A Combined Approach for Maintenance Strategy Selection

Pariazar, M.; Shahrabi, Jamal; Zaeri, M.S.; Parhizi, Sh.

doi:10.3923/jas.2008.4321.4329

Cited by 26 publications

(9 citation statements)

References 16 publications

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“…Bertolini and Bevilacqua (2006) proposed an integrated AHP and "Lexicographic Goal Programming (LGP)" approach to determine the best maintenance strategy for critical centrifugal pumps in an oil refinery. Pariazar et al (2008) proposed an improved AHP method using the rough set theory to eliminate the inconsistency exists in the classical AHP method. Shyjith et al (2008) proposed a combined AHP-TOPSIS method to select the most suitable maintenance strategy for a textile spinning mill ring frame unit.…”

Section: Mcdm Methodsmentioning

confidence: 99%

“…Among the reviewed publications, only Azadivar and Shu (1999) used the experimental approach to collect the data. Nine studies of Al-Najjar and Alsyouf (2003), Mechefske and Wang (2003), Alsyouf (2004), Sharma et al (2005), Zaeri et al (2007), Pariazar et al (2008), Akhshabi (2011), Sarkar et al (2011), and Ingwald and Al-Najjar (2012 utilized the observed and recorded data, three studies of Labib et al (1998a, b) and Labib (2004) used the data available in maintenance management system. The rest of publications have utilized the surveying techniques.…”

Section: Data-collecting Techniquesmentioning

confidence: 99%

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Maintenance strategy selection problem: an MCDM overview

Shafiee

2015

Journal of Quality in Maintenance Engineering

126

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Purpose – Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive review on the use and application of MCDM approach and its associated case studies in the field of MSS. Design/methodology/approach – The paper systematically classifies the published literature of both researchers and practitioners and then analyzes and reviews it methodically. Findings – This paper outlines the important issues relevant to the subject, including the techniques used for data collection, the quantitative and qualitative criteria taken into account in decision making, the maintenance strategies considered for evaluation, the methods applied to find the solution, and the type of industries being studied. In each category, the gaps are identified along with recommendations for the future research work. Practical implications – Literature on classification of the MCDM models used to select the most appropriate maintenance strategy is very limited. The proposed classification scheme not only will be useful to researchers, but also assists maintenance professionals to find the models that fit their specific needs. Originality/value – The paper provides many references in the field, including the articles published in academic journals, conference papers, master and doctoral dissertations, text books, and industrial reports, and suggests a classification scheme according to various attributes.

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Section: Mcdm Methodsmentioning

confidence: 99%

Section: Data-collecting Techniquesmentioning

confidence: 99%

Maintenance strategy selection problem: an MCDM overview

Shafiee

2015

Journal of Quality in Maintenance Engineering

126

View full text Add to dashboard Cite

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“…Apart from the literature that treats specific applications, several other studies were successfully conducted and reported in the literature and some of the include Bashiri et al [31], Bertolini and Bevilacqua [32], Fouladgar et al [33], Gaonkar et al [34], Ilangkumaran and Kumanan [35], Jafari et al [36], Pariazar et al [37], Sagar et al [38], Wang et al [39], Zaeri et al [40] and Zain et al [41].…”

Section: Introductionmentioning

confidence: 99%

A two-stage fuzzy multi-criteria approach for proactive maintenance strategy selection for manufacturing systems

Ighravwe

Oke

2020

SN Appl. Sci.

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This paper studies the use of fuzzy logic theory embedded in fuzzy axiomatic design to develop an integrated model with the analytical hierarchy process, and a selection of maintenance strategies in manufacturing systems through weighted sum-product evaluation. In this paper, an analysis was conducted to understand the model characteristics of combined fuzzy axiomatic design, analytic hierarchy process and weighted aggregated sum product assessment. The results from the analysis served as information to establish the best maintenance strategy. Based on the data obtained from a factory, which was tested on the proposed framework, it is concluded that the most preferred proactive maintenance strategy for the case study was preventive maintenance, followed by reliability-based maintenance while predictive maintenance is the least preferred maintenance strategy in the rolling mill. Accordingly, the two-stage fuzzy multi-criteria maintenance strategy selection approach is appropriate to select the best maintenance strategy for the factory. This paper offers a new method to establish the best maintenance strategy for a rolling mill. As such, the manager could install a method for significant improvement in engineering practices with promising business excellence and competitiveness results.

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“…Therefore, there are a few endeavors found to defeat these troubles. For instance, Pariazar et al [40] proposed a reception of rough set theory into AHP to take out the irregularity as often as possible existing in AHP.…”

Section: Introductionmentioning

confidence: 99%

Maintenance policy selection considering resilience engineering by a new interval-valued fuzzy decision model under uncertain conditions

et al. 2020

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Different maintenance policies, including preventive maintenance (PvM) and predictive maintenance (PdM), are introduced to enhance the execution of systems. Maintenance professional experts have faced numerous challenges with distinguishing the proper maintenance policy, among which causes of failure, accessibility, and the capability of maintenance should be regarded seriously. Moreover, most organizations do not have a deliberate and compelling model for evaluating maintenance policies under uncertainty to deal with real-world conditions. The aim of this paper is to introduce a new interval-valued fuzzy (IVF) decision model for the selection of maintenance policy based on order inclination with comparability to ideal solutions by Monte Carlo simulation. This paper introduces novel separation measures and a new IVF-distinguish index via possibilistic statistical concepts (PSCs) which can assist maintenance decision makers (DMs) to rank maintenance policy candidates. Also, resilience engineering (RE) factors are considered along with conventional evaluation criteria. Finally, the steps of the proposed IVF model-based PSCs are applied to survey a real case in manufacturing industry. Results of the presented model are compared with the recent literature and could help maintenance personnel in identifying the best policy systematically.

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A Combined Approach for Maintenance Strategy Selection

Cited by 26 publications

References 16 publications

Maintenance strategy selection problem: an MCDM overview

Maintenance strategy selection problem: an MCDM overview

A two-stage fuzzy multi-criteria approach for proactive maintenance strategy selection for manufacturing systems

Maintenance policy selection considering resilience engineering by a new interval-valued fuzzy decision model under uncertain conditions

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