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Fuzzy multiple criteria group decision-making in performance evaluation of manufacturing companies

Salehi Sara

Applied Computer Science

2023

Vol. 19, no 3

28--46

In today's competitive industry landscape, it is crucial to assess manufacturing processes to enhance efficiency. However, identifying the critical factors that impact productivity can be a daunting task due to their intricate nature. To tackle this challenge, we propose a novel approach that combines fuzzy logic with TOPSIS to comprehensively evaluate manufacturing company efficiency. The method presented by the author treats this as a complex MCDM problem and accommodates diverse factors with distinct weights, which are crucial for a thorough efficiency analysis. This approach was applied to evaluate potential manufacturing entities in Cyprus through a three-step process. Firstly, relevant criteria were curated using literature and expert insights, endowing them with linguistic terms that were then translated into fuzzy values. Next, fuzzy TOPSIS evaluated efficiency, and sensitivity analysis gauged the criteria weight impact on decisions. This article introduces a new methodology for holistic manufacturing company evaluation. The synergy of fuzzy-set theory and TOPSIS proves effective amidst the ambiguity inherent in performance measurement. By uniting these methodologies, this study advances manufacturing performance evaluation, aiding informed decision-making. The research contributes a pioneering method to enhance manufacturing efficiency assessment while accommodating uncertainty through fuzzy logic integration.