Flexible Manufacturing System Selection under Disparate Level-of-Satisfaction of Decision Maker using Intelligent Fuzzy-MCDM Model

This Chapter outlines an intelligent fuzzy-MCDM model for appropriate selection of Flexible Manufacturing System (FMS) in conflicting criteria environment. A holistic methodology has been developed for finding out the “optimal FMS” from a set of candidate-FMSs. This method trade-offs among various parameters, viz., design parameters, economic considerations, etc., affecting the FMS selection process in multi-criteria decision-making environment. The proposed method calculates the global priority values (GP) for functional, design factors and other important attributes by eigen-vector method of pair-wise comparison. These GPs are used as Subjective Factor Measures (SFMs) in determining selection index (SI). The proposed fuzzified methodology is equipped with the capability of determining changes in the FMS selection process that results from making changes in the parameters of the model. The model achieves balancing among criteria. Relationships among the degree of fuzziness, level of satisfaction and the selection indices (SI) of the MCDM methodology guide decision-makers (DM) under tripartite fuzzy environment in selecting their choice trading-off with a pre-determined allowable fuzziness. The measurement of level-of-satisfaction during making the appropriate selection of FMS is carried out.