Online maintenance policy for a deteriorating system with random change of mode

Saassouh, Bassem; Dieulle, Laurence; Grall, Antoine

doi:10.1016/j.ress.2006.10.017

Cited by 70 publications

(34 citation statements)

References 10 publications

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“…According to the characteristic that degradation rate is diverse in different degradation stage for two-stage degradation system, Saas-sciENcE aNd tEchNology souh et al [5,7,19] put forward adaptive maintenance policy. And this maintenance policy has been proved to be useful.…”

Section: Adaptive Maintenance Policymentioning

confidence: 99%

“…Some researchers have studied on the degradation process modeling for two-stage degradation system. But in most articles [5,6,17,19] the degradation processes are assumed to be continuous Gamma process, and degradation rates for different degradation stages are presented by different Gamma parameters. Wiener process is also used for two-stage degradation modeling [9].…”

Section: Introductionmentioning

confidence: 99%

“…But the degradation rate suddenly increased will bring significant impact on maintenance policy. On the basis that change-point of degradation rate can be monitored perfected, Saassouh [19] put forward an activation zone to plan the maintenance action for a two-stage system. Fouladirad [5,7] proposed an adaptive maintenance policy based on online change detection procedures, where alarm thresholds were diverse in different degradation stage as the degradation rate change.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear degradation modeling and maintenance policy for a two-stage degradation system based on cumulative damage model

Ni¹,

Zhao²,

Song³

et al. 2016

EiN

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show abstract

Section: Adaptive Maintenance Policymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear degradation modeling and maintenance policy for a two-stage degradation system based on cumulative damage model

Ni¹,

Zhao²,

Song³

et al. 2016

EiN

View full text Add to dashboard Cite

show abstract

“…, t n , respectively. While the structural deterioration process is indeed a complex non-stationary stochastic process (Dieulle et al, 2003;Saassouh et al, 2007;Wang et al, 2015), neither fully-correlated nor statistically independent by nature, revealed that the assumption of fully-correlated deterioration is reasonable for reliability analysis producing acceptable error. As a result, in this study, the resistance deterioration process is assumed to be a fully-correlated one, which means that the overall trajectory of deterioration will be determined as soon as the deterioration type and the deterioration value at any time are given.…”

Section: Structural Reliability Analysismentioning

confidence: 99%

Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information

Wang

Pang

et al. 2016

J. Zhejiang Univ. Sci. A

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The performance of an aging structure is commonly evaluated under the framework of reliability analysis, where the uncertainties associated with the structural resistance and loads should be taken into account. In practical engineering, the probability distribution of resistance deterioration is often inaccessible due to the limits of available data, although the statistical parameters such as mean value and standard deviation can be obtained by fitting or empirical judgments. As a result, an error of structural reliability may be introduced when an arbitrary probabilistic distribution is assumed for the resistance deterioration. With this regard, in this paper, the amount of reliability error posed by different choices of deterioration distribution is investigated, and a novel approach is proposed to evaluate the averaged structural reliability under incomplete deterioration information, which does not rely on the probabilistic weight of the candidate deterioration models. The reliability for an illustrative structure is computed parametrically for varying probabilistic models of deterioration and different resistance conditions, through which the reliability associated with different deterioration models is compared, and the application of the proposed method is illustrated.

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“…wear) where it is the degradation increasing which follows a stochastic process, e.g. a Gamma law in [5]. [6] use a vector, representing covariables to take into account in the authors' degradation model of the variations of the operational conditions.…”

Section: Problem Statement On Degradation Model For Prognosismentioning

confidence: 99%

Degradation state model-based prognosis for proactively maintaining product performance

et al. 2008

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Maintenance plays now a critical role in manufacturing for achieving important cost savings and competitive advantage while preserving product conditions. It suggests moving from conventional maintenance practices to predictive strategy. Indeed the maintenance action has to be done at the right time according the component Remaining Useful Life (RUL) assessed by a prognosis process. The accuracy of the RUL is mainly depending on the relevance of the component degradation model used for prediction. In that way, this paper aims at discussing an efficient degradation model taking into account the operational conditions, the health monitoring and the maintenance actions. This model is based on discrete states associated with the degradation levels, and on a cumulative function modelling the transition time between successive states. The model is implemented by means of Stochastic Activity Networks (SAN). The feasibility and added value of such degradation models for prognosis is then highlighted through experimentations made on manufacturing TELMA platform.

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Online maintenance policy for a deteriorating system with random change of mode

Cited by 70 publications

References 10 publications

Nonlinear degradation modeling and maintenance policy for a two-stage degradation system based on cumulative damage model

Nonlinear degradation modeling and maintenance policy for a two-stage degradation system based on cumulative damage model

Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information

Degradation state model-based prognosis for proactively maintaining product performance

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