基于数字孪生仿真的柔性作业车间调度优化研究  

Optimization study of flexible job-shop scheduling based on digital twin simulation

作　　者：刘亮 贺禹铭 祁思远 LIU Liang;HE Yuming;QI Siyuan(School of Economics and Management,Tiangong University,Tianjin 300387,China)

机构地区：[1]天津工业大学经济与管理学院,天津300387

出　　处：《现代制造工程》2025年第3期41-51,共11页Modern Manufacturing Engineering

基　　金：国家科技部创新方法工作专项课题项目(2020IM030300)。

摘　　要：智能制造是世界制造业发展的共同趋势,数字孪生作为推进实施智能制造的重要使能技术,是迈向智能制造的关键环节。为应对车间作业过程中的不确定事件以及生产信息透明度低的问题,提出了一种基于数字孪生仿真的柔性作业车间调度优化方法。首先,设计了数字孪生车间调度框架,构建了基于AnyLogic软件的柔性作业车间数字孪生仿真模型。其次,综合考虑最大完工时间、设备能耗及设备总负荷建立柔性作业车间调度模型,提出了一种改进NSGA-Ⅱ进行求解,采用多策略混合种群初始化方法,并对工序、设备编码采用不同的交叉变异策略。最后,基于标准算例与发动机缸盖制造实例,验证了所提方法的有效性。Intelligent manufacturing is a common trend in the development of the world′s manufacturing industry,and the digital twin,as an important enabling technology to promote the implementation of intelligent manufacturing,is a key link to intelligent manufacturing.To deal with the problems of uncertain events and low transparency of production information,a flexible job-shop scheduling optimization method based on digital twin simulation was proposed.Firstly,the digital twin shop scheduling framework was designed,and the AnyLogic software flexible job-shop digital twin simulation model was constructed.Secondly,considering the maximum completion time,energy consumption and total load of equipment,a flexible job-shop scheduling model was established,and an improved NSGA-Ⅱalgorithm was proposed to solve the problem.Multi-strategy mixed population initialization method was adopted,and different cross-mutation strategies were adopted for process and machine coding.Finally,the effectiveness of the proposed method was verified based on the standard calculation examples and a manufacturing example of engine cylinder head.

关 键 词：柔性作业车间调度 多目标优化 数字孪生仿真 AnyLogic软件 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TH16[自动化与计算机技术—计算机科学与技术]