Application of MADM methods as MOORA and WEDBA for ranking of FMS flexibility

Article history: Received: October 19, 2018 Received in revised format: October 25, 2018 Accepted: December 26, 2018 Available online: December 26, 2018 Flexibility has been cited as a key factor to enhance the performance of flexible manufacturing system (FMS). The main aim of this paper is to rank the flexibility of FMS. The ranking decisions are complex in the manufacturing field to analyze a number of alternatives based on a set of some attributes. In this research, two MADM methods i.e. MOORA (i.e. multi-objective optimization on the basis of ratio analysis) and weighted Euclidean distance based approach (WEDBA) are used for ranking of flexibility in FMS for new part development. MOORA approach can give decision with or without considering relative importance of attributes i.e. attribute weights. While in WEDBA, integrated attribute weights are used for evaluation which included the subjective and objective weights of attributes. Objective weights are calculated by entropy method and subjective weights are calculated by analytic hierarchy process. MOORA is applied in two ways i.e. ratio based and reference point analysis. Ranking of fifteen flexibility of FMS done on the basis fifteen variables which effect flexibility of FMS. The results of MOORA and WEDBA approach shows that product flexibility has the top most flexibility in fifteen flexibilities and programme flexibility has the least impact in fifteen flexibilities. © 2019 by the authors; licensee Growing Science, Canada.

[1]  Jon C. Dattorro,et al.  Convex Optimization & Euclidean Distance Geometry , 2004 .

[2]  Ravi Shankar,et al.  A comparative study of multi criteria decision making approaches for risks assessment in supply chain , 2015, Int. J. Bus. Inf. Syst..

[3]  Tilak Raj,et al.  Evaluation of flexibility in FMS by VIKOR methodology , 2014 .

[4]  S. Chakraborty,et al.  Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection , 2012 .

[5]  Tilak Raj,et al.  Modeling and analysis of FMS performance variables by ISM, SEM and GTMA approach , 2016 .

[6]  J. Gower Euclidean Distance Geometry , 1982 .

[7]  R. Venkata Rao,et al.  Evaluating flexible manufacturing systems using Euclidean distance-based integrated approach , 2011 .

[8]  Tilak Raj,et al.  Evaluating the Variables Affecting Flexibility in FMS by Exploratory and Confirmatory Factor Analysis , 2013 .

[9]  Tilak Raj,et al.  Ranking of Flexibility in Flexible Manufacturing System by Using a Combined Multiple Attribute Decision Making Method , 2013 .

[10]  Tilak Raj,et al.  Modelling and analysis of FMS productivity variables by ISM, SEM and GTMA approach , 2014 .

[11]  Chen-Hua Chung,et al.  An examination of flexibility measurements and performance of flexible manufacturing systems , 1996 .

[12]  Willem Karel M. Brauers,et al.  Multi-objective seaport planning by MOORA decision making , 2013, Ann. Oper. Res..

[13]  Tilak Raj,et al.  A hybrid approach using ISM and modified TOPSIS for the evaluation of flexibility in FMS , 2015 .

[14]  Tilak Raj,et al.  Modelling the factors affecting flexibility in FMS , 2012 .

[15]  Vineet Jain,et al.  Application of combined MADM methods as MOORA and PSI for ranking of FMS performance factors , 2018, Benchmarking: An International Journal.

[16]  Tilak Raj,et al.  Evaluation of flexibility in FMS using SAW and WPM , 2013 .

[17]  Shankar Chakraborty,et al.  Applications of the MOORA method for decision making in manufacturing environment , 2011 .

[18]  Edmundas Kazimieras Zavadskas,et al.  Multimoora Optimization Used to Decide on a Bank Loan to Buy Property , 2011 .

[19]  Tilak Raj,et al.  Tool life management of unmanned production system based on surface roughness by ANFIS , 2017, Int. J. Syst. Assur. Eng. Manag..

[20]  E. Zavadskas,et al.  Project management by multimoora as an instrument for transition economies , 2010 .

[21]  V. B. Shinde,et al.  Optimization of welding process parameters using MOORA method , 2013 .

[22]  Edmundas Kazimieras Zavadskas,et al.  The MOORA method and its application to privatization in a transition economy , 2006 .

[23]  Sanchoy K. Das,et al.  The measurement of flexibility in manufacturing systems , 1996 .

[24]  Tilak Raj,et al.  Evaluating the intensity of variables affecting flexibility in FMS by graph theory and matrix approach , 2015 .

[25]  R. Venkata Rao,et al.  Weighted Euclidean distance based approach as a multiple attribute decision making method for plant or facility layout design selection , 2012 .

[26]  W. Brauers,et al.  Regional development in Lithuania considering multiple objectives by the MOORA method , 2010 .

[27]  E. Zavadskas,et al.  Robustness of the multi‐objective MOORA method with a test for the facilities sector , 2009 .

[28]  Vineet Jain,et al.  Identification of performance variables which affect the FMS: a state-of-the-art review , 2018 .

[29]  Tilak Raj,et al.  Modeling and analysis of FMS flexibility factors by TISM and fuzzy MICMAC , 2015, Int. J. Syst. Assur. Eng. Manag..

[30]  Sandeep Grover,et al.  Decision making over the production system life cycle: MOORA method , 2014, Int. J. Syst. Assur. Eng. Manag..