Functional health prognosis approach of multi-station manufacturing system considering coupling operational factors. (March 2022)

• Record Type: Journal Article
• Authors: Li, Yao; He, Yihai; Ai, Jun; Wang, Chengcheng; Han, Xiao; Liao, Ruoyu; Yang, Xiuzhen
• Is Part Of: Reliability engineering & system safety. Volume 219(2022)
• Publication Date: 2022-03
• Subjects: Manufacturing system -- Functional health prognosis -- Operational factors -- Coupling effect -- Integrated modeling; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2021.108211
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: l The coupling operation mechanism of multi-station manufacturing system is fully discussed. l Quantitative models are established to quantify the coupling effect between operational factors. l An integrated functional health prognosis model based on coupling operational factors is presented. l An industrial example of a multi-station manufacturing system is implemented. Abstract: The core function of the manufacturing system is to ensure the quality and quantity of output products. Therefore, the performance of the manufacturing function can effectively evaluate the health state of the manufacturing system. However, the complex coupling effects caused by the correlation and interaction between multiple operational factors in the running manufacturing system will significantly affect the performance of manufacturing function, which has not been paid due attention. Therefore, a systematic functional health state prognosis approach for the manufacturing system considering coupling operational factors is given in this paper. First, based on functional performance analysis, the relationship among main coupling operational factors including manufacturing machine, production task, and produced workpiece is expounded, and the connotation of the functional health state is defined. Second, three quantitative models of the coupling effect between operational factors are constructed. Third, an integrated functional health prognosis model for the manufacturing system is established. Finally, a prognosis example of a ferrite phase shifting unit manufacturing system is provided to illustrate the effectiveness of the proposed method.