摘要
小批量及定制化生产模式下,由资源、流程不确定性引发的复杂动态生产环境对大型多单元生产系统的运行控制精度提出了更高的要求。如何面向随机产生的动态性,对生产单元的执行状态进行精准建模与实时反映,并通过多单元在线联动决策实现对系统的适应性、迭代式、精细化管控来支持各环节高效协同运作是大型多单元生产物流系统过程控制的关键挑战。以工业园区'产—运—存'三类典型单元的实时联动运作为研究对象,在数字孪生的框架下,提出跨单元的数字孪生联动决策信息架构:通过'物理环境—虚拟模型'的动态精准映射与实时反馈控制,并采用目标级联法对虚拟层中多个具有独立决策且联动运作的'产—运—存'决策单元以全局优化、分布控制的模式进行系统性协调,实现大型系统的在线联动决策。最后以某大型化工生产企业的多单元联动生产过程为例,基于其实际生产数据对所建立的联动决策模型及目标级联法定量联动方法进行仿真和对比分析,结果表明所提方法能够有效实现多单元同步运作,减少生产总成本和订单在库时间。
Under the small batch and customized production mode,the complex and dynamic production environment caused by uncertainty of resources and processes requires higher control accuracy for operation and control of large multi-unit systems.It is a key challenge for process control of large multi-unit production logistics system that how to accurately model and real-time reflect the execution status of production unit and implement the adaptive,iterative and accurate management and control of system to support the efficient collaborative operation of each segment through multi-unit online synchronized decision-making.By taking the real-time synchronized operation of typical industrial park system composed of three typical units of production,transportation and storage as the research object,and under the Digital Twin(DT)framework,the cross-unit synchronized decision-making information architecture was proposed to implement the online synchronized control of large system through the dynamic and precise mapping and real-time feedback control of'physical environment-virtual model'.Meanwhile,the Analytical Target Cascading(ATC)method was adopted to synchronize and control the system systematically in the mode of global optimization and distributed control.By taking the multi-unit synchronized production process of a large chemical production enterprise as an example,the synchronized decision-making model and ATC quantitative synchronized method were simulated,compared and analyzed based on the actual production data.The results showed that the proposed method could effectively realize the multi-unit synchronized operation and reduce the total production cost and the instock time of orders.
作者
周达坚
屈挺
张凯
郭洪飞
闫勉
李从东
黄国全
ZHOU Dajian;QU Ting;ZHANG Kai;GUO Hongfei;YAN Mian;LI Congdong;HUANG Guoquan(Guangdong Provincial Key Lab of CIMS,Guangdong University of Technology,Guangzhou 510006,China;School of Intelligent Systems Science and Engineering,Jinan University,Zhuhai 519070,China;Institute of Physical Internet,Jinan University,Zhuhai 519070,China;School of Management,Jinan University,Guangzhou 510632,China;Departmant of Industrial and Manufacturing Systems Engineering,The University of Hong Kong,Hong Kong 999077,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2019年第6期1576-1590,共15页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(51875251)
广东省自然科学基金重点资助项目(2016A030311041)
国家教育部“蓝火计划”(惠州)产学研联合创新基金资助项目(CXZJHZ201722)
中央高校基本科研业务费专项资金资助项目(11618401)~~
关键词
数字孪生
工业园区
协同决策
联动控制
动态性
化工生产企业
digital twin
industrial park
collaborative decision-making
synchronized control
dynamics
chemical production enterpise