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数字孪生车间制造运营管理平台 被引量:3

Digital twin shop-floor manufacturing operations management platform
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摘要 数字孪生使能的制造信息物理融合是数字经济时代制造业发展的主流方向,数字孪生车间作为制造基础单元,能够基于可信数据和模型的融合决策实现面向多场景适配的制造运营管理能力提升。针对制造运营管理精益化、柔性化、智能化发展需求,以及制造运营管理能力与物理需求难适配、制造运营管理模式与物理状态难适用、制造运营管理策略与物理场景难适应的问题,提出了数字孪生车间制造运营管理平台,阐述了其系统组成、特点和关键技术。在此基础上,随着制造运营管理向着包含物理资源和虚拟资源的跨组织、跨企业智能化协同运营延伸,提出了跨组织/跨企业的“组织管理规范洞察决策改善”协同运营管理策略,为支撑车间内、企业内、跨企业等制造运营管理理论研究和应用落地提供系列理论和方法参考。 Cyber-physical integration in manufacturing enabled by digital twins is the mainstream direction of manufacturing development in the digital economy era.As a basic unit of manufacturing,digital twin shop-floors can improve manufacturing operation management capabilities to adapt to multiple scenarios based on fusion decisions of trusted data and models.A digital twin shop-floor manufacturing operation management platform is proposed to address the needs of lean,flexible and intelligent manufacturing operation management,as well as the difficulties in adapting manufacturing operation management capabilities to physical requirements,adapting manufacturing operation management modes to physical states,and adapting manufacturing operation management strategies to physical scenarios.Its system composition,characteristics and key technologies are also elaborated and discussed respectively.On this basis,as manufacturing operation management extends towards cross-organization and cross-enterprise intelligent collaboration including physical resources and virtual resources,a collaborative operation management strategy of“organization-management-standardization-insight-decision-making-improvement”for intelligent production control was proposed.It provided a series of theoretical and methodological references to support theoretical research and application of manufacturing operations management within shop-floors,within enterprises,and across enterprises.
作者 张永平 左颖 刘博 胡天亮 刘庭煜 刘晓军 吕海洋 朱毅明 施一明 吴恒 何宏宏 孙翰林 张奕帆 胡鹏飞 邹孝付 李瑞琪 王子同 陶飞 ZHANG Yongping;ZUO Ying;LIU Bo;HU Tianliang;LIU Tingyu;LIU Xiaojun;LYU Haiyang;ZHU Yiming;SHI Yiming;WU Heng;HE Honghong;SUN Hanlin;ZHANG Yifan;HU Pengfei;ZOU Xiaofu;LI Ruiqi;WANG Zitong;TAO Fei(School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China;School of Mechanical Engineering,Shandong University,Jinan 250002,China;School of Mechanical Engineering,Southeast University,Nanjing 210096,China;SINOMACH Intelligence Technology Research Institute Co.,Ltd.,Beijing 100083,China;Hollysys Technology Group Co.,Ltd.,Beijing,100176,China;College of Control Science and Engineering,Zhejiang University,Hangzhou 310027,China;Institute of Software,Chinese Academy of Sciences,Beijing 100190,China;Internet of Things Research Center,China Electronics Standardization Institute,Beijing 100010,China;Sino-French Engineer School,Beihang University,Beijing 100191,China;Institute of Artificial Intelligence,Beihang University,Beijing 100191,China;Digital Twin Research Center,International Research Institute for Multidisciplinary Science,Beihang University,Beijing 100191,China)
出处 《计算机集成制造系统》 EI CSCD 北大核心 2024年第1期1-13,共13页 Computer Integrated Manufacturing Systems
基金 国家自然科学基金资助项目(52275471,52105500) 新基石科学基金会“科学探索奖”资助项目。
关键词 数字孪生车间 制造运营管理 数模融合 协同运营 digital twin shop-floor manufacturing operations management digital-model integration collaborative operation
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