Reliability modeling of multi-state phased mission systems with random phase durations and dynamic combined phases

Li, XY, Li, H, Xiong, X, Li, M, Yazdi, M and Zarei, E (2024) Reliability modeling of multi-state phased mission systems with random phase durations and dynamic combined phases. Reliability Engineering & System Safety, 253. ISSN 0951-8320

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Abstract

Random phase durations and dynamic combined phases challenge the application of existing reliability models in the reliability analysis of multistate-phased mission systems (MS-PMSs). To this end, this paper presents a new reliability modeling method for multi-state phased mission systems with random phase durations and dynamic combined phases. Initially, a multi-state multi-valued decision diagram-based (MMDD-based) reliability modeling method is created to efficiently map random phase durations and the dynamic combined phase nature of MS-PMSs into the reliability model. To solve the MMDD-based reliability model, a path probability evaluation method is subsequently constructed with the assistance of the Markov regenerative function. The effectiveness and the superior performance of the proposed MMDD-based reliability model and its solving algorithm are validated by the application to the reliability modeling and analysis of an attitude and orbit control system with multiple modes. Overall, this paper provides the reliability sector with a new reliability model and its solving algorithm to enhance the reliability and safety of multi-state phased mission systems.

Item Type:	Article
Uncontrolled Keywords:	4005 Civil Engineering; 40 Engineering; 01 Mathematical Sciences; 09 Engineering; 15 Commerce, Management, Tourism and Services; Strategic, Defence & Security Studies; 35 Commerce, management, tourism and services; 40 Engineering; 49 Mathematical sciences
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering
Publisher:	Elsevier
Date of acceptance:	30 September 2024
Date of first compliant Open Access:	6 June 2025
Date Deposited:	06 Jun 2025 12:27
Last Modified:	06 Jun 2025 12:30
DOI or ID number:	10.1016/j.ress.2024.110524
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26541

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