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Generalized Design Knowledge and the Higher-Order Singular Value Decomposition

  • Andy Dong
  • Somwrita Sarkar
Conference paper

Abstract

The question of what constitutes generalized design knowledge is central to design cognition. It is knowledge of a generic variety about products, the type of knowledge that is not principally related to any one product per se, but to knowledge about a broad class of products or a broad class of operations to produce products. In this paper, we use a complex systems perspective to propose a computational approach toward deriving generalized design knowledge from product and process representations. We present an algorithm that produces a representation of generalized design knowledge based on two-dimensional and multi-dimensional representations of designed objects and design processes, with the objects and processes being represented as a complex network of interactions. Our results show that the method can be used to infer and extract macroscopic, system level organizational information, or generalized design knowledge, from microscopic, primary or secondary representations of objects and process.

Keywords

Orthonormal Basis Singular Value Decomposition Knowledge Structure Singular Vector Design Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Braha D, Bar-Yam Y (2000) Data for the topology of large-scale engineering problem-solving networks, Available online http://necsi.edu/projects/braha/largescaleengineering.html. Last accessed 02 Jan 2011
  2. 2.
    Braha D, Bar-Yam Y (2004) Topology of large-scale engineering problem-solving networks. Phys Rev E 69(1):016113CrossRefGoogle Scholar
  3. 3.
    Braha D, Bar-Yam Y (2007) The statistical mechanics of complex product development: empirical and analytical results. Manage Sci 53(7):1127–1145CrossRefzbMATHGoogle Scholar
  4. 4.
    Browning TR (2001) Applying the design structure matrix to system decomposition and integration problems: a review and new directions. Eng Manag IEEE Trans 48(3):292–306CrossRefGoogle Scholar
  5. 5.
    Coyne RD, Newton S, Sudweeks F (1993) A connectionist view of creative design reasoning. In: Gero JS, Maher ML (eds) Modeling creativity and knowledge-based creative design. Lawrence Erlbaum Associates, Hillsdale, NJ, USA, pp 177–209Google Scholar
  6. 6.
    Darke J (1979) The primary generator and the design process. Des Stud 1(1):36–44CrossRefGoogle Scholar
  7. 7.
    de Lathauwer L, de Moor B, Vandewalle J (2000) A multilinear singular value decomposition. SIAM J Matrix Anal Appl 21(4):1253–1278CrossRefzbMATHMathSciNetGoogle Scholar
  8. 8.
    Dong A (2005) The latent semantic approach to studying design team communication. Des Stud 26(5):445–461CrossRefGoogle Scholar
  9. 9.
    Dong A, Sarkar S (2011) Unfixing design fixation: from cause to computer simulation. J Creative Behav 45(2):147–159CrossRefGoogle Scholar
  10. 10.
    Fortunato S, Barthélemy M (2007) Resolution limit in community detection. Proc Natl Acad Sci 104(1):36–41CrossRefGoogle Scholar
  11. 11.
    Gero JS (1990) Design prototypes: a knowledge representation schema for design. AI Mag 11(4):26–36Google Scholar
  12. 12.
    Gero JS (1998) Concept formation in design. Knowl Based Syst 11(7–8):429–435CrossRefGoogle Scholar
  13. 13.
    Gero JS, Kannengiesser U (2004) The situated function-behaviour-structure framework. Des Stud 25(4):373–391CrossRefGoogle Scholar
  14. 14.
    Kemp C, Tenenbaum JB (2008) The discovery of structural form. Proc Natl Acad Sci 105(31):10687–10692CrossRefGoogle Scholar
  15. 15.
    Kolda T (2009) Tensor decompositions and applications. SIAM Rev 51(3):455CrossRefzbMATHMathSciNetGoogle Scholar
  16. 16.
    Kroonenberg P, de Leeuw J (1980) Principal component analysis of three-mode data by means of alternating least squares algorithms. Psychometrika 45(1):69–97CrossRefzbMATHMathSciNetGoogle Scholar
  17. 17.
    Landauer TK, Foltz PW, Laham D (1998) Introduction to latent semantic analysis. Discourse Process 25:259–284CrossRefGoogle Scholar
  18. 18.
    Leslie AM (1987) Pretense and representation: The origins of “Theory of Mind”. Psychol Rev 94(4):412–426CrossRefGoogle Scholar
  19. 19.
    Perner J (1991) Understanding the representational mind. The MIT Press, CambridgeGoogle Scholar
  20. 20.
    Sarkar S, Dong A (2011) Community detection in graphs using singular value decomposition. Phys Rev E 83(4). doi: 10.1115/1.3179148
  21. 21.
    Sarkar S, Dong A, Gero JS (2009) Design optimization problem (re)-formulation using singular value decomposition, J Mech Des 131(8). doi: 10.1115/1.3179148
  22. 22.
    Schön DA (1963) Displacement of concepts. Tavistock Publications, LondonGoogle Scholar
  23. 23.
    Sinclair G, Klepper S, Cohen W (2000) What’s experience got to do with it? Sources of cost reduction in a large specialty chemicals producer. Manag Sci 46(1):28–45CrossRefGoogle Scholar
  24. 24.
    Stone RB, Wood KL (2000) Development of a functional basis for design. J Mech Des 122(4):359–370CrossRefGoogle Scholar
  25. 25.
    Stone RB, Wood KL, Crawford RH (2000) A heuristic method for identifying modules for product architectures. Des Stud 21(1):5–31CrossRefGoogle Scholar
  26. 26.
    Strang G (1988) Linear algebra and its applications. Harcourt, Brace, Jovanovich, Publishers, San DiegoGoogle Scholar
  27. 27.
    Summers JD, Bettig B, Shah JJ (2004) The design exemplar: a new data structure for embodiment design automation. J Mech Des 126(5):775–787CrossRefGoogle Scholar
  28. 28.
    Tucker LR (1964) The extension of factor analysis to three-dimensional matrices. In: Frederiksen N, Gulliksen H (eds), Contributions to mathematical psychology, Holt, Rinehart and Winston, Inc., New York, pp 110–127Google Scholar
  29. 29.
    Ward TB (1994) Structured imagination: the role of category structure in exemplar generation. Cogn Psychol 27(1):1–40CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.University of SydneySydneyAustralia

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