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A data- and knowledge-driven framework for digital twin manufacturing cell

机译:数字孪生制造单元的数据和知识驱动框架

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Intelligent manufacturing is regarded as the next generation manufacturing mode with powerful learning and cognitive capacities enabled by new generation information technologies such as Internet of Things, big data analytics, edge computing and artificial intelligence. To provide an insight into intelligent manufacturing, this paper takes autonomous manufacturing cell as implementation scenario and proposes a data- and knowledge-driven framework for digital twin manufacturing cell (DTMC), which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimizing and controlling strategy. In addition, three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analyzed. Then, the implementing methods of DTMC are introduced through a thus constructed digital twin robot, and the usage of data and knowledge for supporting the automous operations of DTMC is also discussed. Finally, benefits of DTMC in smart product-service systems (PSS) and its current challenges are summarized.
机译:智能制造被认为是下一代制造模式,它具有强大的学习和认知能力,这是由诸如物联网,大数据分析,边缘计算和人工智能等新一代信息技术实现的。为了提供对智能制造的见解,本文以自主制造单元为实施方案,并提出了一种由数据和知识驱动的数字孪生制造单元(DTMC)框架,该框架可以通过智能感知,模拟,理解,预测,优化和控制策略。另外,分析了支持上述策略的三种关键使能技术,包括数字孪生模型,动态知识库和基于知识的智能技能。然后,通过这样构造的数字孪生机器人介绍了DTMC的实现方法,并讨论了支持DTMC自动运行的数据和知识的使用。最后,总结了DTMC在智能产品服务系统(PSS)中的优势及其当前的挑战。

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