Competing Failure Modeling for Performance Analysis of Automated Manufacturing Systems With Serial Structures and Imperfect Quality Inspection

• Published in: IEEE transactions on industrial informatics Vol. 16; no. 10; pp. 6476 - 6486
• Main Authors: Ye, Zhenggeng, Cai, Zhiqiang, Si, Shubin, Zhang, Shuai, Yang, Hui
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accumulated degradation; Algorithms; Analytical models; automated manufacturing system (AMS); Automation; competing failure; decision diagram; Decision making; Degradation; Failure; Failure analysis; Failure modes; failure propagation; Heuristic algorithms; Impact analysis; Inspection; Manufacturing; Manufacturing systems; Modelling; Performance analysis; Product quality; Production controls; Propagation; Reliability; system dynamics
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2020.2967030

Fierce global competition drives automated manufacturing systems (AMSs) to be increasingly complex, which poses significant challenges on performance analysis and production control. The multistage production via serial stations will lead to the propagation of failures in AMSs, which will affect system performance by triggering complex competitions among multiple failure modes. Although machine performance and product quality have been considered, very little has been done to investigate the effect of imperfect quality inspection on competing failures. Focusing on a time balance serial AMS, this article presents a new competing failure model to investigate the complex interactions among machine failures, product quality, and inspection process, which enables the characterizations of time-delayed propagation of failure, accumulation of degradation, and dynamics of states in serial AMSs. In order to further analyze the impact of competing behaviors on system performance, we have also developed decision diagram models and algorithms, which are evaluated and validated on serial AMSs with imperfect inspection, revealing the characteristic of multistate interactions. Experimental results show that the proposed methods have strong potentials for performance modeling and analysis of serial AMSs and also demonstrate general applicability for manufacturing decision making.