Customer-driven product design and evaluation method for collaborative design environments
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Product concept generation and evaluation in a product development environment has been identified as the two major activities needed for obtaining an optimal design scheme. Product conceptual design is of critical importance in design through customer involvement for the systematic and simultaneous consideration on the impact of design decisions on manufacturing and assembly leads to repeated and excessive changes in design and processes. This paper introduces a novel knowledge support approach for the organization and ranking of design feature knowledge towards an integrated product model that incorporates a feature-based representation scheme targeted to evaluate the impact of design on subsequent activities in the conceptual design phase, taking into account the presence of design information and user preferences. An uncertain linguistic multi-attribute decision-making evaluation model is proposed and discussed for obtaining an optimal design scheme during the evaluation and selection of product design alternatives in conceptual design. The focus of this paper is on the development of a knowledge-intensive support design scheme and a comprehensive systematic fuzzy evaluation methodology for product conceptual design generation, evaluation, and selection. A case study and the corresponding scenario of knowledge support for design alternatives generation, evaluation and selection are provided for illustration.
KeywordsCustomer-driven design Feature design Design evaluation Uncertainty Multi-attribute decision-making
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- Britton G.A., Tor S.B., Zhang W.Y. (2005) Techniques in knowledge-based expert systems for the design of engineering systems. In: Cornelius T. Leondes (eds) Intelligent knowledge-based systems: Business and technology in the new millennium, Vol. 3: Expert and agent systems. Kluwer, Dordrecht, pp 3–54Google Scholar
- Hazelrigg G. (1996) Systems engineering: An approach to information-based design. Prentice-Hall, Englewood Cliffs, NJGoogle Scholar
- Pahl G., Beitz W. et al (2007) Engineering design: A systematic approach (3rd Edn). Springer, LondonGoogle Scholar
- Ullman D. G., Diambrosio B. (1995) Taxonomy for classifying engineering decision problems and support systems. Artificial Intelligent Engineering Design 9: 427–438Google Scholar
- Zadeh, L. A. (1975). The concept of a linguistic variable and its applications to approximate reasoning. Part I, Information Sciences, 8, 199–249, Part II, Information Sciences, 8, 301–357, Part III, Information Sciences, 9, 43–80.Google Scholar
- Zimmermann H. J. (1996) Fuzzy set theory and its applications (3rd Edn). Kluwer, BostonGoogle Scholar