Selective maintenance optimization for systems operating missions and scheduled breaks with stochastic durations

Khatab, Abdelhakim; Aghezzaf, El‐Houssaine; Djelloul, Imene; Sari, Zaki

doi:10.1016/j.jmsy.2017.03.005

Cited by 61 publications

(17 citation statements)

References 21 publications

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“…The mission duration was viewed as a random variable following a probability distribution, while the duration of a break between 2 adjacent missions was fixed. A similar random mission has also been discussed by Cao et al Khatab et al extended the work of Djelloul et al to a circumstance in which both the durations of the maintenance break and the next mission were assumed to be random variables. A stochastic selective maintenance optimization model was developed.…”

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 88%

A literature review on selective maintenance for multi‐unit systems

Cao

Jia

et al. 2018

Quality & Reliability Eng

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Selective maintenance is regarded as a type of profit-generating maintenance policy, playing an important role in balancing limited maintenance resources with system performance. Since 1988, increasing interest has been focused on this research area. Nevertheless, to the best of our knowledge, there is a lack of critical reviews of selective maintenance. This paper is the first systematic review focusing on this relevant topic. In this work, a definition and some specific features of selective maintenance are elaborated. Based on these features, a set of criteria that have been considered in selective maintenance optimization are summarized into 3 categories: system characteristics, maintenance characteristics, and mission profile characteristics. Based on these criteria, a comprehensive literature review on selective maintenance is undertaken. The solution approaches, as well as a general procedure for selective maintenance optimization, are discussed. Finally, some possible directions for further research are provided.

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Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 88%

A literature review on selective maintenance for multi‐unit systems

Cao

Jia

et al. 2018

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…Therefore, at any time t, the state probability of machine i can be obtained on the basis of the Kolmogorov differential equation group, i.e., Eq. (9).…”

Section: B Mission Reliability Model For Multistate Manufacturing Symentioning

confidence: 99%

“…Furthermore, the state probability function of the machine is calculated on the basis of the transfer strength matrix X i of machine i and Eq. (9). Finally, the mission reliability model of the multistate manufacturing system is obtained on the basis of Eq.…”

Section: Selective Maintenance Optimization For Multistate Manufamentioning

confidence: 99%

Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality

Chen

Zhao

et al. 2019

IEEE Access

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Selective maintenance is widely used as a reliability-centered maintenance strategy due to the limited maintenance resources. However, existing selective maintenance studies only consider basic reliability, which cannot systematically describe the operating mechanism of a multistate system, thereby resulting in the inability to obtain an optimal maintenance strategy. Moreover, intelligent manufacturing systems are highly representative of typical multistate industrial systems. In this study, a mission reliability-oriented selective maintenance optimization model for intelligent manufacturing systems that considers the uncertain maintenance effect was proposed. First, a new connotation and modeling method for mission reliability based on multistate system theory was presented to comprehensively characterize the operating mechanism of intelligent manufacturing systems. Second, a quantitative model between maintenance resources and quality based on real-time data was established to reflect the uncertain characteristics caused by repairmen and tools. Third, a selective maintenance decision model of a multistate manufacturing system was developed under the constraints of maintenance cost and time. This constraint combination optimization problem was solved using the particle swarm optimization algorithm. Finally, a case study of selective maintenance optimization for a cylinder head manufacturing system was presented to verify the proposed method.

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“…The selective maintenance problem for a system executing a mission with a random duration was also addressed by Cao et al, 28 and the mission duration in their work was assumed to be exponentially distributed. Khatab et al [29][30][31] also investigated a selective maintenance problem for a circumstance when both the durations of the break and the next mission were random variables governed by probability distributions. In addition, Cao et al 32 addressed a selective maintenance optimization problem for a fuzzy multi-state system executing missions with fuzzy mission durations and breaks.…”

Section: Selective Maintenance Optimizationmentioning

confidence: 99%

Selective maintenance optimization for random phased-mission systems subject to random common cause failures

Jia

Cao

2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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In both industrial and military fields, there is such a kind of complicated system termed as phased-mission system, which executes missions composed of several different phases in sequence. The structure, failure behavior, and working conditions of such a system may change from phase to phase. The duration of each phase of such a system involved is random and follows a probability distribution, and the system may suffer some events resulting in simultaneous failures of different elements with different probabilities. In order to guarantee such a system completes the phased-mission successfully, a selective maintenance model for random phased-mission systems subject to random common cause failures is proposed to optimally identify a subset of maintenance activities to be performed on some elements of the system. Thereinto, a novel analytic model is developed to estimate the probability of the maintained random phased-mission system successfully completing the phased-mission, and we compare it with a well-known Monte Carlo Simulation approach. Finally, the proposed selective maintenance model has been successfully applied to an artillery weapon system. Comparative analysis is carried out to compare the proposed model with the traditional ones, including selective maintenance models for deterministic phased-mission systems and deterministic single-phase mission systems. The results show that ignoring some mission properties (e.g. randomness and multiple phases) in selective maintenance optimization will lead to (1) incorrect system and mission modeling, (2) incorrect computation of the probability of the random phased-mission system successfully completing a mission, and/or (3) nonoptimal selective maintenance options.

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Selective maintenance optimization for systems operating missions and scheduled breaks with stochastic durations

Cited by 61 publications

References 21 publications

A literature review on selective maintenance for multi‐unit systems

A literature review on selective maintenance for multi‐unit systems

Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality

Selective maintenance optimization for random phased-mission systems subject to random common cause failures

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