A computational method for finding the availability of opportunistically maintained multi-state systems with non-exponential distributions. (1st September 2020)

• Record Type: Journal Article
• Authors: Wang, Naichao; Jin, Yu (Chelsea); Ma, Lin; Liao, Haitao
• Is Part Of: IISE transactions. Volume 52:Number 9(2020)
• Page Start: 1047
• Page End: 1061
• Publication Date: 2020-09-01
• Subjects: Availability -- multi-state system -- non-exponential distributions -- corrective maintenance -- preventive maintenance; Industrial engineering -- Periodicals; Systems engineering -- Periodicals; Industrial engineering; Systems engineering; Electronic journals; Periodicals; 670.285
• DOI: 10.1080/24725854.2019.1688897
• Languages: English
• ISSNs: 2472-5854

Abstract

Abstract: Availability is one of the most important performance measures of a repairable system. Among various mathematical methods, the method of supplementary variables is an effective way of modeling the steady-state availability of systems governed by non-exponential distributions. However, when all the underlying probability distributions are non-exponential (e.g., Weibull), the corresponding state equations are difficult to solve. To overcome this challenge, a new method is proposed in this article to determine the steady-state availability of a multi-state repairable system, where all the state sojourn times, as well as the maintenance times, are generally distributed. As an indispensable step, the well-posedness and stability of the system's state equations are illustrated and proved using C0 operator semigroup theory. Afterwards, based on the generalized Integral Mean Value Theorem, the expression for system steady-state availability is derived as a function of state probabilities. Then, the original problem is transformed into a system of linear equations that can be easily solved. A simulation study and an instance studied in the literature are used to demonstrate the applications of the proposed method in practice. These numerical examples illustrate that the proposed method provides a new computational tool for effectively evaluating the availability of a repairable system without relying on simulation.