Flexible Manufacturing System selection based on grey relation under uncertainty

Flexible Manufacturing System (FMS) selection is a Multi-Criteria Decision-Making (MCDM) problem. To effectively select an FMS, several criteria need to be considered which may be objective or subjective. Objective criteria are quantitative (tangible) while subjective criteria are qualitative (intangible) in nature. As the assessment values have various types of vagueness, one cannot always use the classical decision-making techniques for such decision problems. Grey theory is one of the methods used to study uncertainty. In this paper, a fuzzy MCDM approach based on the concept grey theory has been proposed to systematically evaluate alternatives. A numerical example is used to illustrate the efficiency of the proposed approach.

[1]  Kenneth N. Thompson,et al.  Vendor Profile Analysis , 1990 .

[2]  Deng-Feng Li,et al.  Multiattribute decision making models and methods using intuitionistic fuzzy sets , 2005, J. Comput. Syst. Sci..

[3]  R. Venkata Rao,et al.  A decision-making framework model for evaluating flexible manufacturing systems using digraph and matrix methods , 2006 .

[4]  Edward N. Timmerman.  An Approach to Vendor Performance Evaluation , 1986 .

[5]  E. Ertugrul Karsak,et al.  A fuzzy multiple objective programming approach for the selection of a flexible manufacturing system , 2002 .

[6]  Wang Yingxia,et al.  Application of Fuzzy Decision Optimum Model in Selecting Supplier , 2005 .

[7]  Gülay Barbarosoğlu,et al.  An Application of the Analytic Hierarchy Process to the Supplier Selection Problem , 1997 .

[8]  E. Ertugrul Karsak,et al.  Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data , 2008 .

[9]  Qiang Wu,et al.  Application of grey numerical model to groundwater resource evaluation , 2005 .

[10]  Waldemar Koodziejczyk.  Orlovsky's concept of decision-making with fuzzy preference relation—Further results , 1986 .

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

[12]  H. Zimmermann,et al.  Fuzzy Set Theory and Its Applications , 1993 .

[13]  Denis Borenstein,et al.  Intelligent decision support system for flexible manufacturing system design , 1998, Ann. Oper. Res..

[14]  R. Venkata Rao,et al.  Evaluating flexible manufacturing systems using a combined multiple attribute decision making method , 2008 .

[15]  Ajith Abraham,et al.  FMS SELECTION UNDER DISPARATE LEVEL- OF-SATISFACTION OF DECISION MAKING USING AN INTELLIGENT FUZZY-MCDM MODEL , 2008 .

[16]  Mario T. Tabucanon,et al.  A multiple-criteria approach to machine selection for flexible manufacturing systems , 1994 .

[17]  C. Hwang.  Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .

[18]  Robert M. Monczka,et al.  Cost-Based Supplier Performance Evaluation , 1988 .

[19]  M. Shamsuzzaman,et al.  Applying linguistic criteria in FMS selection: fuzzy‐set‐AHP approach , 2003 .

[20]  Ali Shanian,et al.  TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell , 2006 .

[21]  S. Talluri,et al.  A Model for Strategic Supplier Selection , 2002 .

[22]  Y. Gousty,et al.  An integrated approach to project evaluation and selection , 1988 .

[23]  Toshiyuki Sueyoshi,et al.  A unified framework for the selection of a Flexible Manufacturing System , 1995 .

[24]  Markku Kuula,et al.  Selecting a flexible manufacturing system using multiple criteria analysis , 1991 .

[25]  G. John Miltenburg,et al.  Evaluating Flexible Manufacturing Systems , 1987 .

[26]  Daniel L. Smytka,et al.  Total Cost Supplier Selection Model: A Case Study , 1993 .

[27]  Desheng Dash Wu,et al.  The method of grey related analysis to multiple attribute decision making problems with interval numbers , 2005, Math. Comput. Model..

[28]  James L. Zydiak,et al.  Vendor selection with price breaks , 1993 .

[29]  Srinivas Talluri,et al.  A nonparametric stochastic procedure for FMS evaluation , 2000, Eur. J. Oper. Res..

[30]  R. Venkata Rao,et al.  Flexible Manufacturing System selection using an improved compromise ranking method , 2009 .

[31]  GuoDong Li,et al.  A grey-based decision-making approach to the supplier selection problem , 2007, Math. Comput. Model..

[32]  E. Ertugrul Karsak,et al.  Distance-based fuzzy MCDM approach for evaluating flexible manufacturing system alternatives , 2002 .

[33]  Bertrand Mareschal,et al.  Weight stability intervals in multicriteria decision aid , 1988 .

[34]  Wade M. Jackson,et al.  A GOAL PROGRAMMING MODEL FOR PURCHASE PLANNING , 1983 .

[35]  Joseph Sarkis,et al.  A decision model for evaluation of flexible manufacturing systems in the presence of both cardinal and ordinal factors , 1999 .

[36]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[37]  Gwo-Hshiung Tzeng,et al.  Combining grey relation and TOPSIS concepts for selecting an expatriate host country , 2004, Math. Comput. Model..

[38]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[39]  Kathryn E. Stecke,et al.  Formulation and Solution of Nonlinear Integer Production Planning Problems for Flexible Manufacturing Systems , 1983 .

[40]  Shiang-Tai Liu,et al.  A fuzzy DEA/AR approach to the selection of flexible manufacturing systems , 2008, Comput. Ind. Eng..

[41]  Sai Hong Tang,et al.  Improvement of a Grey Based Method for supplier selection problem , 2008 .