ABSTRACT The worldwide manufacturing industry is facing a wide range of changes. Examples include the diversification of customer demands, increases in labor costs and energy resource costs, environmental pollution, and growth uncertainty. Based on the experience of advanced countries and global manufacturers, smart manufacturing systems (SMS) have the potential to address these. SMS can connect raw materials, production systems, logistic companies, and maintenance schedules using the capabilities of industrial, internet of things (IoT). These connections are creating cyber-physical production systems (CPPS) and linking functions across the entire product lifecycle. These connections are possible today because of the advances in digital manufacturing (DM) technologies that can facilitate factory design, redesign, and analysis in CPPS and help to continuously and efficiently manage factory performance optimization. However, implementing DM today, especially in SMEs, is difficult because the required interface standards and data schema do not exist – unlike other technologies and system such as CAD, PLM, MES, and SCM. This paper describes an approach to design and develop such a data schema based on a reference activity model developed by NIST. The paper then develops a cloud-based DM system based on the data schema. Lastly, its application cases are described, and application effects are discussed.

中文翻译：

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基于智能制造的互操作数据模式的基于云的数字孪生制造系统

摘要 全球制造业正面临着广泛的变化。例子包括客户需求的多样化、劳动力成本和能源资源成本的增加、环境污染和增长的不确定性。基于先进国家和全球制造商的经验，智能制造系统 (SMS) 具有解决这些问题的潜力。SMS 可以使用工业物联网 (IoT) 的功能连接原材料、生产系统、物流公司和维护计划。这些连接正在创建网络物理生产系统 (CPPS) 并在整个产品生命周期中链接功能。由于数字制造 (DM) 技术的进步可以促进工厂设计、重新设计、CPPS 中的分析和分析，有助于持续有效地管理工厂绩效优化。然而，今天实施 DM，尤其是在中小企业中实施 DM 很困难，因为所需的接口标准和数据模式不存在——与其他技术和系统（如 CAD、PLM、MES 和 SCM）不同。本文描述了一种基于 NIST 开发的参考活动模型来设计和开发此类数据模式的方法。然后，本文基于数据模式开发了一个基于云的 DM 系统。最后介绍了其应用案例，讨论了应用效果。和单片机。本文描述了一种基于 NIST 开发的参考活动模型来设计和开发此类数据模式的方法。然后，本文基于数据模式开发了一个基于云的 DM 系统。最后介绍了其应用案例，讨论了应用效果。和单片机。本文描述了一种基于 NIST 开发的参考活动模型来设计和开发此类数据模式的方法。然后，本文基于数据模式开发了一个基于云的 DM 系统。最后介绍了其应用案例，讨论了应用效果。