Optimal preventive maintenance and repair policies for multi-state systems

Sheu, Shey‐Huei; Chang, Chin-Chih; Chen, Yen-Luan; Zhang, Zhe George

doi:10.1016/j.ress.2015.03.029

Cited by 67 publications

(22 citation statements)

References 26 publications

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“…One may notice that, in recent years, many authors have devoted considerable effort on developing novel methods to model repair processes, (see, e.g. Jain & Gupta, 2013;Liang & Parlikad, 2015;Sheu et al, 2015;Vu et al, 2015;Wu & Scarf, 2015, 2017Zhao et al, 2015;Wu, 2017). We consider the current paper and the process we describe as a further important contribution to the literature on the modelling the failure process of a repairable system.…”

Section: Contribution and Importance Of This Workmentioning

confidence: 99%

The semi-geometric process and some properties

Wang

2017

IMA Journal of Management Mathematics

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The geometric process has been widely applied in reliability engineering and other areas since its introduction. One of its assumptions is that the times between occurrences of events are independent. This assumption is rather restrictive and can limit its application in the real world. This paper extends the geometric process to a new process, which we call the semi-geometric process, by relaxing this assumption. Some probabilistic properties of the process are derived and parameter estimation is described. A numerical example, based on a real-world data set, is used to illustrate the model and validate the estimation methodology.

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Section: Contribution and Importance Of This Workmentioning

confidence: 99%

The semi-geometric process and some properties

Wang

2017

IMA Journal of Management Mathematics

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“…Considering multi‐state degraded systems subjected to minimal repairs and imperfect preventive maintenance, Soro et al developed a continuous‐time Markov process‐based model for evaluating the performance indices of the MSS, including the availability, the production rate, and the reliability function. Sheu et al considered 3 types of major, minimal, and imperfect repair actions for multi‐state deterioration systems. They used a recursive approach to compute the time‐dependent distribution of the MSS and find the optimal preventive maintenance for each repair type.…”

Section: Introductionmentioning

confidence: 99%

Reliability modeling of multi‐state degraded repairable systems and its applications to automotive systems

Zheng

Pham

et al. 2018

Quality & Reliability Eng

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In this paper, we presented a continuous‐time Markov process‐based model for evaluating time‐dependent reliability indices of multi‐state degraded systems, particularly for some automotive subsystems and components subject to minimal repairs and negative repair effects. The minimal repair policy, which restores the system back to an “as bad as old” functioning state just before failure, is widely used for automotive systems repair because of its low cost of maintenance. The current study distinguishes with others that the negative repair effects, such as unpredictable human error during repair work and negative effects caused by propagated failures, are considered in the model. The negative repair effects may transfer the system to a degraded operational state that is worse than before due to an imperfect repair. Additionally, a special condition that a system under repair may be directly transferred to a complete failure state is also considered. Using the continuous‐time Markov process approach, we obtained the general solutions to the time‐dependent probabilities of each system state. Moreover, we also provided the expressions for several reliability measures include availability, unavailability, reliability, mean life time, and mean time to first failure. An illustrative numerical example of reliability assessment of an electric car battery system is provided. Finally, we use the proposed multi‐state system model to model a vehicle sub‐frame fatigue degradation process. The proposed model can be applied for many practical systems, especially for the systems that are designed with finite service life.

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“…A maintenance program analyzes, predicts, and evaluates the quality of the product and establishes a variety of physical and mathematical models. The program is essential and strongly influences the product maintenance level [1,14,17].…”

Section: Introductionmentioning

confidence: 99%