A rough set based fuzzy axiomatic design approach in evaluating customer-centric design alternatives

Nowadays, companies strive to provide products that meet individual customer needs and expectations to achieve high profits. Customers' perceptions play a significant role in the design process. However, they are normally expressed using linguistic words which are hard to interpret, especially when trying to evaluate the best design solution among multiple design alternatives. This paper proposes a rough set based fuzzy axiomatic design (AD) approach to guide the design decision-making process which contains imprecise information. It aims to overcome the subjectivity of fuzzy membership functions selection by using rough method instead, to deal with vagueness. The approach utilizes the information axiom of AD principles and extends it to support customer-centric multi-attribute decision making. A comparative case study on bicycle frameset is conducted to validate the approach. The result shows that it has advantages compared to the fuzzy approach in processing linguistic assessments and is better suited for customized product design decision support.

[1]  Feng Zhou,et al.  Affective and cognitive design for mass personalization: status and prospect , 2012, Journal of Intelligent Manufacturing.

[2]  S. Tor,et al.  A Rough-Set-Based Approach for Classification and Rule Induction , 1999 .

[3]  Z. Pawlak Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[4]  Cengiz Kahraman,et al.  Application of axiomatic design and TOPSIS methodologies under fuzzy environment for proposing competitive strategies on Turkish container ports in maritime transportation network , 2009, Expert Syst. Appl..

[5]  Karel Vredenburg,et al.  A survey of user-centered design practice , 2002, CHI.

[6]  Jerzy W. Grzymala-Busse,et al.  Rough Sets , 1995, Commun. ACM.

[7]  Li Pheng Khoo,et al.  A rough set enhanced fuzzy approach to quality function deployment , 2008 .

[8]  Ashok Kumar,et al.  From mass customization to mass personalization: a strategic transformation , 2007 .

[9]  C. Kahraman,et al.  Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic h , 2005 .

[10]  C. Kahraman,et al.  Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach , 2005 .

[11]  Li Pheng Khoo,et al.  A rough set based QFD approach to the management of imprecise design information in product development , 2009, Adv. Eng. Informatics.

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[14]  Cengiz Kahraman,et al.  Fuzzy axiomatic design-based performance evaluation model for docking facilities in shipbuilding industry: The case of Turkish shipyards , 2009, Expert Syst. Appl..

[15]  Yaochu Jin,et al.  Advanced fuzzy systems design and applications , 2003, Studies in Fuzziness and Soft Computing.

[16]  Selcuk Cebi,et al.  A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process , 2009 .

[17]  Ming-Chyuan Lin,et al.  Using AHP and TOPSIS approaches in customer-driven product design process , 2008, Comput. Ind..

[18]  D. Chang Applications of the extent analysis method on fuzzy AHP , 1996 .