Degradation-based maintenance decision using stochastic filtering for systems under imperfect maintenance

Zhang, Mimi; Gaudoin, Olivier; Xie, Min

doi:10.1016/j.ejor.2015.02.050

Cited by 128 publications

(58 citation statements)

References 45 publications

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“…Pandey et al [21] addressed the optimal maintenance decision for binary systems to maximize the next mission reliability under 3 imperfect maintenance. For extensive discussions regarding imperfect maintenance models readers may refer to, Shafiee and Chukova [22], and Zhang et al [7].…”

Section: Introductionmentioning

confidence: 99%

“…Under the CBM philosophy, a system is maintained only when there is an objective evidence of impending failures. Degradation-based maintenance (DBM) is a form of CBM which relies on monitoring and analysis of degradation data [5][6][7]. Variables such as fatigue cracks, vibration features, temperature, and oil concentration are used as degradation indicators and reflect the actual deterioration status in real-time [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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A cost effective degradation-based maintenance strategy under imperfect repair

Wang

Niknam

Kobza

2015

Reliability Engineering & System Safety

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A cost effective degradation-based maintenance strategy under imperfect repair

Wang

Niknam

Kobza

2015

Reliability Engineering & System Safety

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“…, where a is a positive constant, then {X k , k = 1, 2, · · · } is called a geometric process (GP). The GP has attracted a lot of attention in the literature (see, Zhang, Gaudoin, & Xie, 2015;Wu & Scarf, 2015, for example).…”

Section: Definitionsmentioning

confidence: 99%

Two new stochastic models of the failure process of a series system

Scarf

2017

European Journal of Operational Research

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Consider a series system consisting of sockets into each of which a component is inserted: if a component fails, it is replaced with a new identical one immediately and system operation resumes. An interesting question is: how to model the failure process of the system as a whole when the lifetime distribution of each component is unknown? This paper attempts to answer this question by developing two new models, for the cases of a specified and an unspecified number of sockets, respectively. It introduces the concept of a virtual component, and in this sense, we suppose that the effect of repair corresponds to replacement of the most reliable component in the system. It then discusses the probabilistic properties of the models and methods for parameter estimation. Based on six datasets of artificially generated system failures and a real-world dataset, the paper compares the performance of the proposed models with four other commonly used models: the renewal process, the geometric process, Kijima's generalised renewal process, and the power law process. The results show that the proposed models outperform these comparators on the datasets, based on the Akaike information criterion.Our responses are shown below, taking the reviewer comments one by one.In the revised paper, new text is coloured blue, deletions are indicated, and text we wish to emphasise to address a review comment is coloured red.Reviewer #1: This revised version significantly improves the first paper. I have still some comments that should be taken into account before acceptation.1. Throughout the paper, the components of the series systems are supposed to be independent. This assumption should be stated clearly. Response: We now state this clearly at the beginning of Proposition 1. Also, please note that the first sentence immediately under the heading of Section 2 says: "Consider a series system with a number of statistically independent components." (See the sentence in red on page 6).2. Answer to my comment 9. The proof (d) of the additivity of the CRIF is not really a proof. The additivity comes from the facts that the counting process of system failures is the sum of the counting processes of components failures, and that the probability of having more than one failure in an infinitesimal interval is zero because of the independence of the components. See considerations of that kind in reference 1. Response: Yes, we agree, and we have rewritten the text in part (d) there on page 8. In addition, the sentence starting with "Alternatively, …" shortly after is introduced to outline the idea of the proof and is in response to comment 1 of reviewer 3.3. Answer to my comment 15. You say that the sentence "and the oldest VC in the VSS will be renewed" has been removed. But in fact, it is still in the paper. You should explain this part more clearly. The fact that one component in the VSS is renewed seems contradictory with the initial assumption that the VSS is not maintained or minimally repaired. Response: We agree the explanation was ...

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“…Some advances have been made to include imperfect repairs in a degrading system (Alaswad and Xiang (2017); Giorgio and Pulcini (2018)). However, as Zhang et al (2015) claimed, the issue of treating imperfect maintenance in the context of degrading systems remains widely open nowadays.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the development of on-line monitoring which allows the effective measurement of a system deterioration (length of a crack, thickness of a cable, intensity of vibrations, temperature, ...), numerous papers nowadays model the degradation in itself, which is often considered to be (mostly) monotonous with respect to the time. This is done through the use of stochastic processes such as Wiener processes with trend (Liu et al (2017); Zhang et al (2015); Hu et al (2015)), inverse gaussian models (Chen et al (2015)), transformed Beta degradation processes (Giorgio and Pulcini (2018)) or gamma processes (Huynh et al (2014)), among others (see also Mercier and Pham (2012) in case of a bivariate deterioration indicator). This paper focuses on gamma processes, which seem the most popular, see Van Noortwijk (2009) with a large number of references therein.…”

Section: Introductionmentioning

confidence: 99%

Stochastic comparisons of imperfect maintenance models for a gamma deteriorating system

Mercier

Castro

2019

European Journal of Operational Research

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This paper compares two imperfect repair models for a degrading system, with deterioration level modeled by a non homogeneous gamma process. Both models consider instantaneous and periodic repairs. The first model assumes that a repair reduces the degradation of the system accumulated from the last maintenance action. The second model considers a virtual age model and assumes that a repair reduces the age accumulated by the system since the last maintenance action. Stochastic comparison results between the two resulting processes are obtained. Furthermore, a specific case is analyzed, where the two repair models provide identical expected deterioration levels at maintenance times. Finally, two optimal maintenance strategies are explored, considering the two models of repair.

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Degradation-based maintenance decision using stochastic filtering for systems under imperfect maintenance

Cited by 128 publications

References 45 publications

A cost effective degradation-based maintenance strategy under imperfect repair

A cost effective degradation-based maintenance strategy under imperfect repair

Two new stochastic models of the failure process of a series system

Stochastic comparisons of imperfect maintenance models for a gamma deteriorating system

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