ICoRD'13 pp 101-112 | Cite as

Information Entropy in the Design Process

  • Petter Krus
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


In this paper the design process is viewed as a process of increasing the information of the product/system. Therefore, it is natural to investigate the design process from an information theoretical point of view. The design information entropy is introduced as a state that reflects both complexity and refinement, and it is argued that it can be useful as some measure of design effort and design quality. The concept of design information entropy also provides a sound base for defining creativity as the process of selecting areas for expanding the design space in useful direction, “to think outside the box”, while the automated activity of design optimization is focused, so far, on concept refinement, within a confined design space. In this paper the theory is illustrated on the conceptual design of an unmanned aircraft, going through concept generation, concept selection, and parameter optimization.


Information entropy Design complexity Product platform 


  1. 1.
    Ullman DG (1992) The mechanical design process. McGraw-Hill Book Co, Singapore. ISBN 0-07-065739-4Google Scholar
  2. 2.
    Shannon D (1948) A mathematical theory of communication. Bell Syst Tech J 27:379Google Scholar
  3. 3.
    Suh NP (2001) Axiomatic design: advances and applications. Oxford University Press, USA, ISBN-0-19-513466-5Google Scholar
  4. 4.
    Khan WA, Angeles J (2007) The role of entropy in design theory and methodology. In: Proceedings of CDEN/C2E2 2007 conference, Winnipeg, Alberta, CanadaGoogle Scholar
  5. 5.
    Frey D, Jahangir E (1999) Differential entropy as a measure of information content in axiomatic design. In: Proceedings of the 1999 ASME design engineering technical conference, Las Vegas, USAGoogle Scholar
  6. 6.
    Bras B, Mistree F (1995) Compromise design decision support problem for axiomatic and robust design. J Mech des Trans ASME 117Google Scholar
  7. 7.
    Krus P, Andersson J (2004) An information theoretical perspective on design optimization. ASME, DETC, Salt Lake City, USAGoogle Scholar
  8. 8.
    Bansiya J, Davies C, Etzkorn L (1999) An entropy-based complexity measure for object oriented design. Theor Pract Object Syst 5(2):111–118Google Scholar
  9. 9.
    Amadori K, Lundström D, Krus P Automated design and fabrication of micro-air vehicles. Accepted for publication on journal of aerospace engineering, proceedings of the institution of mechanical engineers part G [PIG], doi: 10.1177/0954410011419612
  10. 10.
    Kullback S, Leibler RA (1951) On information and sufficiency. Ann Math Stat 22:79–86MathSciNetMATHCrossRefGoogle Scholar
  11. 11.
    Torenbeek E (1982) Synthesis of subsonic airplane design. Kluwer Academic Publishers, ISBN 90-247-2724-3Google Scholar
  12. 12.
    Zwicky F (1948) The morphological method of analysis and construction. Courant, Anniversary volume, Intersciences Publisher, New York, pp 461–470Google Scholar
  13. 13.
    Krus P, Jansson A, Palmberg JO (1993) Optimization using simulation for aircraft hydraulic system design. In: Proceedings of IMECH international conference on aircraft hydraulics and systems, LondonGoogle Scholar
  14. 14.
    Rosenbrock HH (1960) An automatic method for finding the greatest or least value of a function. Comput J 3:175–184MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.Department of Management and Engineering, Division of Fluid and Mechatronic SystemsLinköping UniversityLinköpingSweden

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