Digital Twins in Supply Chain Operations Bridging the Physical and Digital Worlds using AI.

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Manuel Enrique, Chenet Zuta, Chaitanya Koneti, Dr Olivares Zegarra, Venus Flor, Marina Carvajal-Ordoñez
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引用次数: 0

Abstract

Digital Twins (DTs) are revolutionizing supply chain operations by creating dynamic digital replicas of physical assets, processes, and systems. This paper explores the integration of Artificial Intelligence (AI) with Digital Twins to bridge the physical and digital worlds in supply chain management. By leveraging AI, Digital Twins can analyze real-time data, predict future events, and optimize decision-making processes. This synergy enhances operational efficiency, reduces costs, and improves responsiveness to disruptions. We delve into the architecture of AI-driven Digital Twins, highlighting their components, data flow, and interaction mechanisms. Case studies across different industries demonstrate the practical applications and benefits of this technology. The discussion includes challenges such as data privacy, integration complexity, and the need for standardized protocols. Future research directions focus on advancing AI algorithms for better predictive capabilities and creating more robust, scalable Digital Twin frameworks. This paper underscores the transformative potential of AI-enhanced Digital Twins in creating agile, resilient, and intelligent supply chains. 
供应链运营中的数字双胞胎 利用人工智能架起物理世界与数字世界的桥梁。
数字孪生(DT)通过创建物理资产、流程和系统的动态数字复制品,正在彻底改变供应链运营。本文探讨了人工智能(AI)与数字孪生系统的整合,从而在供应链管理中架起物理和数字世界的桥梁。利用人工智能,Digital Twins 可以分析实时数据、预测未来事件并优化决策流程。这种协同作用可提高运营效率、降低成本并提高对中断的响应速度。我们深入探讨了人工智能驱动的数字孪生系统的架构,重点介绍了其组成部分、数据流和交互机制。不同行业的案例研究展示了这项技术的实际应用和优势。讨论内容包括数据隐私、集成复杂性以及对标准化协议的需求等挑战。未来的研究方向主要集中在改进人工智能算法以提高预测能力,以及创建更强大、可扩展的数字孪生框架。本文强调了人工智能增强型数字孪生在创建敏捷、弹性和智能供应链方面的变革潜力。
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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来源期刊
Journal of Electrical Systems
Journal of Electrical Systems ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
1.10
自引率
25.00%
发文量
0
审稿时长
10 weeks
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