Reliability optimization of flexible test system based on pyro-mechanical device products production driven. (February 2023)

• Record Type: Journal Article
• Authors: Xiao, Yong; Wei, Shanbi; Chai, Yi; Pan, Tianle; Hou, Yang
• Is Part Of: Reliability engineering & system safety. Volume 230(2023)
• Publication Date: 2023-02
• Subjects: Flexible test system -- Bayesian network -- Phased mission system -- Reliability evaluation; 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.2022.108880
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: The quality evaluation of aerospace pyro-mechanical device products(PDPs) is very important to the safety of aerospace engineering. Aerospace PDPs are small-lot batch, multiple batches and one-off products which rely on the analysis of ignition test with limited samples. To accommodate multiple batches and small-lot batch of aerospace PDPs, the flexible test system(FTS) switches between different batches of products by the selection of instruments and channels. The conventional test mode is driven by the completion time of batch products, which usually leads to frequent switching of instruments and channels and affects the reliability of test system. Therefore, the FTS is configured according to the completion of production missions within a certain time period in the future. This paper considers the FTS of aerospace PDPs as a phased mission system, and designs the corresponding dynamic Bayesian network(DBN) model. A test of one batch is taken as a phase of phased mission system. In order to improve efficiency and optimize reliability of the aerospace PDPs FTS, the receding horizon optimization problem is constructed. Numerical experiments show that the FTS with phased mission model can optimize the test sequence during the test process, which improves efficiency and reliability of test system. Highlights: A novel receding horizon optimization algorithm is proposed. The algorithm considering phase wait time and emergency mission insertion. Considering the completion of production missions in a certain period. Numerical experiments proved the effectiveness of the optimization method.