Selective Maintenance Modeling for a Multi-State System Considering Human Reliability

Zhao, Zhonghao; Yan, Xiaoyuan; Xiao, Bing; Sun, Xiaotong

doi:10.1109/icsrs.2018.8688871

Cited by 5 publications

(4 citation statements)

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“…Some were based on the risk probability assessment, such as Reference [22], which proposed a risk model for the definition of the function of reliability (or failure) of "human component" in a railway system and Reference [26], which presented a risk-based methodology to estimate shutdown inspection and the maintenance interval by integrating human errors with degradation modelling of a processing unit. Some of the papers [17,19,28,34] adopted the HRA methods, analysed maintenance error, and measured the occurrence of human error during maintenance tasks. For example, Reference [17] presents a conceptual modelling of human error, defined the system failure, listed and analysed the related human operation, estimated the error probabilities and the effects of human errors on the system.…”

Section: Topic 1 and Topic 2: Human Error And Human Reliability In In...mentioning

confidence: 99%

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

et al. 2021

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Maintenance contributes to gaining high business performance, guarantees system availability and reliability as well as safe and sustainable operations. Maintenance activity effectiveness depends on competences and the skills of operators whose performance strongly affects maintenance and production operations. The research field of human issues in industrial maintenance was deeply addressed in the literature; however, the current industrial paradigm, which focusses on the integration of new technologies in conventional manufacturing operations to support human performance, sheds light on new challenges for enterprises and opportunities for research in this field. While some literature reviews in the field of human errors and human factors are available, no study investigated the main topics, research trends and challenges related to the role of maintenance operators in manufacturing systems. This paper addresses the current state-of-the-art role of maintenance operators in manufacturing systems, providing an overview of the main studies. A systematic literature review was carried out to identify significant papers. Then, a topic modelling algorithm was used to detect the main topics of the selected papers to provide the research trends of the subject. The identified topics provided interesting research insights on the human role in industrial maintenance. Research trends and further research opportunities were defined.

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Section: Topic 1 and Topic 2: Human Error And Human Reliability In In...mentioning

confidence: 99%

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

et al. 2021

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“…Therefore, the composition function is given by: 20 , 0.2392v 0 + 0.3108v 10 + 0.45v 20 = 0.3566v 0 + 0.4004v 10 + 0.243v 20 (24) If the performance rate requirement of the MSS at the end of the next mission is 10, the reliability of the MSS to perform the next mission is 0.6434.…”

Section: Estimation Of Component State Degradation and Multi-state Symentioning

confidence: 99%

“…It can be seen that as the HEP decreases, there is a higher probability that the component will be in a higher state. If we use the selective maintenance model proposed in [24], the probability of components in different states after maintenance is equal for all workers, i.e., P n m (Z i = B i ) = 0.2, which is unable to reflect the different levels of workers. Table 1 shows the probability ranking of component i in each level.…”

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confidence: 99%

Selective Maintenance Optimization for a Multi-State System Considering Human Reliability

et al. 2019

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In an actual industrial or military operations environment, a multi-state system (MSS) consisting of multi-state components often needs to perform multiple missions in succession. To improve the probability of the system successfully completing the next mission, all the maintenance activities need to be performed during maintenance breaks between any two consecutive missions under limited maintenance resources. In such case, selective maintenance is a widely used maintenance policy. As a typical discrete mathematics problem, selective maintenance has received widespread attention. In this work, a selective maintenance model considering human reliability for multi-component systems is investigated. Each maintenance worker can be in one of multiple discrete working levels due to their human error probability (HEP). The state of components after maintenance is assumed to be random and follow an identified probability distribution. To solve the problem, this paper proposes a human reliability model and a method to determine the state distribution of components after maintenance. The objective of selective maintenance scheduling is to find the maintenance action with the optimal reliability for each component in a maintenance break subject to constraints of time and cost. In place of an enumerative method, a genetic algorithm (GA) is employed to solve the complicated optimization problem taking human reliability into account. The results show the importance of considering human reliability in selective maintenance scheduling for an MSS.

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“…Shahraki et al 14 studied selective maintenance optimization for multi-state systems with stochastically dependent components and stochastic imperfect maintenance actions. Of course, some scholars have done some other studies on multi-state selective maintenance problems, [23][24][25][26] which will not be introduced in detail here. However, the above research on multi-state selective maintenance still has the following problems:…”

Section: Introductionmentioning

confidence: 99%

Selective maintenance of multi-state series systems considering maintenance quality uncertainty and failure effects

Ran

Zhang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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In order to improve the lifetime and reliability of equipment operation stage, it is necessary to carry out maintenance for components. The typical selective maintenance model does not consider the maintenance quality uncertainty and the failure effects, which may make the decision-maker overestimates the reliability of completing the next task after system maintenance, resulting in incorrect maintenance decision and prone to serious consequences of failure. In this paper, the potential discrepancy between the target maintenance quality and the actual maintenance quality of the decision maker is considered. At the same time, a multi-state FMECA is proposed to measure the failure effects under different states. Finally, the selective maintenance model of the multi-state series systems is established and solved by the genetic algorithm. The results show that considering the effect of component failure and the uncertainty of maintenance quality has an influence on maintenance decision. The maintenance decision made in this way is more consistent with the engineering practice.

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Selective Maintenance Modeling for a Multi-State System Considering Human Reliability

Cited by 5 publications

References 5 publications

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

Selective Maintenance Optimization for a Multi-State System Considering Human Reliability

Selective maintenance of multi-state series systems considering maintenance quality uncertainty and failure effects

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