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