计算机集成制造系统 ›› 2016, Vol. 22 ›› Issue (第5期): 1221-1229.DOI: 10.13196/j.cims.2016.05.007

• 产品创新开发技术 • 上一篇    下一篇

大数据驱动的智能车间运行分析与决策方法体系

张洁1,高亮2,秦威1,吕佑龙1,李新宇2   

  1. 1.上海交通大学机械与动力工程学院
    2.华中科技大学机械科学与工程学院
  • 出版日期:2016-05-31 发布日期:2016-05-31
  • 基金资助:
    国家自然科学基金资助项目(51435009)。

Big-data-driven operational analysis and decision-making methodology in intelligent workshop

  • Online:2016-05-31 Published:2016-05-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51435009).

摘要: 针对智能车间制造数据呈现的大数据特性,研究大数据驱动的车间运行分析与决策方法体系。在分析传统方法局限性的基础上,提出“关联+预测+调控”的车间运行分析与决策新模式,进而提出该模式下的方法论体系,包括车间大数据预处理与分析方法、车间运行状态预测方法及车间运行状态决策方法等。提出车间运行分析与决策技术体系,深入讨论了海量高维多源异构制造数据预处理、动态制造数据多尺度时序分析、制造数据关系网络建模与关联分析、车间运行状态演化规律与预测和基于定量调控机制的车间运行决策等关键技术。所提体系将对实现大数据驱动的智能工厂有重要借鉴价值。

关键词: 大数据, 智能制造, 运行分析与决策

Abstract: Aiming at the big-data characteristics of intelligent workshop data,operational analysis and decision-making method driven by big-data were investigated.Based on the shortage of traditional methods,a new “correlation,forecast and regulation” decision-making pattern was proposed.The related methodology driven by big data was put forward,which included big data processing and analysis method,the workshop operation prediction method and the workshop operation decision method.The technical system to realize the methodology was designed.The key technologies used in big data processing method,big data temporal analysis method,data network modelling and analysis method,workshop operational analysis and forecast method and quantitative-control-based workshop operation decision method were discussed.The proposed methodology and technical system could provide important referential value to realize big data driven intelligent plants.

Key words: big data, intelligent manufacturing, operational analysis and decision-making

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