A new fuzzy approach to identify the critical risk factors in maintenance management

Nazeri, Ali; Naderikia, Reza

doi:10.1007/s00170-017-0222-4

Cited by 38 publications

(19 citation statements)

References 101 publications

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“…Figure 10 shows that some important findings can be clearly deduced. First, the ranking orders of the proposed framework (ME, EL, OP, IN, and OT) are in agreement with the ranking order of the Fuzzy FMEA framework approach [28]. This demonstrates the validity of our proposed risk priority framework.…”

Section: Final Prioritization With Comparisonsupporting

confidence: 73%

“…These findings of the ANP step support the view that the failure modes influenced the main cluster weights. However, when comparing ANP results to those of previous studies [20,28], the feedback effect of FMs on the main cluster must be pointed out and considered. used for these calculations.…”

Section: The Interdependency and Impact Feedbackmentioning

confidence: 99%

“…The new hybrid framework based on linguistic FMEA, DEMATEL, and ANP approaches is applied to alleviate the drawbacks of the traditional FMEA method. Hence, the traditional FMEA, the linguistic FMEA framework [49], and the Fuzzy FMEA framework [28] are selected for comparison to investigate the benefits of the proposed risk framework. Table 14 reveals the ranking results of the five FMs produced from the above four FMEA framework approaches.…”

Section: Final Prioritization With Comparisonmentioning

confidence: 99%

“…In the previous studies, it was observed that FMEA frameworks were modified to simplify the failure modes analysis and prioritization [43][44][45][46]. Similarly, the work of Nazeri and Naderikia [28] has clearly demonstrated an improved traditional FMEA by integrating expert weights, fuzzy methods, and other techniques into the analysis. However, unlike the study of Nazeri and Naderikia [28], most of the improved versions lack a focus on the back impact of failure modes on the main domain.…”

Section: Introductionmentioning

confidence: 98%

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Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework

et al. 2019

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The oil and gas industry is looking for ways to accurately identify and prioritize the failure modes (FMs) of the equipment. Failure mode and effect analysis (FMEA) is the most important tool used in the maintenance approach for the prevention of malfunctioning of the equipment. Current developments in the FMEA technique are mainly focused on addressing the drawbacks of the conventional risk priority number calculations, but the group effects and interrelationships of FMs on other measurements are neglected. In the present study, a hybrid distribution risk assessment framework was proposed to fill these gaps based on the combination of modified linguistic FMEA (LFMEA), Analytic Network Process (ANP), and Decision Making Trial and Evaluation Laboratory (DEMATEL) techniques. The hybrid framework of FMEA was conducted in a hazardous environment at a power generation unit in an oil and gas plant located in Yemen. The results show that mechanical and gas leakage FM in electrical generators posed a greater risk, which critically affects other FMs within the plant. It was observed that the suggested framework produced a precise ranking of FMs, with a clear relationship among FMs. Also, the comparisons of the proposed framework with previous studies demonstrated the multidisciplinary applications of the present framework.

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Section: Final Prioritization With Comparisonsupporting

confidence: 73%

Section: The Interdependency and Impact Feedbackmentioning

confidence: 99%

Section: Final Prioritization With Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework

et al. 2019

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“…For the purposes of evaluation and selection of optimal locations for freight villages, authors of [137] developed a GIS-ANP-TOPSIS framework. For selection of the most appropriate maintenance policy, an integrated MCDM approach was developed by [138] on the basis of FANP technique and in combination with the DEMATEL. In [139], ANP and DEMETAL were used to determine the leading accident casual factors and to analyze the influence of the relationships of human and organization factors.…”

Section: Hybrid/combined Mcdm Approachesmentioning

confidence: 99%

Application of Multicriteria Decision-Making Methods in Railway Engineering: A Case Study of Train Control Information Systems (TCIS)

Djordjević¹,

Krmac²

2018

Modern Railway Engineering

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In order to improve its position in the transport market railway, as a complex system, it has to fulfill a number of objectives such as increased capacity and asset utilization, improved reliability and safety, higher customer service levels, better energy efficiency and fewer emissions, along with increased economic viability and profits. Some of these objectives call for the implementation of maximum values, while some of them require minimum values. Additionally, some can be expressed quantitatively, while some, for example, customer service, can be described qualitatively through a descriptive scale of points. The application of MCDM in railway engineering can play a significant role. Therefore, the major objective of this chapter is the review of the application of MCDM methods in railway engineering. As one of the means in achieving the objectives of railways and above all the utilization of capacity are Train Control Information Systems (TCIS). Based on that, the aim of this chapter is the evaluation of the efficiency of TCIS in the improvement of railway capacity utilization through defined technical-technological indicators. The non-radial Data Envelopment Analysis (DEA) model for the evaluation of TCIS efficiency in improvement of utilization of railway capacity using the selected indicators is proposed. The proposed non-radial DEA model for TCIS efficiency evaluation in using railway capacity could be applied to an overall network or for separate parts of railway lines.

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Importance of E‐Maintenance for Railways Logistic

Laraib

2024

Cybersecurity in the Transportation Industry

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A new fuzzy approach to identify the critical risk factors in maintenance management

Cited by 38 publications

References 101 publications

Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework

Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework

Application of Multicriteria Decision-Making Methods in Railway Engineering: A Case Study of Train Control Information Systems (TCIS)

Importance of E‐Maintenance for Railways Logistic

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