计算机集成制造系统 ›› 2021, Vol. 27 ›› Issue (2): 642-653.DOI: 10.13196/j.cims.2021.02.028

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基于数字孪生的复杂产品装配过程管控方法与应用

胡兴1,刘检华1,庄存波1+,武颖1,张雷1,2,熊辉1   

  1. 1.北京理工大学机械与车辆学院数字化制造研究所
    2.天津商业大学机械工程学院
  • 出版日期:2021-02-28 发布日期:2021-02-28
  • 基金资助:
    国家重点研发计划资助项目(2020YFB1710300);国家自然科学基金资助项目(51935003);国防基础科研资助项目(JCKY2016204A502,JCKY2018210C005,JCKY2018206B003)。

Digital twin-based management method and application for the complex products assembly process

  • Online:2021-02-28 Published:2021-02-28
  • Supported by:
    Project supported by the National Key Research and Development Program,China(No.2020YFB1710300),the National Natural Science Foundation,China(No.51935003),and the National Defense Fundamental Research Foundation,China(No.JCKY2016204A502,JCKY2018210C005,JCKY2018206B003).

摘要: 针对航天复杂产品装配过程的实时可视化监控、运行状态在线分析与预测难题,提出了一种基于数字孪生的复杂产品装配过程管控方法。首先构建了面向复杂产品装配过程管控的数字孪生模型;在此基础上,引入工作流技术实现了装配过程数据的实时采集与管理,提出实时数据驱动的数字孪生车间同步运行方法;随后通过灰色马尔可夫预测模型、T-K统计控制图以及关联规则算法的集成应用,实现了对复杂产品装配过程中的小样本量质量数据的实时预测与分析。最后,自主设计并开发了基于数字孪生的复杂产品装配过程管控系统,并在某卫星装配车间进行了应用验证。

关键词: 数字孪生, 数字孪生车间, 复杂产品, 装配过程管控, 质量预测

Abstract: Aiming at the issues including the real-time and comprehensive visual monitoring,the analysis and prediction of the operating status,an assembly process management and control method for complex products based on digital twin was proposed.A digital twin model for the assembly process management of the complex product was constructed.On this basis,the real-time collection and management of assembly process data was achieved based on workflow technology.Then,the real-time data-driven synchronized operation of the shop-floor digital twin was proposed.Afterwards,through combining application of grey Markov predictive model,T-K statistical control chart and association rule algorithm,the real-time prediction and analysis of small sample quality data in the assembly process of the complex product were realized.A digital twin-based assembly process management and control system for complex products was developed and verified in a satellite assembly shop-floor.

Key words: digital twin, digital twin shop-floor, complex product, assembly process management and control, quality prediction

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