Mission-Oriented Maintenance Optimization Subject to Resources Constraints

Cao, Wenbin; Hu, Qiwei; Song, Wei; Wu, Yutao

doi:10.1109/incos.2016.79

Cited by 4 publications

(5 citation statements)

References 18 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%

“…The first model was to maximize the system availability with both time and cost constraints, and the other was to minimize cost with availability and time constraints. Cao et al investigated a selective maintenance problem for a series‐parallel system, and the aim was to minimize the total maintenance cost under time and availability constraints. A simulation approach based on a Monte Carlo method was proposed to assess the system availability under different maintenance options.…”

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 99%

“…The production loss and maintenance cost due to such failures were formulated. Cao et al addressed a selective maintenance optimization problem under 2 kinds of missions: a random‐interruption‐permitted mission and a random‐interruption‐inadmissible mission. The results showed that maintenance during the mission could improve the system availability.…”

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 99%

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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%

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 99%

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 99%

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A literature review on selective maintenance for multi‐unit systems

Cao

Jia

et al. 2018

Quality & Reliability Eng

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“…A comparison between the selective maintenance results of deterministic mission duration and stochastic mission duration showed that ignoring the randomness of the next mission duration might yield biased maintenance decisions. 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.…”

Section: Selective Maintenance Optimizationmentioning

confidence: 99%

“…where constraint (27) is the minimal acceptable probability of the system successfully completing the next mission. Constraint (28) shows the relationship of the age of element i before and after maintenance. Constraint (29) is the limited maintenance spares.…”

Section: Probability Of the Rpms Successfully Completing The Next Mismentioning

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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