A new analytical method to optimise the preventive maintenance interval by using a semi-Markov process and z-transform with an application to marine diesel engines

Sánchez-Herguedas, Antonio; Nieto, Ángel Isidro Mena; Rodrigo-Muñoz, Francisco

doi:10.1016/j.ress.2020.107394

Cited by 21 publications

(17 citation statements)

References 38 publications

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“…All the α i 's are null in (Sànchez Herguedas et al, 2020;Sànchez-Herguedas et al, 2021). The use of cumulative distribution functions F i and the probability γ shows a predictive aspect of the maintenance (γ is 1 in (Sànchez Herguedas et al, 2020;Sànchez-Herguedas et al, 2021)). Hence, the model (1) highlights both corrective and preventive aspects of maintenance.…”

Section: Analysis and Optimization Methodology 21 Modeling Of A Multi-state Dynamicsmentioning

confidence: 99%

“…Preventive maintenance (systematic, conditional or predictive maintenance) is intended to delay and limit the impact of total failure. However, a high frequency of preventive maintenance leads to additional costs and limits the sought availability (Sànchez Herguedas et al, 2020;Sànchez-Herguedas et al, 2021). It is therefore necessary to choose the right maintenance strategy (Meuwisse et al, 1993).…”

Section: Introductionmentioning

confidence: 99%

“…Optimization is made on the basis of systematic and perfect preventive maintenance from a number of components beyond a certain degradation threshold. Recently, the authors in (Sànchez Herguedas et al, 2020;Sànchez-Herguedas et al, 2021) approached the optimization of the periodic preventive maintenance interval of a system by taking into account gains/losses due to dwell times in each of the three maintenance states (preventive maintenance, corrective maintenance, operation). Gains or losses related to state transitions are also taken into account.…”

Section: Introductionmentioning

confidence: 99%

“…Gains or losses related to state transitions are also taken into account. The work in (Sànchez Herguedas et al, 2020;Sànchez-Herguedas et al, 2021) generalizes the notion of system state by combining the state itself with the maintenance action in progress. However, they do not take in account neither the degradation nor the level of maintenance (minimal or imperfect maintenance and perfect maintenance).…”

Section: Introductionmentioning

confidence: 99%

“…The objective functions to optimize are presented in subsection 2.3 while the optimization procedure is presented in subsection 2.4. In Section 3 we apply the methodology stated in Section 2 to a case study inspired by (Sànchez Herguedas et al, 2020;Sànchez-Herguedas et al, 2021). The paper ends with a conclusion in Section 4.…”

Section: Introductionmentioning

confidence: 99%

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Semi-Markovian approach to optimizing the time of systematic preventive maintenance and the level of maintenance over a finite horizon

Fotsa-Mbogne¹,

Fonkou²,

Nzie³

et al. 2021

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This work is concerned with the problem of optimizing maintenance policies in terms of economical rewards and availability. We consider a system with multiple states in terms of healthy mode (good state, degraded state and failure state) and maintenance action (running state, stopped for maintenance). The level of maintenance (perfect or not) is also taken into account. We propose semi-Markovian model highlighting the eﬀects of dwell times and transitions on economical rewards. We determine an optimal policy conditionally upon the current state according to eight decision parameters related to time intervals between two preventive maintenances and the level of maintenance. We show through a sensitive analysis that decision parameters have nonlocal eﬀects that imply a multiple objective function. Hence, we propose a compromise by optimizing the asymptotic average reward.

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