计算机集成制造系统 ›› 2019, Vol. 25 ›› Issue (第6): 1444-1453.DOI: 10.13196/j.cims.2019.06.012

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基于数字孪生的零件智能制造车间调度云平台

刘志峰,陈伟,杨聪彬,程强,赵永胜   

  1. 北京工业大学先进制造与智能技术研究所
  • 出版日期:2019-06-30 发布日期:2019-06-30
  • 基金资助:
    国家科技重大专项资助项目(2018ZX04032002);北京市科技计划资助项目(Z181100003118001)。

Intelligent manufacturing workshop dispatching cloud platform based on digital twins

  • Online:2019-06-30 Published:2019-06-30
  • Supported by:
    Project supported  by the National Science and Technology Major Project,China(No.2018ZX04032002),and the Beijing Municipal Science and Technology Program,China(No.Z181100003118001).

摘要: 零件制造车间中工作要素路径的未知性、时间的不确定性,以及生产要素信息的孤立性,严重影响了车间调度的有效运行。基于数字孪生技术提出一种解决零件智能制造车间调度问题的新方法——调度云平台,构建了调度云平台的框架模型以及调度工作流程;搭建了调度云平台的全生命周期监控系统,监控产品的实时运行状态;基于全生命周期监控系统实时监控的数据,利用大数据分析技术对车间生产过程中多源动态扰动进行预测和诊断,在此基础上提前由调度云平台对动态扰动制定相应扰动策略;为阐述如何将所提模型落地,以某企业零件智能制造车间为例,对调度云平台模型进行应用验证,同时指出了基于数字孪生的零件智能制造车间未来的工作方向。

关键词: 数字孪生, 智能制造车间, 调度云平台, 动态扰动预测, 全生命周期监控系统

Abstract: The unknownness of the working factor path,the uncertainty of time and the isolation of production factor information in the parts manufacturing workshop seriously affect the effective operation of the shop scheduling.Based on the digital twinning technology,a new method to solve the problem of intelligent manufacturing workshop scheduling was proposed.The framework model and scheduling workflow of the scheduling cloud platform was constructed.Then the whole lifecycle monitoring system of the scheduling cloud platform was built for monitoring the real-time running status of the product.Based on the real-time monitoring data of the whole life cycle monitoring system,the big data analysis technology was used to predict and diagnose the multi-source dynamic disturbance in the workshop production process,on the basis of which the scheduling cloud platform dynamically determined the dynamic disturbance Perturbation strategy.The intelligent manufacturing workshop of an enterprise was taken as an example to verify the application of the dispatching cloud platform model,and the future working direction of the intelligent manufacturing workshop based on digital twins was also pointed out at the same time.

Key words: digital twin, intelligent manufacturing workshop, dynamic disturbance prediction, scheduling cloud platform, full life cycle monitoring system

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