A multi-agent digital twin–enabled decision support system for sustainable and resilient supplier management

Abstract

Industry 4.0 is reshaping the manufacturing landscape, bringing about revolutionary changes in both product manufacturing and collaborative interactions among value chain constituents. Within the manufacturing value chain process, sustainable and resilient supplier management is recognized as a strategic endeavor that drives value creation, such as enhanced product quality, risk mitigation, and improved organizational reputation. Sustainable and resilient supplier management processes necessitate the integration of multiple criteria, efficient supplier coordination, and adaptability to evolving challenges. Nonetheless, conventional supplier management practices primarily rely on expert judgment, focus on the present situation, and lack a robust decision validation mechanism, leading to a limited capability to constitute proactive managerial decision-making under uncertainty. This paper introduces a digitally enabled decision support system for facilitating an intelligent and customized supplier management process in dynamic and complex environments. The system leverages stratified fuzzy decision-making techniques to account for the potential impacts of future events. Additionally, it integrates multi-agent digital twin technology to provide a reliable validation mechanism for assessing the effectiveness of supplier development strategies. The effectiveness of the proposed system was demonstrated through its successful implementation within a multinational solar water pump manufacturing company, highlighting its promising potential for practical applications.