Extending a pessimistic–optimistic fuzzy information axiom based approach considering acceptable risk: Application in the selection of maintenance strategy

Abstract

Maintenance is considered as an important factor in the improvement of machine performance. Indeed, maintenance plays an important role in maintaining reliability, availability, quality of products, reducing risk, improving efficiency, and safety. In maintenance problems, the desired real data cannot easily be found, thus decision making by applying expert knowledge is the only way. However, due to the existence of uncertainties in these assessments, the accuracy of evaluations may be questioned. The aim of this study was to present an appropriate mathematical model for decision making in the assessment and selection of proper maintenance strategy in risky situations. For this purpose, a model based on fuzzy axiomatic design (FAD) is presented, wherein each evaluation has both optimistic and pessimistic fuzzy scores, as the fuzzy evaluations themselves have risks. In order to improve the accuracy of the presented method, a new concept called “acceptable risk” has been suggested. A real case study, to measure the effectiveness of the proposed model, is conducted in a rolling mill company and the obtained results are compared with other FAD concepts.