A Hybrid Framework to Prioritize the Performance Metrics of Reconfigurable Manufacturing System: An Integrated Fuzzy AHP–TOPSIS approach
Abstract The Reconfigurable Manufacturing System (RMS) meets the challenges of dynamic customer demands, technological advancements, and reducing lead time, among other things. It is necessary to have a framework that can assist in increasing RMS adoption as well as evaluating its performance. The present study seeks to develop a hybrid framework for prioritizing performance metrics of RMS that helps the designers of the manufacturing system in decision making. A total of 31 indicators for RMS are identified through a literature survey, the weight of each indicator is computed by Fuzzy-AHP (Analytic Hierarchy Process) method and the Fuzzy-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is used to prioritize 22 performance metrics of RMS. The findings of the presented study reveal that among all the main indicators; smart factory indicators have the highest weightage followed by strategy and policy indicators. The prioritization of performance metrics shows that lead time, reconfiguration time, and product flexibility are the top three most important performance metrics for RMS. The feasibility and appropriateness of the framework is tested through a case application of the manufacturing organization. The framework developed has a high capacity to assist designers during the adoption of the RMS and will facilitate the identification of the relevant parameters. Authors believe that researchers and professionals will find this study as a ready reference for stepwise adoption of RMS. The study presented here is likely the first to present a hybrid framework in which a set of indicators and performance metrics are presented together.