Maintenance Policy for a Continuously Monitored Deteriorating 
System

Bérenguer, Christophe; Grall, Antoine; Dieulle, Laurence; Roussignol, Michel

doi:10.1017/s0269964803172063

Cited by 77 publications

(43 citation statements)

References 10 publications

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“…Without loss of generality, the actuator wear is seen as the accumulation of positive and independent deterioration increments which are homogeneous in time Acc Θ 1 . The corresponding stochastic process is the homogeneous Gamma process [35,30]. It is characterized by its shape parameter α and by its scale parameter β.…”

Section: Wear Process Z(t)mentioning

confidence: 99%

“…E 1 , E 2 and E 3 respectively denote the events "Dðt i Þ ¼ d i rL 1 ", "L 1 o Dðt i Þ ¼ d i r L 2 " and "Dðt i Þ ¼ d i 4L 2 ". According to [35] and to derive tractable approximations of the quantities R #k i ðtÞ, the difference T 2 À T 1 between the passage times of levels L 2 and L 1 is approximated by the passage time of the level L 2 ÀL 1 . The equality stands only for the continuous trajectories of the process D(t), which is not the case here.…”

Section: Appendix Amentioning

confidence: 99%

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A modeling framework for deteriorating control system and predictive maintenance of actuators

Langeron

Grall

Barros

2015

Reliability Engineering & System Safety

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Section: Wear Process Z(t)mentioning

confidence: 99%

Section: Appendix Amentioning

confidence: 99%

A modeling framework for deteriorating control system and predictive maintenance of actuators

Langeron

Grall

Barros

2015

Reliability Engineering & System Safety

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“…While in operation, the equipment in question may take one of several states, with the two extreme states being as good as new and the faulty state. Between these two state-limits there is a set of intermediate states, which denote different degrees of deterioration (Grall et al 2002;Bérenguer et al 2003;Fouladirad and Grall 2014). The move from state to state is governed by a stochastic mechanism the behavior of which could be unknown, partially known or completely known by the DM.…”

Section: Structure Of a Decision Problem In Maintenancementioning

confidence: 99%

Basic Concepts on Risk Analysis, Reliability and Maintenance

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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Abstract:Man's level of dependence on equipment is increasing. This degree of dependence requires high levels of availability, which has been changing the impact that disruption of these systems causes. For many systems, an interruption has consequences that go beyond the dimension of financial loss, thus justifying a multidimensional consequence approach by using multicriteria (MCDM/A) models. Thus, understanding the relationships between and among risk, reliability and maintenance (RRM) is essential in order to offer more comprehensive solutions to the various problems often treated in isolation from each other, and which are the most important problems of the competitive market. This chapter discusses fundamental topics about RRM, including tools for risk analysis and hazard identification, concepts of reliability, maintenance techniques such as RCM and TPM and eliciting expert's knowledge. These topics are presented in order to provide a basis for structuring different MCDM/A problems that are addressed in several chapters. Some fundamental aspects could be used as input to decision models in different forms such as attributes, objectives, criteria, and problem context. Basic Concepts on Risk AnalysisThere are many concepts on risk found in the literature and also different perceptions to it. However, if a decision is being made and risk is involved, then, the risk concept should combine consequences and probabilities, incorporating the DM's preferences over that, as seen in Chap. 2.Actually, a 'decision process' with no DM's preference has no decision being made, as discussed at the end of Chap. 1. Instead of that, that process either: a) has some preference structure incorporated within the model, at random; b) is just arbitrary following a previous decision of someone else.Even so, in most of real cases, the consequences are multidimensional, and therefore, require an MCDM/A approach for building a decision model. The following topics are mainly based on the basic RRM literature and do not incorporate the idea of decision support, as given in Chap. 2. That is, DM's preferences are not necessarily considered in the model.

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“…Considering now another degradation level B > A, τ B −τ A is the second type of hitting time considered here. Its exact survival function has been derived by Bérenguer et al (2003), but in a complex form. In order to simplify and reduce the numerical computation, we use the approximation proposed by Huynh et al (2011) as follows:…”

Section: Degradation Modelingmentioning

confidence: 99%

On the Construction of Mean Residual Life for Maintenance Decision-Making

Huynh

Castro²,

Barros³

et al. 2012

IFAC Proceedings Volumes

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This paper provides a methodology to assess the efficiency of mean residual life (MRL) in condition-based maintenance decision-making for a system subjected to the competing and dependent risks of degradation and shock. Based on this system, the cost models of two quite simple policies implementing MRL-based or degradation-based preventive replacement are developed and compared with each other. Analyzing the equivalence and the performance of both policies allow us to give some conclusions on the interest of the MRL indicator.

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Maintenance Policy for a Continuously Monitored Deteriorating System

Cited by 77 publications

References 10 publications

A modeling framework for deteriorating control system and predictive maintenance of actuators

A modeling framework for deteriorating control system and predictive maintenance of actuators

Basic Concepts on Risk Analysis, Reliability and Maintenance

On the Construction of Mean Residual Life for Maintenance Decision-Making

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