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Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing

机译:知识驱动的数字双制制造单元致力于智能制造

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摘要

Rapid advances in new generation information technologies, such as big data analytics, internet of things (IoT), edge computing and artificial intelligence, have nowadays driven traditional manufacturing all the way to intelligent manufacturing. Intelligent manufacturing is characterised by autonomy and self-optimisation, which proposes new demands such as learning and cognitive capacities for manufacturing cell, known as the minimum implementation unit for intelligent manufacturing. Consequently, this paper proposes a general framework for knowledge-driven digital twin manufacturing cell (KDTMC) towards intelligent manufacturing, which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimising and controlling strategy. Three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analysed, which equip KDTMC with the capacities of self-thinking, self-decision-making, self-execution and self-improving. The implementing methods of KDTMC are also introduced by a thus constructed test bed. Three application examples about intelligent process planning, intelligent production scheduling and production process analysis and dynamic regulation demonstrate the feasibility of KDTMC, which provides a practical insight into the intelligent manufacturing paradigm.
机译:新一代信息技术的快速进步,如大数据分析,事物互联网(物联网),边缘计算和人工智能,现在已经驱动了传统的制造一直到智能制造。智能制造的特点是自主性和自我优化,这提出了新的要求,例如制造电池的学习和认知能力,称为智能制造的最低实现单元。因此,本文为知识驱动的数字双制造单元(KDTMC)提出了一种智能制造的一般框架,这可以通过智能感知,模拟,理解,预测,优化和控制策略来支持自主制造。分析了三个关键能力技术,包括数字双模型,动态知识库和基于知识的智能技能,用于支持上述战略,以自我思维,自我决策,自我执行和自我提升的能力配备KDTMC 。 KDTMC的实施方法也通过由此构造的试验台引入。关于智能流程规划,智能生产调度和生产过程分析和动态调节的三种应用示例展示了KDTMC的可行性,这为智能制造范例提供了实际洞察力。

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