Opportunistic maintenance considering non-homogenous opportunity arrivals and stochastic opportunity durations

Truong‐Ba, Huy; Cholette, Michael E.; Borghesani, Pietro; Zhou, Yancong; Ma, Lin

doi:10.1016/j.ress.2016.12.011

Cited by 27 publications

(8 citation statements)

References 38 publications

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“…It is often possible to shrink the discretization interval Δ t until the arrival of a second opportunity is negligibly small. If Δ t cannot be decreased, the methods presented here can be extended to account for multiple opportunities using the authors' previous work …”

Section: Model Descriptionmentioning

confidence: 99%

“…However, in some situations, traditional stationary PM is not optimal, particularly when downtime and/or maintenance costs are varying with time. Furthermore, some events, such as the maintenance of other components, weather‐caused production stops, or low‐demand periods can provide an “opportunity” to implement PM with lower cost . A maintenance policy which takes advantage of these chances is called an opportunistic maintenance (OM) policy …”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, some events, such as the maintenance of other components, weathercaused production stops, or low-demand periods can provide an "opportunity" to implement PM with lower cost. 5,6 A maintenance policy which takes advantage of these chances is called an opportunistic maintenance (OM) policy. [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).…”

Section: Introductionmentioning

confidence: 99%

“…5,6 A maintenance policy which takes advantage of these chances is called an opportunistic maintenance (OM) policy. [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.…”

Section: Introductionmentioning

confidence: 99%

“…If Δt cannot be decreased, the methods presented here can be extended to account for multiple opportunities using the authors' previous work. 6 Assumption (5) can be violated without significantly affecting the validity of the maintenance optimization results because i. If the maintenance spans over two or more intervals, the system state is restored immediately after the current time epoch; and the system degradation dynamics are therefore artificially shifted by a few time intervals.…”

mentioning

confidence: 99%

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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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