Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors

Elwany, Alaa; Gebraeel, Nagi; Maillart, Lisa M.

doi:10.1287/opre.1110.0912

Cited by 139 publications

(64 citation statements)

References 47 publications

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“…In the condition-based maintenance literature, there has been a long and rich history of establishing structural properties of optimal maintenance policies (see, e.g., Ross 1971, Makis and Jardine 1992, White 1978, Elwany et al 2011, Maillart 2006, Kurt and Kharoufeh 2010, Ulukus et al 2012. Although a lot of research has been conducted in this area, to our knowledge, this paper constitutes the first paper reporting structural results for maintenance optimization in the presence of model miss-specification.…”

Section: Introductionmentioning

confidence: 99%

Robust Control of Partially Observable Failing Systems

Kim

2016

Operations Research

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This paper is concerned with optimal maintenance decision making in the presence of model misspecification. Specifically, we are interested in the situation where the decision maker fears that a nominal Bayesian model may be miss-specified or unrealistic, and would like to find policies that work well even when the underlying model is flawed. To this end, we formulate a robust dynamic optimization model for condition-based maintenance in which the decision maker explicitly accounts for distrust in the nominal Bayesian model by solving a worst-case problem against a second agent, "nature," who has the ability to alter the underlying model distributions in an adversarial manner. The primary focus of our analysis is on establishing structural properties and insights that hold in the face of model miss-specification. In particular, we prove (i) an explicit characterization of nature's optimal response through an analysis of the robust dynamic programming equation, (ii) convexity results for both the robust value function and the optimal robust stopping region, (iii) a general robustness result for the preventive maintenance paradigm, and (iv) the optimality of a robust control limit policy for the important subclass of Bayesian change point detection problems. We illustrate our theoretical result on a real-world application from the mining industry.

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Section: Introductionmentioning

confidence: 99%

Robust Control of Partially Observable Failing Systems

Kim

2016

Operations Research

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“…It has been shown to have a cost-saving and a better generalization capability than conventional constant control-limit policy. The studies about dynamic control-limit policy can be classified mainly into three categories, such as inspection rate-dependent threshold [5], age-dependent threshold [4,8,15] and degradation-dependent threshold [26]. For an inspection rate-dependent threshold [5], the higher the inspection rate, the higher the degradation-type PM threshold.…”

Section: Introductionmentioning

confidence: 99%

“…For an age-dependent threshold, PM threshold decreases in age and should be triggered by smaller signal values when it deteriorates [4]. The PM threshold can also be non-decreasing in age and it can be more tolerant of larger signal values for older systems, if there is increasing accuracy in predicting the future signal value [8]. For a degradation-dependent threshold, Zhao et al [26] proposed an adaptive maintenance decision to take into account the state of covariates to dynamically adapt the PM threshold.…”

Section: Introductionmentioning

confidence: 99%

An electricity price-dependent control-limit policy for conditionbased maintenance optimization for power generating unit

Xia

2016

EiN

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An electricity price-dependent control-limit policy for conditionbAsed mAintenAnce optimizAtion for power generAting unit zAstosowAnie strAtegii uzAleżniAjącej termin przeglądu od ceny prądu elektrycznego do optymAlizAcji utrzymAniA ruchu AgregAtu prądotwórczego z uwzględnieniem jego stAnu technicznego QIAN X, WU Y. An electricity price-dependent control-limit policy for condition-based maintenance optimization for power generating unit. Eksploatacja i Niezawodnosc -Maintenance and Reliability 2016; 18 (2): 245-253, http://dx

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“…Some successful examples of implementing CBM in real systems have demonstrated its efficiency and effectiveness in preventing catastrophic failures and improving maintenance performance (e.g. [1,4,6,11,12,14]). …”

Section: Introductionmentioning

confidence: 99%

“…The degrading system was modeled by a gamma process, and multiple control limits were used to determine the current maintenance actions and future inspection times. Elwanly et al [6] analyzed a replacement problem for the exponentially increasing degradation system. They sciENcE aNd tEchNology demonstrated that the optimal replacement policy was a multi-level control-limit policy with monotonically increasing control limits.…”

Section: Introductionmentioning

confidence: 99%

Optimal replacement policy for a periodically inspected system subject to the competing soft and sudden failures

Tang

2015

Eksploatacja i Niezawodnosc - Maintenance and Reliability

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Optimal replacement pOlicy fOr a periOdically inspected system subject tO the cOmpeting sOft and sudden failures Optymalna pOlityka wymiany dO zastOsOwania w systemach pOddawanych przeglądOm OkresOwymnarażOnych na kOnkurujące uszkOdzenia parametryczne i nagłe demonstrated that the optimal replacement policy was a multi-level control-limit policy with monotonically increasing control limits. However, considering only the soft failure seems to be inadequate for the degrading systems that are also subject to the sudden failures. In many practical situations, sudden failures are very likely to interrupt the graceful degradation and then result in more serious consequences. Therefore, in this paper, we consider a competing risk maintenance situation. The system is regarded as failed when the degradation process reaches a critical threshold or when the sudden failure occurs although the degradation process has not reached the threshold. Most of the present papers that deal with such failure scenario assume that the degradation process and the sudden failure are independent with each other. Nevertheless, even if independence is demonstrated to be appropriate for certain types of competing risks, e.g. [2,8,20,21], in many situations the dependent structure between the two failure modes is of importance and should not be neglected. We consider the dependence is described by the failure rate of the sudden failure, which is influenced by both the age and the degradation state of the system. Similar assumptions were also found in Huynh et al. [9], Liu et al. [15], Castro et al. [3] and Huynh et al.[10] to deal with competing risk maintenance situation. A preventive threshold in terms of the degradation state was optimized in Huynh et al. [9] and Liu et al. [15] with different monitoring strategies. The former focused on periodically inspected systems and the latter dealt with continuously monitored ones. Castro et al. [13] also considered a degradation state -based control limit as the alarm of preventive maintenance, but multiple degradation processes were involved in the failure mechanism. In Huynh et al. [10], a novel CBM strategy was proposed using the mean residual life as the control limit. The effectiveness and potential of condition indices that are not strictly limited to failure mechanism in CBM decision-making problems was firstly investigated.In this paper, we will focus on analyzing the optimal replacement policy for a periodically inspected system subject to the competing soft and sudden failures. This policy performs the preventive replacement only at inspection instants, and correctively replaces the system at the time of failure. We describe the degrading system using a gamma degradation process, which implies that the soft failure of the system results from a gradual and irreversible accumulation of deterioration. The failure rate corresponding to the sudden failure is described by a proportional hazards model, which means that it is influenced by both the age of the system and the state degradation of ...

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Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors

Cited by 139 publications

References 47 publications

Robust Control of Partially Observable Failing Systems

Robust Control of Partially Observable Failing Systems

An electricity price-dependent control-limit policy for conditionbased maintenance optimization for power generating unit

Optimal replacement policy for a periodically inspected system subject to the competing soft and sudden failures

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