基于数字孪生的智能制造计划管理  

Intelligent Manufacturing Plan Management Based on Digital Twins

作　　者：肖莹莹 王玫[1,2] 郭丽琴 邢驰 庄长辉 Xiao Yingying;Wang Mei;Guo Liqin;Xing Chi;Zhuang Changhui(Beijing Complex Product Advanced Manufacturing Engineering Research Center,Beijing Simulation Center,Beijing 100854,China;State Key Laboratory of Intelligent Manufacturing System Technology,Beijing Institute of Electronic System Engineering,Beijing 100854,China;Science and Technology on Space System Simulation Laboratory,Beijing Simulation Center,Beijing 100854,China)

机构地区：[1]北京市复杂产品先进制造系统工程技术研究中心北京仿真中心,北京100854 [2]复杂产品智能制造系统技术国家重点实验室北京电子工程总体研究所,北京100854 [3]航天系统仿真重点实验室北京仿真中心,北京100854

出　　处：《系统仿真学报》2019年第11期2323-2334,共12页Journal of System Simulation

基　　金：国家重点研发计划(2018YFB1004005)

摘　　要：针对多品种、小批量制造模式下计划管理系统无法根据不确定因素及时自动调整,提出一种基于数字孪生的智能制造计划管理系统框架。建立了计划管理PDCA业务过程模型。提出了静态排程的周期滚动模型和动态应急排程的优化模型的处理逻辑和约束条件。以航天复杂产品两类零部件混线装配场景下的计划管理为背景,验证了本文提出的管理模式能够支持不同订单与资源状态的智能计划动态调整,提升车间应对不确定因素的处理效率。For the multi-variety and small-batch manufacturing mode, the planning management system cannot be timely automatically adjusted according to uncertain factors. This paper proposes an intelligent manufacturing plan management system based on factory digital twins. The plan management PDCA business process model is established. In addition, the processing logic model and constraints of the periodic static scheduling model and the dynamic emergency scheduling model are proposed. Based on the planning management case of hybrid assembly of two types of aerospace complex products, it is verified that the management model proposed in this paper can support the intelligent dynamic adjustment of plans for different orders and resource states, and improve the processing efficiency of the workshop to cope with uncertain factors.

关 键 词：计划管理 智能制造 数字孪生 动态排程 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]