عنوان مقاله [English]
One of the methods widely used by researchers to analyze the risk of maintenance operations is Failure Modes and Effects Analysis (FMEA). However, the conventional approach of the FMEA faces serious drawbacks to rank equipment and failure modes. The purpose of this paper is to dynamically rank equipment in an Interval-Valued Intuitionistic Fuzzy environment to identify critical equipment, So that the main drawbacks of the conventional FMEA are eliminated. To this end, we present the Interval-Valued Intuitionistic Fuzzy condition based dynamic weighing method (IVIF-CBDW). In following, by improving the interval-valued intuitionistic fuzzy power weight Heronian aggregation (IVIFPWHA) operator and improving the approach of multi attributive border approximation area comparison (MABAC) method, these two improved methods by Interval-Valued Intuitionistic Fuzzy condition based dynamic weighing method (IVIF-CBDW) have been merged and a robust FMEA model has been proposed in which the main drawbacks of the conventional FMEA have been eliminated. In order to prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.
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