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离散制造行业数字化转型与智能化升级路径研究
Paths for the Digital Transformation and Intelligent Upgrade of China’s Discrete Manufacturing Industry
在传统离散制造业加快转型升级的背景下，发展智能制造将推进离散制造业提质增效、促进行业由大变强，因此数字化转型与智能化升级成为必然选择。我国离散制造各细分行业存在极大的差异性，相应的数字化转型与智能化升级路径也存在多样性，因而需要结合企业实际探讨具体实施举措。本文提炼了离散制造行业的典型特性，梳理了离散制造行业数字化转型与智能化升级面临的挑战，阐述了包括先进制造技术、新一代信息技术、新一代人工智能在内的共性关键技术；系统调研了我国离散型制造企业数字化转型与智能化升级的4 个典型案例，力求呈现领域前沿应用进展，进而提出了突破智能制造关键使能技术，研发智能制造装备，建设数字化、智能化车间和工厂，提供数字化、智能化服务，构建标准与安全体系等重点发展任务。研究建议，加快示范应用，突出“中国制造”，培育高新技术人才，制定相应的法律法规，以此推动我国离散制造行业的高质量发展。
The discrete manufacturing industry in China is currently being transformed and upgraded. Digital transformation and intelligent upgrade is an inevitable choice for China’s discrete manufacturing industry, as intelligent manufacturing can promote the quality, efficiency, and competitiveness of discrete manufacturing. The sub-sectors of discrete manufacturing in China differs significantly and requires diversified paths for digital transformation and intelligent upgrade. In this paper, we first summarize the typical characteristics of the discrete manufacturing industry, explore the challenges regarding the digital transformation and intelligent upgrade of the industry, and elaborate the common key technologies including advanced manufacturing, new-generation information, and new-generation artificial intelligence. Subsequently, we investigate four typical cases to present the frontier application progress in the field in China, and propose the following key development tasks: (1) achieving breakthroughs in keys enabling technologies for intelligent manufacturing, (2) developing intelligent manufacturing equipment, (3) building digital and intelligent workshops and factories, (4) providing digital and intelligent services, and (5) building standards and safety systems. Furthermore, it is necessary to accelerate pilot application, highlight domestication, increase the reserve of high-tech talents, and formulate relevant laws and regulations, to promote the high-quality development of China’s discrete manufacturing industry.
智能制造 / 离散制造行业 / 数字化转型 / 智能化升级 / 拓扑优化 / 车间调度 深度学习 /
intelligent manufacturing / discrete manufacturing industry / digital transformation and intelligent upgrade / topological optimization / workshop scheduling / deep learning
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