Reliability evaluation of non-repairable phased-mission common bus systems with common cause failures

• Published in: Computers & industrial engineering Vol. 111; pp. 445 - 457
• Main Authors: Yu, Huan, Yang, Jun, Lin, Jing, Zhao, Yu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2017
• Subjects: Common bus performance sharing; Drift och underhållsteknik; Genetic algorithm; Operation and Maintenance Engineering; Phased-mission systems; Recursive algorithm; Reliability evaluation; PM-LCCS; Phased-mission systems; LCCS; CDF; Common bus performance sharing; CCF; Recursive algorithm; SE; Genetic algorithm; UGF; PMS; PMCB; GA; Reliability evaluation; r.v
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2017.08.002

•A new model of phased-mission systems with common bus is proposed.•Common bus performance sharing and common cause failures are considered in the model.•A recursive algorithm is provided for the system reliability evaluation.•Optimal element allocation problem is formulated and solved by genetic algorithm. Phased-mission common bus (PMCB) systems are systems with a common bus structure, performing missions with consecutive and non-overlapping phases of operations. PMCB systems are found throughout industry, e.g., power generating systems, parallel computing systems, transportation systems, and are sometimes characterized by their common cause failures. Reliability evaluation of PMCB systems plays an important role in system design, operation, and maintenance. However, current studies have focused on either phased-mission systems or common bus systems because of their complexity. The challenge in practice is to consider phased-mission systems together with common bus structures and common cause failures. To solve this problem, we propose an evaluation algorithm for PMCB systems with common cause failures by coupling the structure function of a common bus performance sharing system and an existing recursive algorithm. To weigh the efficiency of the proposed algorithm, its complexity is discussed. To improve the reliability of PMCB systems, we adopt the genetic algorithm method to search for the optimal allocation strategies of the service elements. We use both analytical and numerical examples to illustrate the application of the proposed algorithm.