Selective Maintenance for Multistate Series Systems With S-Dependent Components

Dao, Cuong D.; Zuo, Ming J.

doi:10.1109/tr.2015.2494689

Cited by 97 publications

(47 citation statements)

References 29 publications

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“…However, the system configuration considered in Cassady et al was essentially redundant, and the maintenance decision was whether the failed components needed to be replaced. Later, Lust et al and Zhu et al took systems with partially redundant structures (components arranged in series and parallel) as examples to illustrate the selective maintenance problem, while a system with a complex structure (including series, parallel, and bridge) was considered by Maaroufi et al, Hoai et al, Tambe et al, Dao et al, and Dao et al, who carried out research on selective maintenance optimization for systems with series structures. A similarity in the previously mentioned works related to partially redundant or series systems is that there was more than 1 kind of maintenance action for each component. Lifetime Features.…”

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 99%

“…The universal generating function was utilized to evaluate the probability of the maintained MSS successfully completing the succeeding mission. Pandey et al and Dao et al addressed a selective problem for a multi‐state system consisting of multi‐state components (MSS&MSC). They assumed that the components had many states, and the transition time between a pair of states in the next mission followed an exponential distribution.…”

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: 99%

Section: A Review Of Selective Maintenance Modelingmentioning

confidence: 99%

A literature review on selective maintenance for multi‐unit systems

Cao

Jia

et al. 2018

Quality & Reliability Eng

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“…A probabilistic method was proposed with appropriate cost-benefit analyses for MSS in the works of Dao et al 17, 18 Garavaglia and Sgambi 19 proposed the study of strategies of selective maintenance for a steel bridge immersed in an aggressive environment. A probabilistic method was proposed with appropriate cost-benefit analyses for MSS in the works of Dao et al 17, 18 Garavaglia and Sgambi 19 proposed the study of strategies of selective maintenance for a steel bridge immersed in an aggressive environment.…”

Section: Maintenance Kmentioning

confidence: 99%

“…Yu and Huang 16 established an optimization model for an MSS subject to both maintenance cost and time. A probabilistic method was proposed with appropriate cost-benefit analyses for MSS in the works of Dao et al 17,18 Garavaglia and Sgambi 19 proposed the study of strategies of selective maintenance for a steel bridge immersed in an aggressive environment. In these papers, there are different maintenance actives.…”

Section: Maintenance K Mission K Mission K+1mentioning

confidence: 99%

A high‐performance maintenance strategy for stochastic selective maintenance

Zhao

Liu

Zhao

et al. 2018

Concurrency and Computation

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Selective maintenance is often applied in many industrial environments where maintenance is performed between sequence missions. When the mission time is stochastic and there are multiple maintenance workers with different capacities, the system reliability of the next work mission can be maximized by using a stochastic model under the constraint of the limit maintenance time.The optimal maintenance strategy is obtained with an optimization algorithm. A simulation was performed to verify the validity and feasibility of the proposed model. KEYWORDS group maintenance, maintenance time, mission time, stochastic model, stochastic selective maintenance INTRODUCTIONAfter the wisdom of China was presented, cyber-physical systems, 1 cloud computing, wireless networks, 2 big data, Vehicular Network, 3,4 Industrial Intelligence Management, etc, have developed rapidly. In the proper and safe operation of industrial and military equipment, transportation systems maintenance is very important. 5 Maintenance management can establish reasonable maintenance policies for complex systems to meet new design requirements with using reliability and maintenance engineering analyses, such as equipment reliability and maintainability, in order to realize timely and effective maintenance to ensure the performance of the system with the lowest resource consumption. 6In many industrial fields (eg, manufacturing systems, military equipment systems, and power generation systems), maintenance is performed between two continuous missions. Each component or equipment can be repaired in different ways, such as no maintenance, minimal maintenance, preventive maintenance, and replacement. However, all maintenance tasks are not fully performed because of limited resources, such as maintenance time, cost, tools, and maintenance workers, 7 so part of the maintenance tasks are executed to maximize the system reliability of the next work mission. This is called selective maintenance. The workflow of selective maintenance is shown in Figure 1.Unlike the deterministic selective maintenance, a feasible deterministic maintenance set cannot be obtained in the stochastic selective maintenance because of the stochastic maintenance time or work time. For different systems, many different models are defined. Cassady et al 7 defined selective maintenance and a mathematical programming model for a two-state system. Cassady et al 8 developed a model that maximizes the system reliability with maintenance time Constraints for a series-parallel system with two-state components. In the model, the lifespan of a component follows a Weibull distribution, so that this reliability function is influenced by the age of components at the beginning of the mission and the mission time. Zhu et al 9 established a time-constrained Concurrency Computat Pract Exper. 2019;31:e4840. wileyonlinelibrary.com/journal/cpe

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“…Pandey, Zuo, and Moghaddass (2013) investigated the selective maintenance problem for a MSS where the functioning of each component is modelled as a continuous-time Markov chain with more than two states. Dao, Zuo, and Pandey (2014) and Dao and Zuo (2016) studied the selective maintenance problem while considering economic and stochastic dependencies among MSS components. Such dependency is also considered when dealing with the maintenance optimisation of MSS.…”

Section: Introductionmentioning

confidence: 99%

Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

Khatab¹,

Aghezzaf

Diallo

et al. 2017

International Journal of Production Research

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This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme.

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Selective Maintenance for Multistate Series Systems With S-Dependent Components

Cited by 97 publications

References 29 publications

A literature review on selective maintenance for multi‐unit systems

A literature review on selective maintenance for multi‐unit systems

A high‐performance maintenance strategy for stochastic selective maintenance

Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

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