A Stationary Grouping Maintenance Strategy Using Mean Residual Life and the Birnbaum Importance Measure for Complex Structures

Vu, Hai Canh; Van, Phuc Do; Barros, Anne

doi:10.1109/tr.2015.2455498

Cited by 52 publications

(29 citation statements)

References 42 publications

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“…An important indicator for decision making of system-level maintenance strategies is to analyse if the failure of an asset can cause the system failure. With static systems this can be evaluated using minimal cut-set concepts (Vu, Do, & Barros 2016). However, in the context of dynamic repairable scenarios, it is necessary to analyse Minimal Cut Sequence Sets (MCSSs) (Walker & Papadopoulos 2009).…”

Section: Discussionmentioning

confidence: 99%

“…The system is assumed to be a series model and the failure behaviour of system components is defined by Weibull distributions. (Vu, Do, & Barros 2016) make use of Birnbaum importance measures and mean residual life for system-level maintenance strategies. Assets are grouped for maintenance depending on if the failure of a component can cause the system failure.…”

Section: Related Workmentioning

confidence: 99%

“…Analysed parameters include inspection, renewal, and repair times and maintenance threshold. All the analysed system-level models take into account the combinatorial failure logic of the system (Nguyen, Do, & Grall 2015, Do, Vu, Barros, & Bérenguer 2015, Vu, Do, & Barros 2016. Besides, most of the reviewed approaches integrate a degradation process to model the degradation of the asset and facilitate the posterior analytical treatment (Grall, Bérenguer, & Dieulle 2002, Haddad, Sandborn, & Pecht 2012, Do, Vu, Barros, & Bérenguer 2015, Do, Voisin, Levrat, & Iung 2015.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

Aizpurua¹,

Catterson²,

Chiacchio

et al. 2016

Risk, Reliability and Safety: Innovating Theory and Practice

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The implementation of maintenance strategies which integrate online condition data has the potential to increase availability and reduce maintenance costs. Prognostics techniques enable the implementation of these strategies through up-to-date remaining useful life estimations. However, a cost-benefit assessment is necessary to verify the scale of potential benefits of condition-based maintenance strategies and prognostics for a given application. The majority of prognostics applications focus on the evaluation of a specific failure mode of an asset. However, industrial systems are comprised of different assets with multiple failure modes, which in turn, work in cooperation to perform a system level function. Besides, these systems include time-dependent events and conditional triggering events which cause further effects on the system. In this context not only are the system-level prognostics predictions challenging, but also the cost-benefit analysis of condition-based maintenance policies. In this work we combine asset prognostics predictions with temporal logic so as to obtain an up-to-date system level health estimation. We use asset level and system level prognostics estimations to evaluate the cost-effectiveness of alternative maintenance policies. The application of the proposed approach enables the adoption of conscious trade-off decisions between alternative maintenance strategies for complex systems. The benefits of the proposed approach are discussed with a case study from the power industry.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

Aizpurua¹,

Catterson²,

Chiacchio

et al. 2016

Risk, Reliability and Safety: Innovating Theory and Practice

View full text Add to dashboard Cite

show abstract

“…[5][6][7] Most existing OM studies consider the combination of OM of a certain component with maintenance activities of other components (e.g., group maintenance). [8][9][10][11] Other types of opportunity which have been investigated are system stoppages due to production causes such as the blockage or starvation of product flow or production waits, 12 stops of bottleneck machines, 13 or the setup time between productions of two successive batches. 14 Some other studies considered general external opportunities.…”

Section: Introductionmentioning

confidence: 99%

Optimization of condition‐based maintenance considering partial opportunities

Truong‐Ba

Borghesani

Cholette

et al. 2019

Quality & Reliability Eng

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Recent studies have demonstrated the economic benefit of exploiting partial opportunities for maintenance, which arise from the reduction of costs of doing partial maintenance utilizing the opportunity given. A typical example is an externally induced production stop with a duration that may not be sufficient to a complete maintenance activity. This paper combines partial opportunities and condition‐based maintenance (CBM) strategies and proposes an innovative maintenance optimization method considering time‐varying economic conditions. This scenario naturally fits a broad range of assets with a finite design life (including long‐life machinery and infrastructure), operating under variable economic conditions and usage‐intensities. The maintenance optimization problem is formulated in this study as a finite‐horizon Markov decision process, where the randomly occurring opportunities are accounted for by augmenting the time‐varying, decision‐dependent transition probabilities. A dynamic programming approach is subsequently used to obtain the optimal CBM policy, consisting of time‐varying thresholds on equipment condition and the cost of conducting maintenance during the arrived opportunity. A case study of such a maintenance policy for an induced draft fan of a sugar production system located in Queensland, Australia, is undertaken to evaluate the benefits of the proposed methodology against more traditional approaches that neglect opportunities or consider only replete opportunity durations.

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“…In reliability engineering, they are used to prioritize components in a system for reliability improvement, [1,2,3]. Recently, importance measures have been applied for maintenance optimization and spare parts management [9,13,15]. More recently, the link between component importance and preventive maintenance decision making has been discussed in [15].…”

Section: Introductionmentioning

confidence: 99%

MRL-based Importance Measures

Do¹,

Bérenguer²,

Borgonovo³

2019

Proceedings of the 29th European Safety and Reliability Conference (ESREL)

Self Cite

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In this paper, we propose a novel importance measure, namely LIM , which is defined as the improvement ability in the system residual life when replacing a component/group of components at a given time. LIM measure allows considering the current condition (state or degradation level) of all components at given time and the system structure into a single metric to rank a component/group of components regarding to the system life time improvement ability. Moreover, to take into account economic aspects (e.g., preventive maintenance costs, benefit gained by preventive maintenance and economic dependence between components), an extension of LIM measure is then investigated. Thanks to LIM measure and its extension, a component/group of components can be "optimally" selected for preventive maintenance regarding to the technical criterion (residual life of the system) and/or the economic issues (benefit and cost). A numerical example of a 4-component system is introduced to illustrate the use and the advantages of the proposed importance measures.

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A Stationary Grouping Maintenance Strategy Using Mean Residual Life and the Birnbaum Importance Measure for Complex Structures

Cited by 52 publications

References 42 publications

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

Optimization of condition‐based maintenance considering partial opportunities

MRL-based Importance Measures

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