THE MEANING OF "NEAR" AND "FAR": THE IMPACT OF STRUCTURING DESIGN DATABASES AND THE EFFECT OF DISTANCE OF ANALOGY ON DESIGN OUTPUT

This work lends insight into the meaning and impact of “near” and “far” analogies. A cognitive engineering design study is presented that examines the effect of the distance of analogical design stimuli on design solution generation, and places those findings in context of results from the literature. The work ultimately sheds new light on the impact of analogies in the design process and the significance of their distance from a design problem. In this work, the design repository from which analogical stimuli are chosen is the U.S. patent database, a natural choice, as it is one of the largest and easily accessed catalogued databases of inventions. The “near” and “far” analogical stimuli for this study were chosen based on a structure of patents, created using a combination of Latent Semantic Analysis and a Bayesian based algorithm for discovering structural form, resulting in clusters of patents connected by their relative similarity. The findings of this engineering design study are contextualized with the findings of recent work in design by analogy, by mapping the analogical stimuli used in the earlier work into similar structures along with the patents used in the current study. Doing so allows the discovery of a relationship between all of the stimuli and their relative distance from the design problem. The results confirm that “near” and “far” are relative terms, and depend on the characteristics of the potential stimuli. Further, although the literature has shown that “far” analogical stimuli are more likely to lead to the generation innovative solutions with novel characteristics, there is such a thing as too far. That is, if the stimuli are too distant, they then can become harmful to the design process. Importantly, as well, the data mapping approach to identify analogies works, and is able to impact the effectiveness of the design process. This work has implications not only in the area of finding inspirational designs to use for design by analogy processes in practice, but also for synthesis, or perhaps even unification, of future studies in the field of design by analogy.

[1]  Ellen Domb,et al.  Simplified TRIZ: New Problem-Solving Applications for Engineers and Manufacturing Professionals , 2002 .

[2]  Alice M. Agogino,et al.  Analogies and metaphors in creative design , 2008 .

[3]  L. H. Shu,et al.  Biomimetic Concept Generation Applied to Design for Remanufacture , 2002 .

[4]  Sougata Mukherjea,et al.  Information retrieval and knowledge discovery utilizing a biomedical patent semantic Web , 2005, IEEE Transactions on Knowledge and Data Engineering.

[5]  Kenneth D. Forbus,et al.  Analogy and creativity in the works of Johannes Kepler , 1997 .

[6]  Jonathan Cagan,et al.  On the benefits and pitfalls of analogies for innovative design : Ideation performance based on analogical distance, commonness, and modality of examples , 2011 .

[7]  Kenneth D. Forbus,et al.  MAC/FAC: A Model of Similarity-Based Retrieval , 1995, Cogn. Sci..

[8]  Jonathan Cagan,et al.  A METHODOLOGY FOR DISCOVERING STRUCTURE IN DESIGN DATABASES , 2011 .

[9]  L. Guttman A basis for scaling qualitative data. , 1944 .

[10]  Hal B. Gregersen,et al.  The innovator's DNA: mastering the five skills of disruptive innovators , 2011 .

[11]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[12]  Jeremy Thomas Murphy Patent-based analogy search tool for innovative concept generation , 2011 .

[13]  Jonathan Cagan,et al.  Discovering Structure in Design Databases Through Functional and Surface Based Mapping , 2013 .

[14]  Robert W. Weisberg,et al.  On “Out-of-the-Box” Thinking in Creativity , 2009 .

[15]  Arthur B. Markman,et al.  INCREASING INNOVATION: PRESENTATION AND EVALUATION OF THE WORDTREE DESIGN- BY-ANALOGY METHOD , 2008 .

[16]  John R. Anderson,et al.  The Adaptive Nature of Human Categorization. , 1991 .

[17]  Arthur B. Markman,et al.  Supporting Innovation by Promoting Analogical Reasoning , 2009 .

[18]  K. Kotovsky,et al.  The influence of open goals on the acquisition of problem-relevant information. , 2007, Journal of experimental psychology. Learning, memory, and cognition.

[19]  M. Ross Quillian,et al.  Retrieval time from semantic memory , 1969 .

[20]  Steven M. Smith,et al.  Metrics for measuring ideation effectiveness , 2003 .

[21]  D. Gentner,et al.  Structure mapping in analogy and similarity. , 1997 .

[22]  Moss Jarrod,et al.  Design Ideas and Impasses: the Role of Open Goals , 2007 .

[23]  Charles Kemp,et al.  Bayesian models of cognition , 2008 .

[24]  Charles Kemp,et al.  The discovery of structural form , 2008, Proceedings of the National Academy of Sciences.

[25]  K. Wood,et al.  QUANTITATIVE MEASURES FOR DESIGN BY ANALOGY , 2000 .

[26]  R. A. Bradley,et al.  RANK ANALYSIS OF INCOMPLETE BLOCK DESIGNS THE METHOD OF PAIRED COMPARISONS , 1952 .

[27]  Arthur B. Markman,et al.  Design by Analogy: A Study of the WordTree Method for Problem Re-Representation , 2012 .

[28]  Jonathan Cagan,et al.  The Role of Functionality in the Mental Representations of Engineering Students: Some Differences in the Early Stages of Expertise , 2006, Cogn. Sci..

[29]  Jonathan Cagan,et al.  A Study of Design Fixation, Its Mitigation and Perception in Engineering Design Faculty , 2010 .

[30]  Ashok K. Goel,et al.  A content account of creative analogies in biologically inspired design , 2010, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[31]  Shuang Song,et al.  Triangulation of Indicators of Successful Student Design Teams , 2006 .

[32]  J. Piaget,et al.  The early growth of logic in the child : classification and seriation , 1965 .

[33]  K. Dunbar How scientists think: On-line creativity and conceptual change in science. , 1997 .

[34]  John P. Huelsenbeck,et al.  MRBAYES: Bayesian inference of phylogenetic trees , 2001, Bioinform..

[35]  Bo T. Christensen,et al.  The relationship of analogical distance to analogical function and preinventive structure: the case of engineering design , 2007, Memory & cognition.

[36]  Kas Kasravi,et al.  Patent Mining - Discover y of Business Value from Patent Repositor ies , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[37]  Gabriela Goldschmidt,et al.  Expertise and the use of visual analogy: implications for design education , 1999 .

[38]  Arthur B. Markman,et al.  Wordtrees: A Method For Design By Analogy , 2008 .

[39]  David W. Rosen,et al.  The effects of biological examples in idea generation , 2010 .

[40]  Alok K. Chakrabarti,et al.  Interorganizational transfer of knowledge: an analysis of patent citations of a defense firm , 1991 .

[41]  Kristin L. Wood,et al.  Tools for Innovation , 2009 .

[42]  R. Crawford,et al.  Influences And Interests In Humanitarian Engineering , 2010 .

[43]  Willemien Visser,et al.  Two functions of analogical reasoning in design: a cognitive-psychology approach , 1996 .

[44]  J. S. Wiggins,et al.  An informal history of the interpersonal circumplex tradition. , 1996, Journal of personality assessment.

[45]  Arthur B. Markman,et al.  Modality and representation in analogy , 2008, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[46]  Ashok K. Goel Design, Analogy, and Creativity , 1997, IEEE Expert.

[47]  Jonathan Cagan,et al.  The role of timing and analogical similarity in the stimulation of idea generation in design , 2008 .

[48]  Dedre Gentner,et al.  Learning by Analogical Bootstrapping , 2001 .

[49]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[50]  Shinji Tanaka,et al.  INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN , 2005 .

[51]  Craig A. Kaplan,et al.  In search of insight , 1990, Cognitive Psychology.

[52]  K.V. Indukuri,et al.  Similarity Analysis of Patent Claims Using Natural Language Processing Techniques , 2007, International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007).

[53]  T. Landauer,et al.  A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .

[54]  Thomas Ertl,et al.  Iterative Integration of Visual Insights during Scalable Patent Search and Analysis , 2011, IEEE Transactions on Visualization and Computer Graphics.

[55]  M. Boden The creative mind : myths & mechanisms , 1991 .

[56]  Alice M. Agogino,et al.  Text analysis for constructing design representations , 1997, Artif. Intell. Eng..

[57]  W. Gordon Synectics: The Development of Creative Capacity , 1961 .

[58]  Robert Stone,et al.  Capturing Creativity: Using a Design Repository to Drive Concept Innovation , 2005 .

[59]  K. Holyoak,et al.  Analogical problem solving , 1980, Cognitive Psychology.

[60]  Karl T. Ulrich,et al.  Idea Generation and the Quality of the Best Idea , 2009, Manag. Sci..

[61]  Peter H. A. Sneath,et al.  Numerical Taxonomy: The Principles and Practice of Numerical Classification , 1973 .

[62]  Michael French,et al.  Invention and evolution : design in nature and engineering, 2nd ed. , 1988 .

[63]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[64]  A. Fiske The four elementary forms of sociality: framework for a unified theory of social relations. , 1992, Psychological review.

[65]  R N Shepard,et al.  Multidimensional Scaling, Tree-Fitting, and Clustering , 1980, Science.

[66]  T. McCaffrey Innovation Relies on the Obscure , 2012, Psychological science.

[67]  Ruihong Zhang,et al.  A conceptual design model using axiomatic design, functional basis and TRIZ , 2007, 2007 IEEE International Conference on Industrial Engineering and Engineering Management.

[68]  Peter W. Foltz,et al.  The Measurement of Textual Coherence with Latent Semantic Analysis. , 1998 .

[69]  Kristin L. Wood,et al.  Integrating Service-Oriented Design Projects in the Engineering Curriculum , 2002 .

[70]  D. Dahl,et al.  The Influence and Value of Analogical Thinking during New Product Ideation , 2002 .

[71]  Prabhakar Raghavan,et al.  Scalable feature selection, classification and signature generation for organizing large text databases into hierarchical topic taxonomies , 1998, The VLDB Journal.

[72]  Simon Szykman,et al.  A functional basis for engineering design: Reconciling and evolving previous efforts , 2002 .