams is working on quantifying the ship impact of accomodating a future panoply of unmanned vehicles. These so-called UxV's may be air vehciles (UAVs), surface vehicles (USVs), or undersea vehicles (UUVs.)

I was called upon by this team to assist in developing concepts for minimizing this ship impact, by in particular minimizing the impact of the launch and recovers operation.

I applied the menu of Innovation techniques to this problem, in a two-hour discussion with the three-person team.

The Problem Definition

The problem is to launch, recover, resupply, and maintain an unknown number of unknown types of UxVs. In our discussion we spent most time upon the recovery aspect, because this was perceived to be the thorniest problem. We did however generate one useful guidance for the launch problem, which will be documented (out of order) here:

Air, Surface, and subsurface vehicles may compete for different types of ship launch support infrastructure. Helicopter-like UAVs need a flight deck. Boat-like USVs need a boat ramp, davit, or other similar way to be put into the water.

In order to minimize ship impact, and maximize ship flexibility, we concluded with the recommendation that all types of UxV should be configured for water take-off. This means that no matter whether the vehicle dives, swims, or flies, it would do so from an attitude of 'floating near the mother ship', and that the act of "launch" would - from the mother ship's point of view - consist only of putting the vehicle into the water in a satisfactory manner.

The Problem Generalized

Already from the "launch" discussion above we begin to see a generalization of the UxV task. The task is to recover the vehicle from its native element, in a manner consistent with the vehicles sensitivity to, say, impact, wetness, personnel hazard, etc. To generalize this problem we called it "catching eggs."

Note how, even in the act of generalizing the problem, we begin to find analogs.

TRIZ:

What is the inherent conflict in the project? It was somewhat difficult to state the challenge of UxV recovery in the words of a TRIZ contradiction, but we must recall that none of the participants are truly expert in TRIZ.

The gist of the contradiction is that the unmanned vehicle is separate from the ship, by design and intention, and we need to make it not-separate from the ship, as the act of recovery.

Figure {} duplicates the TRIZ 40 principle / 39 feature contradiction table. http://triz40.com/aff_Principles.htm

Lexical Techniques:

Keywords that are relevant:

Synonyms:

Antonyms:

MUDA:

Similar to TRIZ's use of contradiction, can I define any aspect of the problem as "muda" - that for which I have no customer?

QUINTILLIAN'S SEVEN QUESTIONS:

Who? -
What? -
When? - Time is a factor, in that we wish to not overly constrain the maneuverability of the mother ship
Where? - The vehicle must be recovered in all types of environments, including sea and wind conditions that we couldn't launch in, but that arose after the vehicle had been deployed.
With What? - Our goal is to minimize the space, weight, cost, and other impacts of the "with what." This also includes our inventory of recovery assets that already exist or may exist on the mother ship, such as davits, kingposts, cranes, flight decks, etc.
How? - TBD

MARTIN GARDNER:

Would it be easier if the vehicle were stationary?

VISUAL ANALOGS:

SYNECTICS:

" An EFV is like an Alligator because they are both amphibious."
" An EFV is like s tug boat because they are both in unfavorable Froude Numbers."
" An EFV is like a snow shovel because they both plow water."
" An EFV is like a bull in a china shop, because it is blunt."
" An EFV is like a half-tide rock, because the water flows around it much faster than one might wish."
" An EFV is like

BIOMIMETICS

MULTITASKING:

Are there any functions that are logically similar and could thus be combined into a single multitasked component or subsystem? I am unable to find any on this problem.

The Search for Solutions

No that we have generalized the problem in a variety of terms, let us attempt to find concept level solutions in those same terms.

First, a quick look at the naval architectural task. The task is to build a 34.5 tonne 12 knot boat...how much does this differ from the EFV?

A good 12 knot 34.5 tonne boat will be as follows:

Expected TF = 34.5

Thus expected power = 60 kW

Now let's look at the ideation methods:

TRIZ:

The team is focusing on a TRIZ-like resolution of the contradiction, by pursuing the design of a variable-length vehicle. Their particular focus is on the implementation of this variable-length concept. They have developed several concepts, and the most fruitful is a form of telescoping structure that pushes out an inflatable ship's bow, but retracts (and deflates) for overland mode. This is a classic TRIZ transformation.

MUDA:

QUINTILLIAN'S SEVEN QUESTIONS:

Who? - The fighting vehicle
What? - Needs to cross water at 12 knots. To do this, we think it needs to be longer or at least more hydrodynamically shaped.
When? - Time is not a factor, except in the desired speed
Where? - must function in deep water
With What? - Must only use systems or components that can be easily carried on the vehicle
How? - TBD

MARTIN GARDNER:

What if we didn't need it to go 12 knots, but only 10? or 8? or 2? A hydrodynamic investigation suggests that the EFV length and weight are not suited to a 12 knot speed, but perhaps they match at a lower speed? Unfortunately, this turns out not to be the case, with no match found down to 2 knots.

What if we didn't need it to be self propelled, but could instead be towed? I am unable to visualize a means of using this idea.

What if it were designed as a boat first, and then made to be a land vehicle after? There may be some merit to this idea. A 12 knot 34 tonne boat is about 33 meters long. Upon reaching the shore this boat could 'break apart' and become....what? An EFV plus three HMMVs?

Note also the relationship between this idea and the MUDA idea.

SYNECTICS:

" An EFV is like an Alligator because they are both amphibious."
" An EFV is like s tug boat because they are both in unfavorable Froude Numbers."
" An EFV is like a snow shovel because they both plow water."
" An EFV is like a bull in a china shop, because it is blunt."
" An EFV is like a half-tide rock, because the water flows around it much faster than one might wish."

Following the lizard analogy, I wonder if the EFV has to make more than one trip? If not, can the lizard drop its tail when it reaches shore?

BIOMIMETICS

Applying the Solutions

Implementing the Application

Learning

The Problem Definition

The Problem Generalized

The Search for Solutions

Applying the Solutions

Implementing the Application

Learning

Workplace Barriers to Creativity and Innovation (4pp)

There are many barriers to creativity. A significant number of papers have been published on the characteristics of a workplace that is 'innovation friendly.' need citations. These papers often also contain essays upon the character of the innovators, since an innovation-friendly environment is a pleasant one to innovators, but it is likely to be The Workplace From Hell for adaptors.

The dissertation will not go far down this path. It will include a minor unit on the characteristics of an innovation-friendly environment (what Rhodes called 'Press' in the 4P model) but it will leave the bulk of this topic to those other courses that already exist on this subject (viz: UNO MANG 4407 "Management of Technology and Innovation" )

There is a very interesting opportunity to study the physical design of the workplace as a means of fostering increased innovation and creativity. THe New Yorker articel "http://www.newyorker.com/reporting/2012/01/30/120130fa_fact_lehrer?currentPage=all" has the following interesting story about the physical workplace:

"A few years ago, Isaac Kohane, a researcher at Harvard Medical School, published a study that looked at scientific research conducted by groups in an attempt to determine the effect that physical proximity had on the quality of the research. He analyzed more than thirty-five thousand peer-reviewed papers, mapping the precise location of co-authors. Then he assessed the quality of the research by counting the number of subsequent citations. The task, Kohane says, took a “small army of undergraduates” eighteen months to complete. Once the data was amassed, the correlation became clear: when coauthors were closer together, their papers tended to be of significantly higher quality. The best research was consistently produced when scientists were working within ten metres of each other; the least cited papers tended to emerge from collaborators who were a kilometre or more apart. “If you want people to work together effectively, these findings reinforce the need to create architectures that support frequent, physical, spontaneous interactions,” Kohane says. “Even in the era of big science, when researchers spend so much time on the Internet, it’s still so important to create intimate spaces.”

A new generation of laboratory architecture has tried to make chance encounters more likely to take place, and the trend has spread in the business world, too. One fanatical believer in the power of space to enhance the work of groups was Steve Jobs. Walter Isaacson’s recent biography of Jobs records that when Jobs was planning Pixar’s headquarters, in 1999, he had the building arranged around a central atrium, so that Pixar’s diverse staff of artists, writers, and computer scientists would run into each other more often. “We used to joke that the building was Steve’s movie,” Ed Catmull, the president of both Disney Animation and Pixar Animation, says. “He really oversaw everything.”

Jobs soon realized that it wasn’t enough simply to create an airy atrium; he needed to force people to go there. He began with the mailboxes, which he shifted to the lobby. Then he moved the meeting rooms to the center of the building, followed by the cafeteria, the coffee bar, and the gift shop. Finally, he decided that the atrium should contain the only set of bathrooms in the entire building. (He was later forced to compromise and install a second pair of bathrooms.) “At first, I thought this was the most ridiculous idea,” Darla Anderson, a producer on several Pixar films, told me. “I didn’t want to have to walk all the way to the atrium every time I needed to do something. That’s just a waste of time. But Steve said, ‘Everybody has to run into each other.’ He really believed that the best meetings happened by accident, in the hallway or parking lot. And you know what? He was right. I get more done having a cup of coffee and striking up a conversation or walking to the bathroom and running into unexpected people than I do sitting at my desk.” Brad Bird, the director of “The Incredibles” and “Ratatouille,” says that Jobs “made it impossible for you not to run into the rest of the company.”

In the spring of 1942, it became clear that the Radiation Laboratory at M.I.T.—the main radar research institute for the Allied war effort—needed more space. The Rad Lab had been developing a radar device for fighter aircraft that would allow pilots to identify distant German bombers, and was hiring hundreds of scientists every few months. The proposed new structure, known as Building 20, was going to be the biggest lab yet, comprising two hundred and fifty thousand square feet, on three floors. It was designed in an afternoon by a local architecture firm, and construction was quick and cheap. The design featured a wooden frame on top of a concrete-slab foundation, with an exterior covered in gray asbestos shingles. (Steel was in short supply.) The structure violated the Cambridge fire code, but it was granted an exemption because of its temporary status. M.I.T. promised to demolish Building 20 shortly after the war.

Initially, Building 20 was regarded as a failure. Ventilation was poor and hallways were dim. The walls were thin, the roof leaked, and the building was broiling in the summer and freezing in the winter. Nevertheless, Building 20 quickly became a center of groundbreaking research, the Los Alamos of the East Coast, celebrated for its important work on military radar. Within a few years, the lab developed radar systems used for naval navigation, weather prediction, and the detection of bombers and U-boats. According to a 1945 statement issued by the Defense Department, the Rad Lab “pushed research in this field ahead by at least 25 normal peacetime years.” If the atom bomb ended the war, radar is what won it.

Immediately after the surrender of Japan, M.I.T., as it had promised, began making plans for the demolition of Building 20. The Rad Lab offices were dismantled and the radio towers on the roof were taken down. But the influx of students after the G.I. Bill suddenly left M.I.T. desperately short of space. Building 20 was turned into offices for scientists who had nowhere else to go.

The first division to move into Building 20 was the Research Laboratory of Electronics, which grew directly out of the Rad Lab. Because the electrical engineers needed only a fraction of the structure, M.I.T. began shifting a wide variety of academic departments and student clubs to the so-called “plywood palace.” By the nineteen-fifties, Building 20 was home to the Laboratory for Nuclear Science, the Linguistics Department, and the machine shop. There was a particle accelerator, the R.O.T.C., a piano repair facility, and a cell-culture lab.

Building 20 became a strange, chaotic domain, full of groups who had been thrown together by chance and who knew little about one another’s work. And yet, by the time it was finally demolished, in 1998, Building 20 had become a legend of innovation, widely regarded as one of the most creative spaces in the world. In the postwar decades, scientists working there pioneered a stunning list of breakthroughs, from advances in high-speed photography to the development of the physics behind microwaves. Building 20 served as an incubator for the Bose Corporation. It gave rise to the first video game and to Chomskyan linguistics. Stewart Brand, in his study “How Buildings Learn,” cites Building 20 as an example of a “Low Road” structure, a type of space that is unusually creative because it is so unwanted and underdesigned. (Another example is the Silicon Valley garage.) As a result, scientists in Building 20 felt free to remake their rooms, customizing the structure to fit their needs. Walls were torn down without permission; equipment was stored in the courtyards and bolted to the roof. When Jerrold Zacharias was developing the first atomic clock, working in Building 20, he removed two floors in his lab to make room for a three-story metal cylinder.

The space also forced solitary scientists to mix and mingle. Although the rushed wartime architects weren’t thinking about the sweet spot of Q or the importance of physical proximity when they designed the structure, they conjured up a space that maximized both of these features, allowing researchers to take advantage of Building 20’s intellectual diversity.

Room numbers, for instance, followed an inscrutable scheme: rooms on the second floor were given numbers beginning with 1, and third-floor room numbers began with 2. Furthermore, the wings that made up the building were named in an unclear sequence: B wing gave onto A wing, followed by E, D, and C wings. Even longtime residents of Building 20 were constantly getting lost, wandering the corridors in search of rooms. Those looking for the Ice Research Lab had to walk past the military recruiting office; students on their way to play with the toy trains (the Tech Model Railroad Club was on the third floor, in Room No. 20E-214) strolled along hallways filled with the latest computing experiments.

The building’s horizontal layout also spurred interaction. Brand quotes Henry Zimmerman, an electrical engineer who worked there for years: “In a vertical layout with small floors, there is less research variety on each floor. Chance meetings in an elevator tend to terminate in the lobby, whereas chance meetings in a corridor tended to lead to technical discussions.” The urban theorist Jane Jacobs described such incidental conversations as “knowledge spillovers.” Her favorite example was the rise of the automobile industry in Detroit. In the eighteen-twenties, the city was full of small shipyards built for the flour trade. Over time, the shipyards became centers of expertise in the internal-combustion engine. Nearly a century later, those engines proved ideal for powering cars, which is why many pioneers of the automotive industry got their start building ships. Jacobs’s point was that the unpredictable nature of innovation meant that it couldn’t be prescribed in advance.

Building 20 was full of knowledge spillovers. Take the career of Amar Bose. In the spring of 1956, Bose, a music enthusiast, procrastinating in writing his dissertation, decided to buy a hi-fi. He chose the system with the best technical specs, but found that the speakers sounded terrible. Bose realized that the science of hi-fi needed help and began frequenting the Acoustics Lab, which was just down the hall. Before long, Bose was spending more time playing with tweeters than he was on his dissertation. Nobody minded the interloper in the lab, and, three years later, Bose produced a wedge-shaped contraption outfitted with twenty-two speakers, a synthesis of his time among the engineers and his musical sensibility. The Bose Corporation was founded soon afterward."

Future Research Opportunities (4pp)

Consider whether there should be a Future Research Opportunities graphic - something like the morphology tree, but listing the papers to be written, listing each title according to where it fits on the tree.

Finally, the section entitled "Future Research Opportunities" will be a collection of short abstracts of topics suitable for future papers, theses, or dissertations. By including this section in a textbook I would hope it might stimulate some student to further action on these lines.

For example, a strong suggestion will be the creation of a work dedicated solely to the application of TRIZ to naval engineering. TRIZ is, based on my research thus far, the most comprehensive of theories / models / algorithms for innovation. Indeed, I nearly suggested making it the sole focus of my dissertation. But I decided that this would be premature, and that the situation might be best handled as follows:

The present (proposed) dissertation is an omnibus treatment of the many available models and algorithms, each of which has some merit even if only in a limited domain. The omnibus work serves as a foundation for the study of innovation in Naval Engineering.

Upon this broad foundation it is possible to erect several edifices, and one of them could be devoted to TRIZ. I envision, thus, a second work (either my own or another candidate's) which is specific to the application of TRIZ to naval architecture. This work would focus mainly on applying the TRIZ algorithm and thus 'translating' TRIZ into maritime paradigms. This would be an interesting work and useful to the industry, but as explained above I leave it to a 'phase II' of this line of study, in the belief that the foundation is the necessary starting point.

A second follow-on work that I can currently envision would be to attempt a comprehensive detailed teleological decomposition of a ship. By taking a work breakdown system such as SWBS (ref), one could develop a list of all of the functions that are present on a ship, and the functions that they support, and the functions that support them. For example, the man is on board to steer the ship, the HVAC system is on board to support the man, the chilled water plant is there to support the HVAC. A comprehensive map of all these functions - all these \i{teleos} - might provide very interesting opportunities to eliminate muda or pursue multitasking.

Paper: The relation between cognitive style and choice of analogy-search method: I BELIEVE THat the cognitive style of the person will affect his choice of preferred tool at each step of the process. I can imagine visual thinkers enjoying the visual analogies method, while lexical thinkers enjoy WordTree. This is a fruitful avenue of future research

Software: Tools exist for several of the invention methodologies discussed herein, but these tools tend to be vertically integrated. Thus for example there is a TRIZ software. What I do not find, however, is a horizontal software such as, for example, a comprehensive tool for the step {finding analogies} that would use all of the methods mentioned: Image analogies, word analogies, patent databases, and word antonyms. Developing such a software would result in a "stereoscopic" tool that would present the inventor with many directions from which to tackle his problem, and would result in a much more robust candidate solution space.

Software: Building on the previous software solution, we may then imagine an algebra that would combine the software-found analogs. In this scheme we may imagine that an analog is found in, say, biology and then lexicon and the patent database. THe fact that this same analogy is found in three very different types of search might suggest that it is a particularly fruitful one for investigation. Therefore it might be interesting to find a means for counting these "hits" and scoring each analogy with some sort of measure of merit, thus ranking them so that the software automatically presents a 'most-likely to be fruitful' subset. This scheme is similar in effect to the way that Google ranks websearch findings to present a 'most likely to be what you wanted' front page.

Paper: When to avoid fixation. Many of the fundamental authors have touched upon the need to maintain an open mind as long as possible, to avoid fixating on a design solution. This is, for example, axiomatic in brainstorming wherein the participants are required to suspend judgment until a specific point in the process.

The research question for this paper would be: Is the point up to which we must suspend judgement a common point for all of the methods? I.e., do we suspend judgment up through step {x} pf the morphology, regardless of which techniques we are using at each step? Or are there some techniques that are more 'judgment tolerant'?

This could have important application to which techniques one should employ, if one knows, for example, that she is working with a group that is prone to hasty judgment, or prone to avoid judgment.

As mentioned in the section on the work of Tyson Browning, I see a relationship between his focus upon interactions in design (which is also found in other models, including TRIZ) and the Cognitivie Network Model and its attention to associative distance and interactions between concepts. It would be interesting to apply Browning's philosophy by actively studying, not concepts, but the associations between concepts, explicitly. As a mental placeholder for this future research, imagine studying adjectives instead of nouns. If instead of studying "apples" what if we studied "red"? Whats would be the engineering benefit of design a research project based on interactions rather than components?

I would love to see the work of Uzzi repeated in the naval design realm. I find it easy to imagine that the Q for the naval design community if too high for good innovation.

Thus the reviewer may see that even at this point in the process I envision a series of works, starting with the present foundation work, and then followed by (for example) a work specific to TRIZ, or a work specific to the teleology of ship systems, or other specialized study. My hope would be that the present project would establish a framework for publication in the field of Innovation in Naval Engineering, which framework could then be built upon by several subsequent works.

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I haven't seen the immediate applicability of this to my thesis, but I can imagine that the tool of Transactional Analysis, and the resulting technique of modeling human interactions as "games" might have relevance to certain aspects of the _implementation_ of invention and innovation in the workplace.

I am also struck by the author's definition of the above-the-game level of maturity called "autonomy." While I am not so arrogant as to think that I am game-free, it does seem to me that I operate largely at the autonomous level, and it is not inconceivable that this is contributory to my success at innovation.

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Retrieved from "http://www.mckesson.us/mckwiki/index.php?title=NEW_COURSE_-_Innovation_in_Ship_Design"

 == Implement Application==
 == Learn==
+<h1>A menu of innovation opportunities in ship design</h1>
+As a result of prosecution this dissertation the author has identified a number of opportunities for innovation in ship design.
+Some of these opportunities are huge, with potentially dramatic impacts.  Some of them are smaller component-level ideas.
+And some of them are probably bad ideas.
+In this section I will present these ideas.  (Some of them have been introduced previously.  For completeness sake I repeat them here.)  I will present these ideas as future research topics -- projects that somebody else could complete.  I have not myself tackled them - yet.
+In my presentation I will attempt to show how each of the proposed innovation flows from the principles above.  My purpose in this dissertation is not to create a menu of innovations, but rather to put forward a lesson in cooking which can yield many and diverse menus.  The examples in this section are merely "serving suggestions."
 <h1>Techniques within each component of the generalized morphology (20pp)</h1>

NEW COURSE - Innovation in Ship Design

From Mckwiki

Revision as of 13:22, 23 July 2012

Contents

Foreword (1pp)

Introduction & Background (2pp)

Definition of Terms

Design (2pp)

Innovation (3pp)

Sustaining versus Disruptive

Incremental versus Radical

Architectural Innovation

Existing Models

Models of Creativity (4pp)

Stahl's Overview

Rhodes' 4P model

Lopez' 4P+N Model

The Cognitive Network Model

Creativity versus Novelty

Models of Design (9pp)

The Design Spiral

Dr. Tyson Browning

C-K Theory

Models of Creative People (4pp)

Creativity versus Intelligence

Creativity and Quality

Creativity as a social product

Measuring Innovation Aptitude

Characteristics of Team Leaders

Expertise as a Cognitive Skill

Characteristics of Innovators

Existing Models and Tools for Design Innovation (20pp)

Osborn-Parnes Creative Problem Solving Process

\subsubsection{The need for expert knowledge}

\subsubsection{Quintillian's Seven Questions}

\subsubsection{Mathematical Problem Solving:}

\subsubsection{Teleological Decomposition}

\subsubsection{ARI - Accelerated Radical Innovation}

\subsubsection{TRIZ}

History

Basic principles of TRIZ

Essentials

Basic terms

Identifying a problem: contradictions

Inventive principles and the matrix of contradictions

Laws of technical system evolution

Substance-field analysis

ARIZ - algorithm of inventive problems solving

Use of TRIZ methods in industry

Books on TRIZ by Altshuller

\subsubsection{Brainstorming}

Morphological Analysis

\subsubsection{Muda}

\subsubsection{Multitasking}

\subsubsection{Design By Analogy}

WordTree

\subsubsection{Synonyms, Antonyms and Homonyms}

Visual Analopies

Synectics

History

Theory

Books

Inspiration from Nature - Biomimetics

Function and Flow

Places for tool application

The Innovation Algorithm Morphology (10pp)

Define Problem

Generalize Problem

Search for solutions

Apply Solutions

Implement Application

Learn

A menu of innovation opportunities in ship design

Techniques within each component of the generalized morphology (20pp)

Divergent thinking

Lateral thinking and problem solving

Method of focal objects

Application of the Invention Morphology to a Ship Design Task (10pp)

The Task

First attempt: 8 June 12.