智能制造专题主编寄语

工程（英文） ›› 2019, Vol. 5 ›› Issue (4) : 595 -596. DOI: 10.1016/j.eng.2019.07.004

智能制造专题主编寄语

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Editorial for the Special Issue on Intelligent Manufacturing

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Engineering, Huazhong University of Science and Technology, Wuhan 430074, China), AuthorCompanyExt(id=1201201950017381018, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159946843691999430, companyId=1201201949967049368, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=^a The State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)])])] 李培根,Vladimir Marik,高亮,Weiming Shen. 智能制造专题主编寄语[J]. 工程（英文）, 2019, 5(4): 595-596 DOI:10.1016/j.eng.2019.07.004

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智能制造是先进信息技术与先进制造技术的深度融合，贯穿于产品设计、制造、服务和回收的全生命周期。其中，智能产品是主体，智能生产是主线，以智能服务为中心的产业模式变革是主题。智能制造将驱动制造系统向敏捷响应、高质高效、个性定制、绿色健康、舒适人性的方向发展。智能制造技术已成为世界制造业发展的一大趋势。

本期智能制造专题收录了智能制造领域的部分最新研究成果，将有力促进该领域的快速发展。本专题包含10篇论文，包括两篇观点论文和8篇研究论文，由来自中国、美国、英国、瑞典、日本、新加坡和澳大利亚等国的有影响力的专家撰写。这些文章阐述了智能制造在以下领域的发展现状。

（1）智能制造的关键技术。

本期智能制造专题介绍的第一类关键技术是大数据和人工智能技术，包括机器学习、深度学习、强化学习、群体智能和跨媒体智能等。近年来，这些技术得到了长足进步，将促进智能制造的加速发展。第二类关键技术是智能制造设计技术。第三类关键技术包括数字孪生和信息物理系统等技术，它们能实现制造中信息空间与物理空间的交互和集成，是实现智能制造的基础。人-信息-物理系统是信息物理系统的扩展，也是智能制造的关键技术之一。它揭示了智能制造的技术机理，也构成了智能制造的技术体系。

（2）智能制造技术的典型应用。

智能制造技术广泛存在于制造业的各个环节。本期智能制造专题介绍了部分智能制造技术的典型应用，将为新技术的应用和推广起到示范作用。第一个典型应用是将生物启发式设计用于情境感知智能产品的设计过程。提出的生物启发式设计框架阐明了利用生物灵感进行智能产品设计的前景，也可用于产品智能化的其他方面，如适应性、位置感知和网络感知等。第二个典型应用是智能机床，机床的发展经历了数控机床、互联网机床和智能机床等三个阶段，它在智能制造中发挥着越来越重要的作用。第三个典型应用是将深度信念网络用于激光焊接状态的在线监测，为基于机器视觉的在线监测系统应用于其他生产过程提供了一定的借鉴。第四个典型应用是将数据驱动的异常诊断系统用于数控机床的加工过程，该技术能提高数控机床的加工质量和效率，也可以用于产品检测、装配等生产过程。工业大数据的私密性与安全性一直是产业界与学术界关注的焦点，本专题的一个研究提出了一种基于雾计算的大数据集成与共享方法，基于雾计算技术将多源数据分析任务分解至本地边缘端执行，通过中间数据的传输与串联实现多源数据的分析，以保障多来源工业数据的协作分析中源数据的私密性与安全性，为解决工业大数据分析中源数据的安全问题提供了一种可行方案。本期专题的最后一个研究提出了基于三个基本范式的智能制造技术升级路线分析模型，总结出中国企业推进智能制造的技术升级路线——“并行推进、融合发展”，该路线有利于指导制造企业、决策者和投资者选择适合自己的智能制造推进路径。

我们感谢所有作者对本期智能制造专题所作的贡献。同时，本专题的研究成果表明，智能制造技术的研究和应用才刚刚开始。未来，将有越来越多的人工智能和大数据技术应用于制造业的方方面面，包括产品设计、生产、服务和回收等各个环节，将推动传统制造模式的根本性变革。