Data-driven prioritization of performance variables for flexible manufacturing systems: revealing key metrics with the best–worst method

Abstract

In the dynamic landscape of evolving customer preferences and intense competition, manufacturing firms grapple with the imperative to reassess their strategies in product design, operations, and process validation to maintain a competitive edge. This study clarifies this challenge by diligently evaluating flexible manufacturing system (FMS) performance in the German manufacturing sector. Employing a survey-based inquiry questionnaire and the best and worst method (BWM), we meticulously analyze 34 performance variables, classifying them into three primary factors: “quality (Q),” “productivity (P),” and “flexibility (F).” The study emphasizes the essential role of quality, followed by flexibility and productivity as performance parameters in achieving its objectives. To ensure a robust analysis, a comprehensive review of scientific publications in the bibliometric overview was conducted, offering a comprehensive analysis of 272 scientific publications retrieved from the “Dimensions and Web of Science” database spanning 2013 to 2023. The BWM calculations were executed utilizing Excel software, providing a systematic approach to assessing the weights of 34 FMS performance variables. This methodological thoroughness sheds light on the qualitative aspects of FMS elements not previously explored by major manufacturing firms. The theoretical implications of this study introduce a novel theoretical framework that integrates queuing theory and decision theory. Additionally, the research validates the resource-based view theory, emphasizing its relevance in delineating the competitive advantage of firms implementing FMS through empirical analysis. On the business front, the hierarchical arrangement of FMS performance metrics offers managers invaluable insights into specific factors amenable to enhancement, empowering them to adapt efficiently to fluctuations in the manufacturing process. By prioritizing key FMS variables, managers can make well-informed decisions, optimizing manufacturing endeavors in response to dynamic market conditions. This study presents a significant contribution to the examination of FMS within the German manufacturing sector. It not only provides a basis for informed decision-making but also offers a roadmap for targeted actions to enhance manufacturing performance. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.