Design and implementation of a CPS-based predictive maintenance and automated management platform

IET Cyber-Physical Systems

Huei-Yung Lin¹  Fang-Ning Yang² 

[1] Advanced Institute of Manufacturing with High-Tech Innovation, National Chung Cheng University;National Chung Cheng University;

关键词: production engineering computing;    big data;    mobile robots;    manufacturing data processing;    service-oriented architecture;    intelligent control;    cloud computing;    maintenance engineering;    cps-based predictive maintenance;    automated management platform;    cyber-physical systems;    intelligent automatic operational management platform;    on-site data;    big data;    management system;    predictive maintenance platform;    generated synthetic data;    real-world data;    system design;   

DOI  :  10.1049/iet-cps.2019.0019

来源: DOAJ

【 摘 要 】

The concept of cyber-physical systems (CPSs) is a core technology indispensable to Industry 4.0. The development of an intelligent automatic operational management platform is presented in this study. The platform is used to collect on-site data, provide predictive maintenance, and monitor and control the mobile robots. For predictive maintenance, it is targeted at products from manufacturing big data to cloud computing, and predictive maintenance for all factories around the world. The efficiency of the management system is improved by the performance evaluation strategy. In the experiments, the authors implement and discuss the predictive maintenance platform with generated synthetic data and real-world data collected from a gearbox plant. The results show that the important variables possess large drops according to mean decrease Gini. A warning generation for battery simulation and manufacturing execution is also presented to demonstrate the proposed system design. The results show that the discharge curve drops sharply at the last stage, and the warning value can be set accordingly.

【 授权许可】

Unknown