MAINTENANCE STRATEGY SELECTION OF HYDRAULIC SYSTEMS IN THE STEEL INDUSTRY: A DESIGN SCIENCE RESEARCH APPROACH

Determination of a plant maintenance strategy in a manufacturing plant is a crucial process. The appropriateness of the adopted maintenance strategy will directly and indirectly affect the plant manufacturing cost. Analytical Hierarchy Process (AHP) offers as an alternative instrument to cater the decision-making problem. However, in a higher critical condition, AHP analysis as only one method is insufficient for a concrete decision making. This paper explores and extends the methodology and results of a research study which utilizes Fuzzy-AHP and TOPSIS-AHP. The objective of this research is to select the best maintenance management method between corrective maintenance (CM), predictive maintenance (PDM) and condition-based maintenance (CBM) via methodologies. Fuzzy-AHP is one popular decision-making instrument which has the ability to capture the uncertainty in judgement. TOPSIS-AHP is another simple and powerful alternative instrument to solve multi-criteria decision making (MCDM) problem. It is concluded that condition-based maintenance (CBM) strategy is the best plant maintenance strategy using all the MCDM methods. For future study, other MCDM instrument such as Preference Ranking Organization Method (PROMETHEE) can be explored, and compared.KeywordsMulti-criteria decision makingFuzzy analytical hierarchy processMaintenance strategy selectionPairwise comparisonPlant maintenance strategy development

The growth of world-class manufacturing companies and global competition caused significant changes in the manufacturing companies operations. These changes have affected maintenance and made its role even more crucial to stay ahead of the competition. Maintenance strategy selection is one of the strategic decision-making issues that manufacturing companies in the current competitive world are facing. In this paper, a comparison between different Multiple Criteria Decision Making (MCDM) approaches is conducted in a dairy manufacturing factory to rank the maintenance strategies. The aim is to suggest an appropriate approach for the best selection of the maintenance strategy. The decision-making elements including evaluation criteria/sub-criteria and problem alternatives, i.e., maintenance strategies are determined and a group of experts from the case-study factory are asked to make their pair-wise comparisons. The pair-wise comparison matrix is constructed by using the crisp and triangular fuzzy numbers, while the aggregation of individual priorities (AIP) approach is utilized to aggregate the decision-makers' judgments. The priority vectors of decision elements are calculated by Mikhailov's fuzzy preference programming (FPP) methods and the final weights of the decision elements are found. Results show that when the effectiveness of one element on the other elements is higher, it will have greater weights; and therefore, the results from the analytic network process (ANP) method is completely different from those of the analytic hierarchy process (AHP). The reason for the differences between the AHP and Fuzzy AHP (FAHP) with the ANP and Fuzzy ANP (FANP) is that both AHP and FAHP evaluate the criteria only based on the level of importance and do not consider the interdependencies and interactions among the evaluation elements. In this research, a predictive maintenance is selected as the most appropriate strategy in the case company and the preventive strategies outperformed the corrective strategies. The results of this research are consistent with the results of previous studies found in the literature.

Managers face with the problem of decision-making for selecting suitable maintenance strategy because of the emergence of different maintenance strategies for systems and equipments. Considering implementation methods and strengths and weaknesses of each maintenance strategy, simultaneous employment of these strategies may result in improvement or reduction of organisational performance. The main purpose of this paper is to consider interdependency of maintenance strategies to find the most suitable maintenance strategy for equipments. While the problem of selecting a suitable maintenance strategy can be solved by multi-criteria decision-making, the approach of analytic network process (ANP) has been suggested due to its network structure and its capability in counting the interdependency of maintenance strategies. As a case study, an attempt has been made to propose the most suitable maintenance strategies for a category of equipments in Chadormalu Mining-Industrial Company by the ANP approach. The findings imply that the priorities of maintenance strategies include TPM, CBM, DOM, TBM, EM, respectively. Also, maintainability and reliability have been found as the main reasons of higher rankings of TPM and CBM strategies.

Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process

PurposeDesign science research (DSR) is a structured approach for solving complex ill-structured problems in organizations through the development of an artefact followed by its validation. This paper aims to evaluate existing DSR methodology and propose specific accents to promote DSR for environmental, social and governance (ESG)-oriented operational excellence (OPEX) initiatives within organizations.Design/methodology/approachThis commentary paper is based on an abductive reasoning approach to evaluate and understand DSR and assess its effectiveness for developing solutions to typical ESG-oriented OPEX-based problems within organizations.FindingsExisting literature on DSR is reviewed, after which it is evaluated on its ability to contribute to the implementation of sustainable solutions for ESG-oriented OPEX-based problems. Based on the review, specific DSR methodological accents are proposed for the development of ESG-oriented OPEX-based solutions in organizations.Research limitations/implicationsThis conceptual paper contributes to the conceptual understanding of the applicability, limitations and contextual preconditions for applying DSR. This paper proposes an explicit and, in some ways, alternative view on DSR research for OPEX researchers to apply and further the body of knowledge on matters of sustainability (ESG) in operations management.Practical implicationsCurrently, there is limited understanding and application of the DSR methodology for OPEX-based problem-solving initiatives, as appears in the scant literature on DSR applied for the implementation of OPEX based initiatives for ESG purposes. This paper aims to challenge and provide accents for DSR applied to OPEX-related problems by means of a DSR framework and thereby promotes intervention-based studies among researchers.Originality/valueThe proposed step-by-step methodology contains novel elements and is expected to be of help for OPEX-oriented academicians and practitioners in implementing DSR methodology for practical related problems which need research interventions from academics from Higher Education Institutions.

The selection of a maintenance strategy is a decision often made with uncertainty or subjectivity. This decision involves the prioritization of critical factors since there are several factors to be considered simultaneously. Decision-making generally depends on subjective assessments from experts. To deal with multiple factors, Analytic Hierarchy Processes (AHP) is a well-established multiple criteria decision analysis (MCDA) method. This article presents an AHP application for the selection of a maintenance strategy by a real industrial plant. Four maintenance strategies are considered: Corrective Maintenance, Preventive Maintenance, Predictive Maintenance, and Proactive Maintenance. Decision criteria are cost, quality, safety, value added and viability. Then, incorporating the concepts of the fuzzy set theory, fuzzy AHP was applied to the same decision problem. In both applications, Corrective Maintenance was the strategy with the highest priority, and value added was the highest priority criterion. With the classical AHP application, some comparison matrices produced Consistency Ratios (CR) greater than 0.10, possibly generated by mistakes or misunderstandings from experts. However, the same result was obtained from fuzzy AHP and validated the result obtained from classical AHP application. The major contribution of the paper is the evidence that Fuzzy AHP may be a useful tool to solve the consistency problems in classical AHP applications.

Maintenance Strategy Selection: a comparison between Fuzzy Logic and Analytic Hierarchy Process

An appropriate maintenance strategy can improve the availability and reliability levels of industries, while improper maintenance strategy can significantly reduce the effectiveness of companies. This paper aims to select the optimal maintenance strategy utilizing four decision-making techniques in a food company in Turkey. In this study, four multi-criteria decision making (MCDM) methods (Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW) and Weighted Product (WP)) are used to determine the optimal maintenance strategy. In this context, four main criteria (safety, cost, reliability, and added-value), twelve criteria and five alternatives (corrective maintenance, time-based preventive maintenance, opportunistic maintenance, condition-based maintenance, and predictive maintenance) are defined according to focus group meetings in the company and the literature review. The obtained results are compared with each other, and then the appropriate maintenance strategies are identified.

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.

Decision-making is a highly researched topic and various methods have been developed to facilitate a decision-maker (DM) in choosing the best alternative. Saaty's analytic hierarchy process (AHP) has been very popular since 1977 and has been adapted all over the world. However, AHP is a highly-debated topic. Technique for order of preference by similarity to ideal solution (TOPSIS) is another multi-criteria decision-making (MCDM) method developed by Hwang and Yoon in 1981 as a ranking method. This research is focused on identifying which is the MCDM method between AHP and TOPSIS. Since TOPSIS is a ranking method, the authors propose to combine AHP and TOPSIS methods and determine which method's ranking (AHP, AHP-TOPSIS combination, and TOPSIS with equal weights) aligns more closely with the DM's initial preference. Moreover, this research states the efficiency of the method by comparing the time it takes to make a decision and its reliability.

Maintenance plays a key role in oil and gas enterprises, especially in the process of increasing pressure to improve equipment efficiency, reduce costs, and comply with environmental protection requirements towards sustainable production. This study proposes an optimal maintenance strategy based on the overall equipment effectiveness (OEE) index, using a multi-criteria decision-making method (MCDM) integrating an Analytical Hierarchy Process (AHP) and a Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS). The study evaluates five maintenance strategies—preventive maintenance (PM), risk-based maintenance (RBM), condition-based maintenance (CBM), reliability-centered maintenance (RCM), and predictive maintenance (PdM)—based on four key criteria: maintenance cost, safety, efficiency, and flexibility. The comparison of each pair of criteria and the maintenance strategy choices was carried out systematically to ensure consistency in the decision-making process. The Evaluation Distance to the Mean Solution (EDAS) method was used as a cross-validation tool to strengthen the reliability of the results. The results showed that RCM is the optimal maintenance strategy, providing superior equipment performance and reliability. The study expands the theoretical basis in industrial maintenance, providing a structured and data-driven decision support tool. The method can be flexibly applied in many industries to optimize maintenance strategies and promote sustainable production.

Optimality of flood influencing factors for flood hazard mapping: An evaluation of two multi-criteria decision-making methods

PurposeThe purpose of this study is to evaluate maintenance strategies based on fuzzy decision-making trial evaluation and laboratory (DEMATEL) and fuzzy analytic network process (ANP) in the petrochemical industry.Design/methodology/approachThis study proposes a hybrid-structured multi-criteria decision-making (MCDM) method based on fuzzy Delphi, fuzzy DEMATEL and fuzzy ANP as a structured methodology to assist decision makers in strategic maintenance. The fuzzy Delphi method (FDM) is applied to refine the effective criteria, fuzzy DEMATEL is applied for defining the direction and relationships between criteria and Fuzzy ANP is used for the selection of optimized maintenance strategy.FindingsThe results identify “strategic management complexity” as the top criterion. The predictive maintenance (PdM) with the highest priority is the best strategy. It is followed by reliability-centered (RCM), condition-based (CBM), total productive (TPM), predictive (PM) and corrective maintenance (CM).Originality/valueToday, companies act in an atmosphere that is known with the features of uncertainty. In this atmosphere, only those companies can survive that have a strategy based on presenting the quality services and products to their customers. Similarly, maintenance as a system plays a vital role in availability and the quality of products, which creates value for customers. The selection of maintenance strategy is a kind of MCDM problem, which includes consideration of different factors. This article considers a broad category of alternates, including CM, PM, TPM, CBM, RCM and PdM.

Multicriteria decision analysis (MCDA) problems (also known as multicriteria decision-making or MCDM) involve the ranking of a finite set of alternatives in terms of a finite number of decision criteria. Often times such criteria may be in conflict with each other. That is, an MCDA problem may involve both benefit and cost criteria at the same time. Although this is a frequent characteristic of many real-life MCDA problems, this subject has not received adequate attention in the literature. This paper examines the use of four key MCDA methods when two approaches for dealing with conflicting criteria are used. The two approaches are the benefit to cost ratio approach and the benefit minus cost approach. The MCDA methods used in this study are the weighted sum model, the weighted product model, and the analytic hierarchy process (AHP) along with some of its variants, including the multiplicative AHP. Not surprisingly, these two approaches for aggregating conflicting criteria may result in a different indication of the best alternative or ranking of all alternatives when they are used on the same problem. As it is demonstrated here, it is also possible for the two approaches to even result in the opposite ranking of the alternatives. An extensive empirical analysis of this methodological problem revealed that the previous phenomena might occur frequently on simulated MCDA problems. The WSM, the AHP, and the revised AHP performed in an almost identical manner in these tests. The contradiction rates in these tests were rather significant and became more dramatic when the number of alternatives was high. Although it may not be possible to know which ranking is the "correct" one, this study also theoretically proved that the multiplicative AHP is immune to these ranking inconsistencies.

PurposeThe purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection problem across multiple problem domains. The domains are energy generation, logistics, public services and retail facilities. This study aims to answer the following research questions: Which evaluating criteria were used for each site selection problem domain? Which MCDM methods were frequently applied in a particular site selection problem domain?Design/methodology/approachThe goals of the systematic review were to identify the evaluating criteria as well as the MCDM method used for each problem domain. A total of 81 recent papers (2014–2018) including 32 papers published in conference proceedings and 49 journal articles from various databases including IEEE Xplore, PubMed, Springer, Taylor and Francis as well as ScienceDirect were evaluated.FindingsThis study has shown that site selection for energy generation facilities is the most active site selection problem domain, and that the analytic hierarchy process (AHP) method is the most commonly used MCDM method for site selection. For energy generation, the criteria which were most used were geographical elements, land use, cost and environmental impact. For logistics, frequently used criteria were geographical elements and distance, while for public services population density, supply and demand, geographical layout and cost were the criteria most used. Criteria useful for retail facilities were the size (space) of the store, demographics of the site, the site characteristics and rental of the site (cost).Research limitations/implicationsThis study is limited to reviewing papers which were published in the years 2014–2018 only, and only covers the domains of energy generation, logistics, public services and retail facilities.Practical implicationsMCDM is a viable tool to be used for solving the site selection problem across the domains of energy generation, logistics, public services and retail facilities. The usage of MCDM continues to be relevant as a complement to machine learning, even as data originating from embedded IoT devices in built environments becomes increasingly Big Data like.Originality/valuePrevious systematic review studies for MDCM and built environments have either focused on studying the MCDM techniques itself, or have focused on the application of MCDM for site selection in a single problem domain. In this study, a critical review of MCDM techniques used for site selection as well as the critical criteria used during the MCDM process of site selection was performed on four different built environment domains.