分析数字双胞胎在发展弹性可持续制造供应链中的作用:灰色影响分析(GINA)方法

IF 12.9 1区 管理学 Q1 BUSINESS Technological Forecasting and Social Change Pub Date : 2024-10-16 DOI:10.1016/j.techfore.2024.123763
Gaurvendra Singh , R. Rajesh , Subhas Chandra Misra , Shubhendu Singh
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引用次数: 0

摘要

数字化举措和技术对于风险管理以及在中断和故障期间维持可持续的制造系统至关重要。本研究确定并分析了数字双胞胎对制造供应链(MSC)的影响,以增强生产系统的弹性-可持续能力。可持续性和复原力是两个相互关联的概念,最近由于供应链的复杂性不断增加而受到研究人员的关注。本研究通过现有文献和专家意见,确定了数字化驱动的供应链管理中的十七个弹性可持续因素。这项研究工作采用了一种新技术--灰色影响分析法(GINA),对这些因素进行因果分析。经过分析,根据影响总得分,可见性(VIS)和协调性(COO)分别排在第一和第二位。这两个因素是影响最大的因素,因为在 MSC 中采用了数字孪生(DT)。在弹性可持续系统的供应链管理中采用数字孪生将提高可视性,供应链参与者必须相互协作和联系,以有效管理风险,确保数字供应链中所有环节的可持续性。这项研究对从事数字驱动的供应链管理的从业人员、研究人员和管理人员很有帮助。
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Analyzing the role of digital twins in developing a resilient sustainable manufacturing supply chain: A grey influence analysis (GINA) approach
Digitalization initiatives and technology are essential for risk management and for maintaining a sustainable manufacturing system during disruptions and failures. This research has identified and analyzed the impact of digital twins on the manufacturing supply chain (MSC) in enhancing the resilient-sustainable capabilities of the production systems. Both sustainability and resilience are interrelated concepts and have recently gotten attention from researchers because of the rising complexity in the supply chain. This research study has identified the seventeen resilient sustainable factors in the digitally driven MSC through extant literature and experts' opinions. This research work has used a novel technique, grey influence analysis (GINA), for causal analysis of the factors. After analysis, based on total influence score, visibility (VIS) and coordination (COO) ranked first and second, respectively. These are the most influencing factors because of the adoption of digital twins (DTs) in the MSC. The DT in MSC for the resilient-sustainable systems will improve the visibility, and supply chain players must collaborate and connect to effectively manage risks and ensure the sustainability of all links in the digital supply chain. This research study is helpful for practitioners, researchers, and managers working in digitally driven MSC.
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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