Using quality function deployment for collaborative product design and optimal selection of module mix

In response to fast-growing and rapidly-changing markets, launching new products faster than competitors cannot only assist firms in acquiring larger market share but also reducing development lead time, significantly. However, owing to its intrinsically uncertain properties of managing NPD (new product development), manufacturing companies often struggle with the dilemma of increasing product variety or controlling manufacturing complexity. In this study, a fuzzy MCDM (multi-criteria decision making) based QFD (quality function deployment) which integrates fuzzy Delphi, fuzzy DEMATEL (decision making trial and evaluation laboratory), with LIP (linear integer programming) is proposed to assist an enterprise in fulfilling collaborative product design and optimal selection of module mix when aiming at multi-segments. In particular, Fuzzy Delphi is adopted to gather marketing information from invited customers and their assessments of marketing requirements are pooled to reach a consensus; fuzzy DEMATEL is utilized to derive the priorities of technical attributes in a market-oriented manner; and LIP is used to maximize product capability with consideration of supplier's budget constraints of manufacturing resources. Furthermore, a real case study on developing various types of sport and water digital cameras is demonstrated to validate the proposed approach.

[1]  Jaeil Park,et al.  A product platform concept development method , 2008 .

[2]  R. Luce,et al.  Simultaneous conjoint measurement: A new type of fundamental measurement , 1964 .

[3]  Liang-Hsuan Chen,et al.  A fuzzy model for exploiting quality function deployment , 2003 .

[4]  Sevin Sozer,et al.  Product planning in quality function deployment using a combined analytic network process and goal programming approach , 2003 .

[5]  Thomas L. Saaty,et al.  Decision making with dependence and feedback : the analytic network process : the organization and prioritization of complexity , 1996 .

[6]  Liang-Hsuan Chen,et al.  An evaluation approach to engineering design in QFD processes using fuzzy goal programming models , 2006, Eur. J. Oper. Res..

[7]  Roger Jianxin Jiao,et al.  Customer Requirement Management in Product Development: A Review of Research Issues , 2006, Concurr. Eng. Res. Appl..

[8]  Da Ruan,et al.  Fuzzy group decision-making to multiple preference formats in quality function deployment , 2007, Comput. Ind..

[9]  C. K. Kwong,et al.  A fuzzy AHP approach to the determination of importance weights of customer requirements in quality function deployment , 2002, J. Intell. Manuf..

[10]  Zülal Güngör,et al.  A new mixed integer linear programming model for product development using quality function deployment , 2009, Comput. Ind. Eng..

[11]  N. Kano,et al.  Attractive Quality and Must-Be Quality , 1984 .

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

[13]  Gary S. Wasserman,et al.  ON HOW TO PRIORITIZE DESIGN REQUIREMENTS DURING THE QFD PLANNING PROCESS , 1993 .

[14]  E. Ertugrul Karsak,et al.  Fuzzy multiple objective decision making approach to prioritize design requirements in quality function deployment , 2004 .

[15]  Elim Liu,et al.  A structural component-based approach for designing product family , 2005, Comput. Ind..

[16]  Da Ruan,et al.  Determining the importance weights for the design requirements in the house of quality using the fuzzy analytic network approach , 2004, Int. J. Intell. Syst..

[17]  Soundar R. T. Kumara,et al.  A methodology for knowledge discovery to support product family design , 2010, Ann. Oper. Res..

[18]  C K Kwong,et al.  Determining the Importance Weights for the Customer Requirements in QFD Using a Fuzzy AHP with an Extent Analysis Approach , 2003 .

[19]  Liang-Hsuan Chen,et al.  A fuzzy nonlinear model for quality function deployment considering Kano's concept , 2008, Math. Comput. Model..

[20]  Chi-Jen Lin,et al.  A causal analytical method for group decision-making under fuzzy environment , 2008, Expert Syst. Appl..

[21]  Victor B. Kreng,et al.  QFD-based modular product design with linear integer programming—a case study , 2004 .

[22]  Ming-Lang Tseng,et al.  Using QFD and ANP to analyze the environmental production requirements in linguistic preferences , 2010, Expert Syst. Appl..

[23]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[24]  Da Ruan,et al.  Determining the importance weights for the design requirements in the house of quality using the fuzzy analytic network approach , 2004 .

[25]  R. Yager On a general class of fuzzy connectives , 1980 .

[26]  Gülçin Büyüközkan,et al.  A fuzzy optimization model for QFD planning process using analytic network approach , 2006, Eur. J. Oper. Res..

[27]  Hsing-Pei Kao,et al.  Rating the importance of customer needs in quality function deployment by fuzzy and entropy methods , 1999 .

[28]  Yoji Akao,et al.  Quality Function Deployment : Integrating Customer Requirements into Product Design , 1990 .

[29]  Shih-Wen Hsiao,et al.  ANP-GP approach for product variety design , 2006 .

[30]  Leo L. Pipino,et al.  A pilot study of fuzzy set modification of Delphi , 1985 .

[31]  Ching-Hsue Cheng,et al.  Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation , 2002, Eur. J. Oper. Res..

[32]  Amy H. I. Lee,et al.  An evaluation framework for product planning using FANP, QFD and multi-choice goal programming , 2010 .

[33]  Shing I. Chang,et al.  An integrated group decision-making approach to quality function deployment , 1999 .

[34]  Zaifang Zhang,et al.  An integrated approach for rating engineering characteristics' final importance in product-service system development , 2010, Comput. Ind. Eng..

[35]  Roger Jianxin Jiao,et al.  A methodology of developing product family architecture for mass customization , 1999, J. Intell. Manuf..

[36]  J. Jiao,et al.  Towards high value-added products and services: mass customization and beyond , 2003 .