数据驱动的复杂产品智能服务技术与应用

Hao Li, Haoqi Wang, Ying Cheng, Fei Tao, Bing Hao, Xinchang Wang, Yangjian Ji, Wenyan Song, Wenliao Du, Xiaoyu Wen, Xiaoyun Gong, Ke Li, Yingfeng Zhang, Guofu Luo, Qifeng Li

科研成果: 期刊稿件文章同行评审

26 引用 (Scopus)

摘要

With the applications of sensors, data acquisition devices and other modules with sensing ability in the service operation stages of complex products, the operation and maintenance system of complex products was becoming more and more digital and intelligent. Data with real-time, multi-source, heterogeneous, and massive characteristics were become the basis of decision making to improve the reliability and low cost operation for complex product systems, especially the DT technology provided an effective way. Thus, the research progress of data-driven intelligent service for complex products was introduced. The characteristics and framework mode of data-driven intelligent services were analyzed herein, and data-driven intelligent service approaches for complex products were proposed, which included service-oriented complex product modeling and simulation methods, accurate analysis and prediction method for data-driven service demand acquisition, equipment fault identification and dynamic performance prediction based on DT, data-driven multi-objective decision-making optimization method for equipment condition-based maintenance and spare parts inventory, assisted maintenance technology for complex products based on DT, precise analysis and prediction method for energy efficiency of complex equipment based on multi-element cooperation, and optimal control method for complex product operation based on data mining. The application case of intelligent service system was given. The proposed framework and approach may provide reference for the intelligent transformation and upgrading of modern manufacturing services.

投稿的翻译标题Technology and Application of Data-driven Intelligent Services for Complex Products
源语言繁体中文
页(从-至)757-772
页数16
期刊Zhongguo Jixie Gongcheng/China Mechanical Engineering
31
7
DOI
出版状态已出版 - 10 4月 2020

关键词

  • Data-driven
  • Digital twin(DT)
  • Intelligent manufacturing
  • Intelligent service

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