A gamma process based model for systems subject to multiple dependent competing failure processes under Markovian environments. (January 2022)

• Record Type: Journal Article
• Authors: Wu, Bei; Ding, Dong
• Is Part Of: Reliability engineering & system safety. Volume 217(2022)
• Publication Date: 2022-01
• Subjects: Gamma process -- Random shock -- Degradation -- Multiple dependent competing failure processes -- Markov process -- Reliability function -- System availability; 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.2021.108112
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: The performance rules of many products that suffer from both natural degradation and random shocks may have discrepancies in different environments during their service life. This article proposes a reliability model for systems subject to multiple dependent competing failure processes affected by Markovian environments. The effect of dynamic environment is embodied in that the natural wear behavior of the system in different environments is controlled by distinct gamma processes. A maintenance model is developed in the case where switches of environment states take place only when systems are operating. Explicit formulas for system reliability indexes including the reliability function, first failure time distribution, mean time to first failure, and system availability are analytically derived in the form of Laplace transforms. In order to verify the correctness of the analytical formula, a simulation algorithm for evaluating the reliability function is proposed. Finally, they are applied to a study case of the micro-engine system, which illustrates the applicability of proposed models and the validity of obtained results. Highlights: A system subject to dependent soft and hard failure processes is investigated. Degradation and maintenance actions related to environments are considered. Analytical formulas for system reliability indexes are derived. A simulation algorithm for computing the reliability function is provided. A detailed case study is conducted to demonstrate derived formulas.