Developing a novel risk-based MCDM approach based on D numbers and fuzzy information axiom and its applications in preventive maintenance planning

Maintenance in organizations plays an important role in the preservation and improvement of equipment, product quality, safety requirements, and cost reduction. There are many methods to plan and decide over a maintenance activity, among which multi-criteria decision-making (MCDM) is the well-known one. However, in many organizations, especially where limited information is available on the failure of components and equipment, it is difficult to apply quantitative models. Furthermore, the dynamic nature of maintenance and the presence of predictable and unpredictable factors that affect the reliability of equipment further complicate the process of planning. Considering the above factors, we present a novel model for preventive maintenance planning. This method employs fuzzy numbers to express reliability and take into account the associated risks and errors to analyze effective factors. This method, named as D-FAD method, is a combination of fuzzy axiomatic design and D numbers. A real case study of a part in a steel plant is presented to demonstrate the efficiency of the proposed model in different risk scenarios. The results showed that considering the risk of reliability increases the chance of other part replacement intervals to be selected. This gives decision-makers confidence and flexibility to deal with the risk of unseen events. Further, considering an interval lying between riskless and risky scenarios leads to a robust solution. (C) 2019 Elsevier B.V. All rights reserved.