scholarly journals Maintenance strategies: Decision Making Grid vs Jack-Knife Diagram

2018 ◽  
Vol 24 (1) ◽  
pp. 61-78 ◽  
Author(s):  
Turuna Seecharan ◽  
Ashraf Labib ◽  
Andrew Jardine

Purpose Maintenance management is a vital strategic task given the increasing demand on sustained availability of machines. Machine performance depends primarily on frequency and downtime; therefore, ranking critical machines based on these two criteria is important to determine the appropriate maintenance strategy. The purpose of this paper is to compare two methods, using case studies, to allocate maintenance strategies while prioritising performance based on frequency and downtime or Mean Time to Repair: the Decision Making Grid (DMG) and Jack-Knife Diagram (JKD). Design/methodology/approach The literature indicates the need for an approach able to integrate maintenance performance and strategy in order to adapt existing data on equipment failures and to routinely adjust preventive measures. Maintenance strategies are incomparable; one strategy should not be applied to all machines, nor all strategies to the same machine. Findings Compared to the Pareto histogram, the DMG and JKD provide visual representations of the performance of the worst machines with respect to frequency and downtime, thus allowing maintenance technicians to apply the appropriate maintenance strategy. Each method has its own merits. Research limitations/implications This work compares only two methods based on their original conceptualisation. This is due to their similarities in using same input data and their main features. However, there is a scope to compare to other methods or variations of these methods. Practical implications This paper highlights how the DMG and JKD can be incorporated in industrial applications to allocate appropriate maintenance strategy and track machine performance over time. Originality/value Neither DMG nor JKD have been compared in the literature. Currently, the JKD has been used to rank machines, and the DMG has been used to determine maintenance strategies.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asghar Aghaee ◽  
Milad Aghaee ◽  
Mohammad Reza Fathi ◽  
Shirin Shoa'bin ◽  
Seyed Mohammad Sobhani

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.


2012 ◽  
Vol 18 (1) ◽  
pp. 16-29 ◽  
Author(s):  
Selim Zaim ◽  
Ali Turkyılmaz ◽  
Mehmet F. Acar ◽  
Umar Al‐Turki ◽  
Omer F. Demirel

PurposeThe purpose of this paper is to demonstrate the use of two general purpose decision‐making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements.Design/methodology/approachThe Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey.FindingsThe two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise.Practical implicationsThe techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step‐by‐step approach for easier adaptation by practitioners in all types of organizations.Originality/valueThe value of the paper is in applying AHP and ANP decision‐making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amitkumar Patil ◽  
Gunjan Soni ◽  
Anuj Prakash ◽  
Kritika Karwasra

PurposeIn today's competitive industries, the selection of best suitable maintenance strategy is dependent on large number of quantitative and qualitative factors, and it becomes an extensively difficult problem for maintenance engineers. Over the years, a diverse range of solution methodologies have been developed for solving this multi-criteria decision-making (MCDM) problem. In this paper, the authors have presented a comprehensive review of latest maintenance strategy paradigms and solution approaches proposed for the selection of an appropriate strategy in various industries. It would provide a systematic mapping of developments in this field and identify some research gaps to explore further studies.Design/methodology/approachA systematic state-of-the-art comprehensive literature review on maintenance strategy paradigms and selection approaches is presented in this study. In this study, 87 research articles published in peer-reviewed journals, since year 2012, are reviewed.FindingsFor the selection of a suitable maintenance strategy, a variety of criteria are considered to better evaluate the alternatives. In this study, contemporary strategies are discussed, and their applications in different industries are also depicted. Moreover, through the analysis of extant literature, critical criteria are selected and classified in six major categories (namely, economic, technical, safety, environmental, feasibility and social) and further sub-categorized in quantitative and qualitative classes. These clusters of criteria can be helpful as an initial set of criteria for survey and then case- or industry-specific criteria can be shortlisted for further alternative evaluation.Practical implicationsFrom the perspective of maintenance managers, maintenance management can be a very difficult task, considering the numerous factors affecting the decision-making process. In order to help in the decision-making process, this study presents the contemporary maintenance strategies in a systematic manner. In a previous study (Kothamasu et al., 2006), these strategies were classified into repair and prevent classes only. With the developments of autonomous maintenance and design out maintenance (DOM), it was fair to include continuous improvement class. It will help managers and practitioners to identify, according to organization policy, appropriate maintenance strategy alternatives for the asset. A benchmark set of state-of-the-art maintenance strategies are laid out with their applications. The industrial case studies discussed in this study summarizes the optimal maintenance strategies for respective industries. Also, most critical criteria are identified from the existing studies for various industries that can help maintenance practitioners in acknowledging the critical factors and making appropriate decisions. Evaluation parameters for the maintenance strategy selection (MSS) generally conflict with each other, and considering the difficulty of quantifying the qualitative measures, it is a challenging task to determine the optimal trade-off. In order to overcome these challenges, popular MCDM approaches, demonstrating effective results across different industries are discussed with their limitations and applications. Decision-makers can refer this study to identify best suitable decision-making technique for the MSS problem in the industry of their choice. Maintenance managers and engineers can refer the case studies illustrated in Tables 1 and 2 to analyse the MSS techniques proposed by previous studies with industry-specific applications.Social implicationsThis study is an attempt to provide a reference point for research scholars interested in the field of maintenance management and/or development of maintenance strategy framework. This study provides a critical state-of-the-art review of efforts made in the field of MSS. The prominent maintenance strategies being implemented in contemporary industries are discussed with respective case studies. Interested researchers and academicians can familiarize themselves with these strategies and their distinct features in this study. In order to guide future studies and provide a reference point for academicians, MSS critical criteria used in extant literature are identified and classified into a comprehensive benchmark framework. Moreover, the industrial case studies are discussed with the most critical criteria of MSS for different industries and which strategy is most suitable for the respective industries based on these criteria. Table 1 presents different MCDM techniques and their hybrid applications for solving MSS problem that can help researchers in identifying research gaps. Future research can be directed at addressing the limitation of MCDM approach employed in existing studies and comparing the differences in results obtained by the proposed approach. Different industrial case studies with considered maintenance strategy alternatives are presented in Table 2, which can help researchers in identifying the industries that have not been studied yet. Moreover, not all of the existing studies are carried out by considering all the presented benchmark strategies, which can be addressed in future studies by interested researchers. More detailed discussion on research gaps is presented in the following section.Originality/valueFrom the analysis of the extant literature, the authors could observe that the decision-making process adopted in numerous studies was limited to the classical maintenance strategies and not inclusive of aggressive maintenance strategy alternatives. To overcome these limitations and help maintenance managers in the decision-making, this study depicts the contemporary maintenance strategies, critical evaluation criteria and MCDM frameworks (employed to solve the MSS problem with industrial case studies) in a structured manner.


2015 ◽  
Vol 32 (7) ◽  
pp. 763-782 ◽  
Author(s):  
Hu-Chen Liu ◽  
Jian-Xin You ◽  
Xue-Feng Ding ◽  
Qiang Su

Purpose – The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes. Design/methodology/approach – A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes. Findings – A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies. Practical implications – The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method. Originality/value – This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.


2018 ◽  
Vol 24 (2) ◽  
pp. 152-169 ◽  
Author(s):  
Alberto Martinetti ◽  
Erik Jan Schakel ◽  
Leo A.M. van Dongen

Purpose The purpose of this paper is to create a framework to provide a scalable maintenance program for unmanned aircraft systems (UAS) in order to choose the most suitable and feasible maintenance strategy in terms of reliability. Design/methodology/approach The paper opted for a reliability-centered maintenance-based approach to develop the framework using a UAS as the starting point of the research. A linear and user-friendly design of the methodology based on a Boolean flowchart was chosen in order to lead the analyst through the process avoiding as much as possible subjectivity decision-making issues. Finally, the framework was, on the component level, performed by a UAS company gathering feedback on its applicability. Findings An agile and structured decision-making framework for developing scalable maintenance program of UAS is provided. The proposed solution gives the opportunity to tailor the maintenance strategy to the technical characteristics, considering not only the single component but also situations and conditions in which the machine will operate. Research limitations/implications Because of the chosen research approach, the framework is potentially applicable to every UAS. A first trial of the method was run on a multirotor vehicle equipped with eight electric brushless motors. Further studies focused on different UAS will be mandatory in order to obtain comparable and robust findings and a reliable approach. Practical implications This study offers a different scheme to elaborate a specific maintenance solution related to the characteristics of the system. It strives to remedy the drawbacks of the traditional approach for a manned aircraft not completely suitable for systems with such different functions, features and tasks. The authors believe that the method presented in this paper will provide a new selection tool for choosing maintenance actions based on the features of the UAS. Originality/value This paper provides a new and usable solution to include the maintenance actions in the management of pioneering products. In spite of the maintenance program representing an essential aspect to provide reliable assets, frameworks to create programs and to help manufacturers and users are still difficult to find or to apply to different UAS. This gap enhances the misunderstanding that the maintenance is not required or essential for the unmanned aircrafts management.


2019 ◽  
Vol 26 (4) ◽  
pp. 509-525
Author(s):  
Mary C. Kurian ◽  
Shalij P.R. ◽  
Pramod V.R.

Purpose The purpose of this paper is to demonstrate the application of analytic network process (ANP) as a methodology to make multiple criteria decision in selecting the most appropriate maintenance strategy for organizations with critical manufacturing requirements. Design/methodology/approach Maintenance strategy selection problems are multiple criteria decision making (MCDM) problems which consist of many qualitative and quantitative characteristics. For solving MCDM problems, the ANP is highly recommended as it considers the interdependent influences among and between the various levels of decision attributes. In this research paper, the ANP method is used to select the optimum maintenance strategy in a cement industry in India. Findings The ANP method can be used as an effective tool for the evaluation of possible alternatives in maintenance strategy decision problems by considering the dependency among the strategic factors. Research limitations/implications As illustrated in this paper, ANP method can also be used in other industries for adopting the optimum maintenance strategy to enhance the business performance by decreasing the losses associated with equipment effectiveness. Practical implications The major contribution of this research is the successful development of the comprehensive ANP model for the cement plant. ANP model incorporates diversified variables of the cement plant supply chain and includes their interdependencies. The proposed ANP model in this paper, not only guides the decision makers in the selection of the best services but also enables them to visualize the impact of various criteria in the arrival of the final solution. Social implications The model can be extended to certain other manufacturing sectors as the future scope of research and may assist in obtaining a clear idea regarding the status of current maintenance strategies. It should be carried out with a larger number of firms in India focusing on small and medium firms to confirm these results and reinforce their applicability to these kinds of firms. Studies of such a nature would help in identifying successful organizational factors or successful maintenance practices that lead to superior performance. Originality/value This paper explores the value of implementing ANP as a decision making method in maintenance strategy, which is currently not a prevalent method.


Facilities ◽  
2019 ◽  
Vol 38 (5/6) ◽  
pp. 421-444
Author(s):  
Hector Martin ◽  
Fey Mohammed ◽  
Kevin Lal ◽  
Shannon Ramoutar

Purpose There are limited studies addressing how choosing a maintenance strategy can contribute towards maximising outputs from given inputs, thereby minimising costs and improving a company’s competitiveness. The analytic hierarchy constant sum method (AHCSM) is used to access the appropriateness of maintenance strategies for improving the overall efficiency of a structural steel fabrication construction company. Design/methodology/approach A semi-structured interview was formulated with the stakeholders of the quality department to understand the company’s maintenance portfolio and its current functional capability. The information from this case study was then dissected to represent the factors that the company deemed appropriate for evaluating their maintenance strategy. The AHCSM approach provided a framework, which ranked the importance of factors that are sensitive to the construction industry and rank the suitability of maintenance strategies. Findings Factors affecting the selection of maintenance strategies to improve business efficiency are productivity, quality, reliability, cost, safety and work environment, morale, inventory and flexibility. Total productive maintenance strategy produces the most desirable outcome; however, the predictive or condition-based maintenance strategy provides an optimum solution for the case study company while considering the equipment usage, frequency of production and the current economic climate. Originality/value The approach presented allows practitioners to consider ways to increase the level of production and improve the efficiency of construction businesses without a high increase in investment. The findings can inform gaps in existing maintenance approaches in achieving business objectives.


2016 ◽  
Vol 7 (3) ◽  
pp. 51-69 ◽  
Author(s):  
Malek Tajadod ◽  
Mohammadali Abedini ◽  
Ali Rategari ◽  
Mohammadsadegh Mobin

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdul Kareem Abdul Jawwad ◽  
Ibrahim AbuNaffa

PurposeThe purpose of this paper is to help newly established plants with minimal or no historical machine data select best maintenance strategies that suit their specific working setup and at the same time satisfy relevant selection criteria.Design/methodology/approachAnalytical hierarchy process (AHP) was applied successfully in this study to select the maintenance strategy at a newly established chemical fertilizers plant. Implementation started by identifying main and sub-criteria pertinent to maintenance practice in this particular industry. Pair-wise comparisons and consistency calculations were carried out on the chosen criteria and then were used to assess candidate maintenance strategies through a special scoring process. The methodology included the use of surveys, brainstorming and expert consultation.FindingsThe results have shown that the most important main criteria are cost, resources, failures, management, operations, quality and safety. The final maintenance strategy selected for the plant under consideration included a mix of condition-based predictive maintenance (PDM), time-based preventive maintenance (PM) and corrective maintenance (CM). The best balance between the three maintenance activities, which satisfies the maintenance criteria with technical applicability, was found to be 50, 23 and 19% for PDM, PM and CM, respectively.Originality/valueThe present paper is a novel application of AHP coupled with deterministic application-specific ranking for devising a procedure for selecting viable and applicable comprehensive maintenance strategies for newly established chemical fertilizers plants with no historical data on machine failures.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hafed Touahar ◽  
Nouara Ouazraoui ◽  
Nor El Houda Khanfri ◽  
Mourad Korichi ◽  
Bilal Bachi ◽  
...  

PurposeThe main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).Design/methodology/approachThe optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).FindingsA case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.Originality/valueThe maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.


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