An Edge-Fog-Cloud Computing-Based Digital Twin Model for Prognostics Health Management of Process Manufacturing Systems  

作　　者：Jie Ren Chuqiao Xu Junliang Wang Jie Zhang Xinhua Mao Wei Shen 

机构地区：[1]College of Mechanical Engineering,Donghua University,Shanghai,201620,China [2]Institute of Artificial Intelligence,Donghua University,Shanghai,201620,China [3]School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,200240,China [4]Beijing Chonglee Machinery Engineering Co.,Ltd.,Beijing,101111,China

出　　处：《Computer Modeling in Engineering & Sciences》2023年第4期599-618,共20页工程与科学中的计算机建模（英文）

基　　金：supported by the Fundamental Research Funds for The Central Universities(Grant No.2232021A-08);National Natural Science Foundation of China(GrantNo.51905091);Shanghai Sailing Program(Grand No.19YF1401500).

摘　　要：The prognostics health management(PHM)fromthe systematic viewis critical to the healthy continuous operation of processmanufacturing systems(PMS),with different kinds of dynamic interference events.This paper proposes a three leveled digital twinmodel for the systematic PHMof PMSs.The unit-leveled digital twinmodel of each basic device unit of PMSs is constructed based on edge computing,which can provide real-time monitoring and analysis of the device status.The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters,which are deployed for the manufacturing execution on the fog server.The shop-leveled digital twin maintenancemodel is designed for production planning,which gives production instructions fromthe private industrial cloud server.To cope with the dynamic disturbances of a PMS,a big data-driven framework is proposed to control the three-level digital twin models,which contains indicator prediction,influence evaluation,and decisionmaking.Finally,a case study with a real chemical fiber system is introduced to illustrate the effectiveness of the digital twin model with edge-fog-cloud computing for the systematic PHM of PMSs.The result demonstrates that the three-leveled digital twin model for the systematic PHM in PMSs works well in the system’s respects.

关 键 词：Process manufacturing system prognostics health management digital twin chemical fiber big data-driven 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]