Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

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A NOVEL HYBRID METHOD FOR NON-TRADITIONAL MACHINING PROCESS SELECTION USING FACTOR RELATIONSHIP AND MULTI-ATTRIBUTIVE BORDER APPROXIMATION METHOD

Selection of the most appropriate non-traditional machining process (NTMP) for a definite machining requirement can be observed as a multi-criteria decision-making (MCDM) problem with conflicting criteria. This paper proposes a novel hybrid method encompassing factor relationship (FARE) and multi-attributive border approximation area comparison (MABAC) methods for selection and evaluation of NTMPs. The application of FARE method is pioneered in NTMP assessment domain to estimate criteria weights. It significantly condenses the problem of pairwise comparisons for estimating criteria weights in MCDM environment. In order to analyze and rank different NTMPs in accordance with their performance and technical properties, MABAC method is applied. Computational procedure of FARE-MABAC hybrid model is demonstrated while solving an NTMP selection problem for drilling cylindrical through holes on non-conductive ceramic materials. The results achieved by FARE-MABAC method exactly corroborate with those obtained by the past researchers which validate the usefulness of this method while solving complex NTMP selection problems

A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing

© 2019 Institution of Chemical Engineers Modern manufacturing organizations have started giving paramount importance to sustainable aspects of the manufacturing processes, realizingnot only that the natural resources are dwindling rapidly but also that they bear significant responsibility to the society and surroundings for the overall future development. Catastrophic failures and the maintenance of complex equipment can generate a large amount of hazardous waste within the organization that can affect the overall production level, environment, along with impacting the health of workers in the long run. Failure mode and effect analysis (FMEA) is an efficient risk analysis tool for processes, products, designs or services and has been adopted by different types of organizations. In this paper, for the first time in the literature, the consequences of failure modes of industrial equipment are considered from the sustainable point of view, which is believed to be a requirement for the establishment of a successful sustainable manufacturing strategy. Severities of failure modes are considered from environmental, societal and economic points of view, along with the chances of occurrences and detections. However, due to lack of exact data, these risk factors are evaluated linguistically by cross-functional experts, which made the situation complex. To properly prioritize the failure modes according to their risk levels, a novel hybrid Multi-Criteria Group Decision Making (MCGDM) approach by integrating Interval Type-2 Fuzzy Decision-Making Trial and Evaluation Laboratory (IT2F-DEMATEL) and Modified Fuzzy Multi-Attribute Ideal Real Comparative Analysis (Modified FMAIRCA) methods is proposed. Calculating the causal dependencies among the risk factors and finding out their relative importance are the twofold benefits of the IT2F-DEMATEL approach. Defuzzified criteria weights are further utilized in the proposed modified FMAIRCA approach for risk ranking of failure modes. The effectiveness of the proposed hybrid approach is demonstrated by considering a case-study from a process plant gearbox. Next, the obtained ranking results are compared with the results obtained from other commonly applied fuzzy MCDM methods in the FMEA domain. Stability and robustness of the proposed approach is also highlighted by performing sensitivity analysis

An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA

© 2019 Elsevier Ltd Failure mode and effect analysis (FMEA) is a proactive risk assessment technique, which has been widely used by engineers to meet the safety and reliability requirements of processes, products, structures, services, and systems. The major aim of the FMEA technique is to rank the failure modes according to their risk levels and subsequent actions are performed to eliminate/mitigate their consequences. In a typical FMEA, for each failure mode, three risk factors, namely severity (S), occurrence (O) and detection (D) are evaluated and a risk priority number (RPN) is estimated by multiplying these risk factors. In recent years a significant effort has been underway and different approaches have been proposed to improve FMEA, to overcome its several drawbacks. We notice that there is a significant amount of literature based on multi-criteria decision making (MCDM) methods, which have been solely aimed to improve the risk estimation process in FMEA by overcoming the drawbacks of the traditional FMEA technique. In this work, we propose a novel integrated MCDM approach by combining Fuzzy Analytical Hierarchy Process (FAHP) with the modified Fuzzy Multi-Attribute Ideal Real Comparative Analysis (modified FMAIRCA). At first, we calculate the fuzzy relative importance between the risk factors by using the FAHP method and then we use those importance values in our proposed modified FMAIRCA to rank the failure modes according to their risk level. Our modified FMAIRCA method is computationally inexpensive and is able to provide more viable decisions. We consider a benchmark example in FMEA domain to validate the ability of our integrated approach and highlight the usefulness of the same. Further, we compare the ranking result with other MCDM methods - FVIKOR, FCOPRAS, FMOORA, FMABAC, FTOPSIS and sensitivity analysis is also performed to highlight the robustness of the proposed approach