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The connotation of digital twin, and the construction and application method of shop-floor digital twin

机译：数字双胞胎的内涵，以及车间数字双胞胎施工与应用方法

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摘要

Digital twin (DT) technology provides a novel, feasible, and clear implementation path for the realization of smart manufacturing and cyber-physical systems (CPS). Currently, DT is applied to all stages of the product lifecycle, including design, production, and service, although its application in the production stage is not yet extensive. Shop-floor digital twin (SDT) is a digital mapping model of the corresponding physical shop-floor. How to build and apply SDT has always been challenging when applying DT technology in the production phase. To address the existing problems, this paper first reviews the origin and evolution of DT, including its application status in the production stage. Then, an implementation framework for the construction and application of SDT is proposed. Three key implementation techniques are explained in detail: the five-dimensional modeling of SDT; DT-based 3D visual and real-time monitoring of shop-floor operating status; and prediction of shop-floor operating status based on SDT using Markov chain. A DT-based visual monitoring and prediction system (DT-VMPS) for shop-floor operating status is developed, and the feasibility and effectiveness of the proposed method are demonstrated through the use of an engineering case study. Finally, a summary of the contributions of the paper is given, and future research issues are discussed.
机译：数字双（DT）技术提供了实现智能制造和网络物理系统（CPS）的新颖，可行和明确的实现路径。目前，DT适用于产品生命周期的所有阶段，包括设计，生产和服务，尽管其在生产阶段的应用尚未广泛。车间数字双胞胎（SDT）是相应物理车间的数字映射模型。如何构建和应用SDT在生产阶段应用DT技术时一直在具有挑战性。为了解决现有问题，本文首先审查了DT的起源和演进，包括其在生产阶段的应用现状。然后，提出了用于SDT的构造和应用的实施框架。详细解释了三个关键实施技术：SDT的五维建模;基于DT的3D视觉和实时监控车间运行状态;基于SDT的基于SDT的商业地位预测Markov链。开发了一种基于DT的视觉监控和预测系统（DT-VMP），通过使用工程案例研究，证明了所提出的方法的可行性和有效性。最后，给出了本文贡献的摘要，并讨论了未来的研究问题。

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