Evaluating the Ranking of Performance Variables in Flexible Manufacturing System through the Best-Worst Method

Designs Pub Date : 2024-01-22 DOI:10.3390/designs8010012
A. Bagherian, Gulshan Chauhan, A. Srivastav, Rajiv Kumar Sharma
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Abstract

Flexible Manufacturing Systems (FMSs) provide a competitive edge in the ever-evolving manufacturing landscape, offering the agility to swiftly adapt to changing customer demands and product lifecycles. Nevertheless, the complex and interconnected nature of FMSs presents a distinct challenge: the evaluation and prioritization of performance variables. This study clarifies a conspicuous research gap by introducing a pioneering approach to evaluating and ranking FMS performance variables. The Best-Worst Method (BWM), a multicriteria decision-making (MCDM) approach, is employed to tackle this challenge. Notably, the BWM excels at resolving intricate issues with limited pairwise comparisons, making it an innovative tool in this context. To implement the BWM, a comprehensive survey of FMS experts from the German manufacturing industry was conducted. The survey, which contained 34 key performance variables identified through an exhaustive literature review and bibliometric analysis, invited experts to assess the variables by comparing the best and worst in terms of their significance to overall FMS performance. The outcomes of the BWM analysis not only offer insights into the factors affecting FMS performance but, more importantly, convey a nuanced ranking of these factors. The findings reveal a distinct hierarchy: the “Quality (Q)” factor emerges as the most critical, followed by “Productivity (P)” and “Flexibility (F)”. In terms of contributions, this study pioneers a novel and comprehensive approach to evaluating and ranking FMS performance variables. It bridges an evident research gap and contributes to the existing literature by offering practical insights that can guide manufacturing companies in identifying and prioritizing the most crucial performance variables for enhancing their FMS competitiveness. Our research acknowledges the potential introduction of biases through expert opinion, delineating the need for further exploration and comparative analyses in diverse industrial contexts. The outcomes of this study bear the potential for cross-industry applicability, laying the groundwork for future investigations in the domain of performance evaluation in manufacturing systems.
通过最佳-最差法评估柔性制造系统中的性能变量排序
柔性制造系统(FMS)为不断发展的制造业提供了竞争优势,能够迅速适应不断变化的客户需求和产品生命周期。然而,柔性制造系统的复杂性和相互关联性带来了一个独特的挑战:性能变量的评估和优先排序。本研究通过引入一种开创性的方法来评估和排序 FMS 性能变量,澄清了一个明显的研究空白。最佳-最差法(BWM)是一种多标准决策(MCDM)方法,被用来应对这一挑战。值得注意的是,BWM 擅长解决配对比较有限的复杂问题,使其成为这方面的创新工具。为了实施 BWM,我们对德国制造业的 FMS 专家进行了一次全面调查。该调查包含通过详尽的文献回顾和文献计量分析确定的 34 个关键绩效变量,并邀请专家对这些变量进行评估,比较最佳和最差变量对 FMS 整体绩效的意义。BWM 分析的结果不仅让人们深入了解了影响财务管理系统绩效的因素,更重要的是,它传达了对这些因素的细微排序。研究结果揭示了一个明显的层次结构:"质量(Q)"因素最为关键,其次是 "生产率(P)"和 "灵活性(F)"。就贡献而言,本研究开创了一种新颖而全面的方法,用于对财务管理系统的绩效变量进行评估和排序。它弥补了一个明显的研究空白,并为现有文献做出了贡献,提供了实用的见解,可指导制造企业识别最关键的绩效变量并确定其优先次序,以增强其财务管理系统的竞争力。我们的研究承认,专家意见可能会带来偏差,因此需要在不同行业背景下进行进一步探索和比较分析。本研究的成果具有跨行业适用性的潜力,为今后在制造系统绩效评估领域开展调查奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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