将趋势转化为行动:基于模拟的数字孪生架构,促进战略和运营决策

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Romão Santos, Henrique Piqueiro, Rui Dias, Cláudia D. Rocha
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引用次数: 0

摘要

在当今充满活力的制造业领域,整合数字技术已成为提高运营效率和决策流程的关键。本文介绍了一种新颖的系统架构,该架构将基于仿真的数字孪生系统(DT)与制造业的新兴趋势相结合,以增强决策能力,并附有详细的技术方法,包括每个组件的协议和技术。DT 利用先进的仿真技术对生产流程进行实时建模、监控和优化,从而促进战略和运营决策。作为对 DT 的补充,人工智能、增材制造、协作机器人、自动驾驶汽车和连接性进步等趋势技术被战略性地整合在一起,以提高运营效率,促进制造即服务(MaaS)模式的采用。在 MaaS 供应商背景下进行的一项案例研究,部署在一个配备先进机器人系统的工业实验室中,展示了使用基于仿真的 DT 优化动态作业车间配置的实际应用,展示了提高运营效率和资源利用率的策略。工业实验的结果非常令人鼓舞,强调了扩展到更复杂的工业系统的潜力,特别强调纳入可持续性和再制造原则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transitioning trends into action: A simulation-based Digital Twin architecture for enhanced strategic and operational decision-making
In the dynamic realm of nowadays manufacturing, integrating digital technologies has become paramount for enhancing operational efficiency and decision-making processes. This article presents a novel system architecture that integrates a Simulation-based Digital Twin (DT) with emerging trends in manufacturing to enhance decision-making, accompanied by a detailed technical approach encompassing protocols and technologies for each component. The DT leverages advanced simulation techniques to model, monitor, and optimize production processes in real time, facilitating both strategic and operational decision-making. Complementing the DT, trending technologies such as artificial intelligence, additive manufacturing, collaborative robots, autonomous vehicles, and connectivity advancements are strategically integrated to enhance operational efficiency and facilitate the adoption of the Manufacturing as a Service (MaaS) paradigm. A case study within a MaaS supplier context, deployed in an industrial laboratory with advanced robotic systems, demonstrates the practical application of optimizing dynamic job-shop configurations using Simulation-based DT, showcasing strategies to improve operational efficiency and resource utilization. The results of the industrial experiment were highly encouraging, underscoring the potential for extension to more intricate industrial systems, with particular emphasis on incorporating sustainability and remanufacturing principles.
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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