Evaluating the flexibility in a manufacturing system using fuzzy multi-attribute group decision-making with multi-granularity linguistic information
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Evaluation of flexibility in a manufacturing system development in operations management is important to determine the competitiveness of manufacturing system, and is being increasing discussed in the literature on manufacturing system. This paper presents a fuzzy group decision-making model with different linguistic term sets (multi-granularity linguistic term sets) for evaluating manufacturing flexibility development, where the performance rating of manufacturing systems under flexibility metrics and the importance grade of all flexibility dimensions are assessed in linguistic terms represented by trapezoidal fuzzy numbers. The linguistic term sets chosen by decision-makers will have more or less terms. This paper proposes a procedure to assess the degree of manufacturing flexibility in a fuzzy environment by a fuzzy fusion method of linguistic information. While evaluating the degree of manufacturing flexibility, one may find the need for improving manufacturing flexibility, and determine the dimensions of manufacturing flexibility as the best direction to improvement. Example using a case of leading Taiwan firm in the bicycle industry is used to illustrate the computational process of the proposed method.
KeywordsManufacturing flexibility Fuzzy multi-attribute group decision-making Fuzzy numbers Maximum entropy ordered weighted averaging operators
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