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A review of function modeling: Approaches and applications

Published online by Cambridge University Press:  14 March 2008

M.S. Erden ,
H. Komoto ,
T.J. van Beek ,
V. D'Amelio ,
E. Echavarria  and
T. Tomiyama
M.S. Erden
Affiliation:
Intelligent Mechanical Systems Group, Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
H. Komoto
Affiliation:
Intelligent Mechanical Systems Group, Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
T.J. van Beek
Affiliation:
Intelligent Mechanical Systems Group, Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
V. D'Amelio
Affiliation:
Intelligent Mechanical Systems Group, Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
E. Echavarria
Affiliation:
Intelligent Mechanical Systems Group, Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
T. Tomiyama
Affiliation:
Intelligent Mechanical Systems Group, Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
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Abstract

This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delineate what FM introduces to these fields, and to discuss the applicability of various FM approaches in these fields. Finally, the basic ideas underlying our projects are introduced with reference to the general framework of FM.

Keywords

BehaviorDesignFunction ModelingMaintenanceService
Type
Research Article
Information
AI EDAM , Volume 22 , Issue 2 , Spring 2008 , pp. 147 - 169
Copyright
Copyright © Cambridge University Press 2008

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References

REFERENCES

America, P., & van Wijgerden, J. (2000). Requirements modeling for families of complex systems. IW-SAPF 3: 3rd Int. Workshop on Software Architecture for Product Families, Lecture Notes in Computer Science, Vol. 1951. Berlin: Springer.Google Scholar
Arai, T., & Shimomura, Y. (2004). Proposal of service CAD system—a tool for service engineering. Annals of the CIRP 53(1), 397–400.CrossRefGoogle Scholar
Arai, T., & Shimomura, Y. (2005). Service CAD system—evaluation and quantification. Annals of the CIRP 54(1), 463–466.CrossRefGoogle Scholar
Balachandran, M., & Gero, J.S. (1990). Role of prototypes in integrated expert systems and CAD systems. In Applications of Artificial Intelligence in Engineering V (Gero, J.S., Ed.), Vol. 1, pp. 195–211. Berlin: Springer–Verlag.Google Scholar
Bhatta, S., Goel, A., & Prabhakar, S. (1994). Innovation in analogical design: a model-based approach. Proc. Third Int. Conf. Artificial Intelligence in Design (AID-94), pp. 57–74, Lausanne, Switzerland.CrossRefGoogle Scholar
Bonnema, G.M., & van Houten, F.J.A.M. (2006). Use of models in conceptual design. Journal of Engineering Design 17(6), 549–562.CrossRefGoogle Scholar
Bracewell, R.H., & Sharpe, J.E.E. (1996). Functional descriptions used in computer support for qualitative scheme generation—Schemebuilder. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 10(4), 333–346.CrossRefGoogle Scholar
Browing, R. (2001). Applying the design structure matrix to system decomposition and integration problems: a review and new directions. IEEE Transactions on Engineering Management 48(3), 292–306.CrossRefGoogle Scholar
Cagan, J., Campbell, M.I., Finger, S., & Tomiyama, T. (2005). A framework for conceptual design synthesis: model and applications. Journal of Computing and Informatic Science in Engineering 5(3), 171–181.CrossRefGoogle Scholar
Chakrabarti, A., & Bligh, T.P. (2001). A scheme for functional reasoning in conceptual design. Design Studies 22, 493–517.CrossRefGoogle Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B.S. (2005). A functional representation for aiding biomimetic and artificial inspiration of new ideas. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19, 113–132.CrossRefGoogle Scholar
Chandrasekaran, B. (1994 a). Functional representation and causal processes. Advances in Computers 38, 73–143.CrossRefGoogle Scholar
Chandrasekaran, B. (1994 b). Functional representations: a brief historical perspective. Applied Artificial Intelligence 8, 173–197.CrossRefGoogle Scholar
Chandrasekaran, B. (2005). Representing function: relating functional representation and functional modeling research streams. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19, 65–74.CrossRefGoogle Scholar
Chandrasekaran, B., & Josephson, J.R. (2000). Function in device representation. Engineering With Computers 16, 162–177.CrossRefGoogle Scholar
D'Amelio, V., & Tomiyama, T. (2007). Predicting the unpredicted problems in mechatronics design. Proc. ICED 2007 16th Int. Conf. Engineering Design.Google Scholar
De Kleer, J., & Brown, J.S. (1984). A qualitative physics based on confluences. Artificial Intelligence 24, 7–83.CrossRefGoogle Scholar
Deng, Y.M. (2002). Function and behavior representation in conceptual mechanical design. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 16, 343–362.CrossRefGoogle Scholar
Deng, Y.M., Britton, G.A., & Tor, S.B. (2000). Constraint-based functional design verification for conceptual design. Computer-Aided Design 32, 889–899.CrossRefGoogle Scholar
Deng, Y.M., Tor, S.B., & Britton, G.A. (1999). A computerized design environment for functional modeling of mechanical products. Proc. 5th ACM Symp. Solid Modeling, pp. 1–12, Ann Arbor, MI.Google Scholar
Dorst, K., & Vermaas, P.E. (2005). John Gero's function–behaviour–structure model of designing: a critical analysis. Research in Engineering Design 16, 17–26.CrossRefGoogle Scholar
Echavarria, E., Tomiyama, T., & van Bussel, G.J.W. (2007 a). Fault diagnosis approach based on a model-based reasoner and a functional designer for a wind turbine. An approach towards self-maintenance. Journal of Physics: Conference Series 75, http://www.iop.org/EJ/abstract/1742-6596/75/1/012078Google Scholar
Echavarria, E., Tomiyama, T., & van Bussel, G.J.W. (2007 b). The concept of self-maintained offshore wind turbines. Proc. European Wind Energy Conf.Milan, ItalyMay 7th–10th.Google Scholar
Far, B.H., & Elamy, A.H. (2005). Functional reasoning theories: problems and perspectives. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19, 75–88.CrossRefGoogle Scholar
Forbus, K.D. (1984). Qualitative process theory. Artificial Intelligence 24(3), 85–168.CrossRefGoogle Scholar
Gero, J.S. (1990). Design prototypes: a knowledge representation schema for design. AI Magazine 11(4), 26–36.Google Scholar
Gero, J.S., & Kannengiesser, U. (2004). The situated function–behaviour–structure framework. Design Studies 25(4), 373–391.CrossRefGoogle Scholar
Goel, A.K. (1991). A model-based approach to case adaptation. Proc. 13th Annual Conf. Cognitive Science Society, pp. 143–148. Hillsdale, NJ: Erlbaum.Google Scholar
Goel, A.K., & Bhatta, S.R. (2004). Use of design patterns in analogy-based design. Advanced Engineering Informatics 18, 85–94.CrossRefGoogle Scholar
Goel, A.K., & Chandrasekaran, B. (1989). Functional representation of designs and redesign problem solving. Proc. 11th Int. Joint Conf. Artificial Intelligence (IJCAI-89), pp. 1388–1394. San Mateo, CA: Morgan Kaufmann.Google Scholar
Goel, A.K., & Chandrasekharan, B. (1992). Case-based design: a task analysis. In Artificial Intelligence Approaches to Engineering Design (Tong, C., & Sriram, D., Eds.), Vol. 2, pp. 165–184. San Diego, CA: Academic.CrossRefGoogle Scholar
Keuneke, A., & Allemang, D. (1989). Exploring the no-function-in-structure principle. Journal of Experimental & Theoretical Artificial Intelligence 1(1), 79–89.CrossRefGoogle Scholar
Keuneke, A.M. (1991). Device representation—the significance of functional knowledge. IEEE Expert 6(2), 22–25.CrossRefGoogle Scholar
Kitamura, Y., Kashiwase, M., Fuse, M., & Mizoguchi, R. (2004). Deployment of ontological framework of functional design knowledge. Advanced Engineering Informatics 18(2), 115–127.CrossRefGoogle Scholar
Kitamura, Y., & Mizoguchi, R. (2003). Ontology-based description of functional design knowledge and its use in a functional way server. Expert Systems With Applications 24, 153–166.CrossRefGoogle Scholar
Kitamura, Y., & Mizoguchi, R. (2004). Ontology-based systematization of functional knowledge. Journal of Engineering Design 15(4), 327–351.CrossRefGoogle Scholar
Klein, W.E., & Lalli, V.R. (1989). Model 0A Wind Turbine Generator FMEA. Cleveland, OH: NASA Glenn Research Center.Google Scholar
Kuipers, B. (1981, November). de Kleer and Brown's “Mental Models:” A Critique, Technical Report 17. Boston: Tufts University.Google Scholar
Kuipers, B. (1994). Qualitative Reasoning: Modeling and Simulation With Incomplete Knowledge. Cambridge, MA: MIT Press.Google Scholar
Labib, A.W. (2006). Next generation maintenance systems: towards the design of a self-maintenance machine. 2006 IEEE Int. Conf. Industrial Informatics, pp. 213–217, Singapore.CrossRefGoogle Scholar
Lee, W.S., Grosh, D.L., Tillman, F.A., & Lie, C.H. (1985). Fault tree analysis, methods, and applications—a review. IEEE Transactions on Reliability R-34(3), 194–203.CrossRefGoogle Scholar
Miles, L.D. (1972). Techniques of Value Analysis and Engineering. New York: McGraw–Hill.Google Scholar
Muller, G. (2007). A multidisciplinary research approach, illustrated by the Boderc project. Accessed at http://www.gaudisite.nlGoogle Scholar
Pahl, G., & Beitz, W. (1988). Engineering Design: A Systematic Approach. Berlin: Springer–Verlag.Google Scholar
Rault, A. (1992). Mechatronics and bond graphs in the automotive industry. In Mechatronics, Pioneering or Self-Evident? (Scintilla, E.T.S.V., Ed.), pp. 68–77. Enschede: University of Twente.Google Scholar
Rausand, M. (1998). Reliability centered maintenance. Reliability Engineering & System Safety 60, 121–132.CrossRefGoogle Scholar
Rausand, M., & Oien, K. (1996). The basic concepts of failure analysis. Reliability Engineering & System Safety 58, 73–83.CrossRefGoogle Scholar
Rodenacker, W. (1971). Methodisches Konstruieren. Berlin: Springer–Verlag.Google Scholar
Rosenberg, R., & Karnopp, D.C. (1983). Introduction to Physical System Dynamics. New York: McGraw–Hill.Google Scholar
Shimomura, Y., Tanigawa, S., Umeda, Y., & Tomiyama, T. (1995). Development of self-maintenance photocopiers. AI Magazine 16(4), 41–53.Google Scholar
Shimomura, Y., Yoshioko, M., Takeda, H., Umeda, Y., & Tomiyama, T. (1998). Representation of design object based on the functional evolution process model. Journal of Mechanical Design 120, 221–229.CrossRefGoogle Scholar
Snooke, N., & Price, C. (1998). Hierarchical functional reasoning. Knowledge-Based Systems 11, 301–309.CrossRefGoogle Scholar
Suh, N.P. (1990). The Principle of Design. New York: Oxford University Press. Accessed at http://www.axiomaticdesign.com/Google Scholar
Szykman, S., Fenves, S.J., Keirouz, W., & Shooter, S.B. (2001). A foundation for interoperability in next-generation product development systems. Computer-Aided Design 33, 545–559.CrossRefGoogle Scholar
Szykman, S., Raez, J., Bochenek, C., & Sriram, R.D. (2000). A web-based system for design artifact modeling. Design Studies 21, 145–165.CrossRefGoogle Scholar
Tomiyama, T. (2006). Knowledge structure and complexity of multi-disciplinary design. Proc. 16th Int. CIRP Design Seminar 2006—Design & Innovation for a Sustainable Society (Gu, P., Xue, D., Ramirez-Serrano, A., Park, S., & Fletcher, D., Eds.), pp. 310–316. Alberta, Canada: Kananaskis.Google Scholar
Tomiyama, T., & D'Amelio, V. (2007 a). Towards design interference detection to deal with complex design problems. The Future of Product Development, Proc. 17th CIRP Design Conf. (Krause, F.L., Ed.), pp. 473–482. Berlin: Springer–Verlag.Google Scholar
Tomiyama, T., & D'Amelio, V. (2007 b). Complexity of multi-disciplinary product development and design interference detector. Proc. 3rd Int. Conf. Virtual Design and Automation VIDA.Google Scholar
Tomiyama, T., D'Amelio, V., Urbanic, J., & ElMaraghy, W. (2007). Complexity of multi-disciplinary design. CIRP Annals Manufacturing Technology 56(1).CrossRefGoogle Scholar
Tomiyama, T., & Meijer, B.R. (2005). Directions of next generation product development. In Advances in Design (ElMaraghy, H.A., & ElMaraghy, W.H., Eds.), pp. 27–35. London: Springer.Google Scholar
Tomiyama, T., Shimomura, Y., & Watanabe, K. (2004). A note on service design methodology. Proc. DETC'04, p. 57393, ASME.Google Scholar
Tomiyama, T., Umeda, Y., & Yoshikawa, H. (1993). A CAD for functional design. Annals of the CIRP 42(1), 143–146.CrossRefGoogle Scholar
Tor, S.B., Deng, Y.M., & Britton, G.G. (1999). A comprehensive representation model for functional design of mechanical products. Proc. 12th Int. Conf. Engineering Design, pp. 1929–1932, Munich, Germany.Google Scholar
Umeda, Y., Ishii, M., Yoshioka, M., Shimomura, Y., & Tomiyama, T. (1996). Supporting conceptual design based on the function-behavior-state modeller. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 10(4), 275–288.CrossRefGoogle Scholar
Umeda, Y., Kondoh, S., Shimomura, Y., & Tomiyama, T. (2005). Development of design methodology for upgradable products based on function–behavior–state modeling. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19(3), 161–182.CrossRefGoogle Scholar
Umeda, Y., Takeda, H., & Tomiyama, T. (1990). Function, behaviour, and structure. In Applications of Artificial Intelligence in Engineering V (Gero, J.S., Ed.), pp. 177–193. Berlin: Computational Mechanics Publications/Springer–Verlag.Google Scholar
Umeda, Y., & Tomiyama, T. (1995). FBS modeling: modeling scheme of function for conceptual design. Proc. Working Papers of the 9th Int. Workshop on Qualitative Reasoning About Physical Systems, pp. 271–278, Amsterdam.Google Scholar
Umeda, Y., & Tomiyama, T. (1997). Functional reasoning in design. IEEE Expert 12(2), 42–48.CrossRefGoogle Scholar
Umeda, Y., Tomiyama, T., & Yoshikawa, H. (1989). Model based diagnosis using qualitative physics. Computer Applications in Production and Engineering CAPE'89 (Kimura, F., & Rolstadas, A., Eds.), pp. 443–450. Amsterdam: North-Holland/Elsevier.Google Scholar
Umeda, Y., Tomiyama, T., & Yoshikawa, H. (1995 a). FBS modeling: modeling scheme of function for conceptual design. Proc. 9th Int. Workshop on Qualitative Reasoning, pp. 271–278, Amsterdam, May 11–19.Google Scholar
Umeda, Y., Tomiyama, T., & Yoshikawa, H. (1995 b). Design methodology for self-maintenance machines. Journal of Mechanical Design, Transactions of the ASME 117(3), 355–362.CrossRefGoogle Scholar
Umeda, Y., Tomiyama, T., Yoshikawa, H., & Shimomura, Y. (1994). Using functional maintenance to improve fault tolerance. IEEE Expert, Intelligent Systems & Their Applications 9(3), 25–31.Google Scholar
Van Bussel, G.W., & Zaaijer, M.B. (2001). Reliability, availability and maintenance aspects of large-scale offshore wind farms, a concepts study. Proc. Int. Conf. Marine Renewable Energy, pp. 119–126. London: Institute of Marine Engineers, London.Google Scholar
Van Bussel, G.W., & Zaaijer, M.B. (2003). Estimation of Turbine Reliability Figures Within the DOWEC Project, Report No. 10048. Petten, The Netherlands: DOWEC.Google Scholar
Van Wie, M., Bryant, C.R., Bohm, M.R., Mcadams, D.A., & Stone, R.B. (2005). A model of function-based representations. AIEDAM: Artificial Intelligence for Engineering, Design, and Manufacturing 19, 89–111.CrossRefGoogle Scholar
Wang, L., Shen, W., Xie, H., Neelamkavil, J., & Pardasani, A. (2002). Collaborative conceptual design—state of the art and future trends. Computer-Aided Design 34, 981–996.CrossRefGoogle Scholar
Welch, R.V., & Dixon, J.R. (1992). Representing function, behavior and structure during conceptual design. In Design Theory and Methodology—DTM'92 (Taylor, D.L., & Stauffer, L.A., Eds.), pp. 11–18. New York: ASME.Google Scholar
Welch, R.V., & Dixon, J.R. (1994). Guiding conceptual design through behavioral reasoning. Research in Engineering Design 6(3), 169–188.CrossRefGoogle Scholar
Yaner, P.W.Y., & Goel, A.K. (2006). From form to function: from SBF to DSSBF. In Design Computing and Cognition 2006 (Gero, J.S., Ed.), pp. 423–441. Berlin: Springer.Google Scholar
Yoshiaka, M., Umeda, Y., Takeda, H., Shimomura, Y., Nomaguchi, Y., & Tomiyama, T. (2004). Physical concept ontology for the knowledge intensive engineering framework. Advanced Engineering Informatics 18(2), 95–113.CrossRefGoogle Scholar
Yoshioka, M., Nomaguchi, Y., & Tomiyama, T. (2001). Proposal of an integrated design support environment based on the model of synthesis. Proc. ASME Design Engineering Technical Conf. 2, pp. 1319–1328.Google Scholar
Yoshioka, M., Umeda, Y., Takeda, H., Shimomura, Y., Nomaguchi, Y., & Tomiyama, T. (2004). Physical concept ontology for the knowledge intensive engineering framework. Advanced Engineering Informatics 18(2), 69–127.CrossRefGoogle Scholar