Fault Mode Risk Assessment Of Machining Center Based On Interval 2-Tuple Linguistic

This paper considers the inaccuracy,uncertainty and incompleteness of the linguistic term set in group decision-making with FMEA due to the differences in members' educational background,Knowledge Fields Involved and individual preferences,a fault mode risk assessment method based on interval 2-tuple linguistic variables is proposed.And a series of domestic machining centers are taken as the research object to analyze the reliability and identify the weak links,it is of great significance to carry out the reliability design and make the maintenance strategy.Firstly,the fault mode of machining center is divided,and the collected fault data is subdivided and counted according to the divided fault mode classification.FMEA team members then perform a semantic assessment of the classified failure data information.FMEA team members can be evaluated using a familiar set of semantic terms based on their professional background and personal preferences,which can vary in granularity.Then use the interval 2-tuple linguistic variables processing to evaluate the results of FMEA members using different granularity of semantic term sets.Secondly,the weight of the experts is defined.Considering the experts' varying degrees of familiarity with each failure mode and their degree of daily exposure,the dynamic weight of experts is determined based on the proximity of evaluation information among experts,the similarity of evaluation information between experts and groups,and the discrimination degree of evaluation information of experts themselves.Then,based on the idea of weighted value,the expert weight is used to determine the evaluation result of the risk factor of the failure mode of machining center.Thirdly,the subjective weight of risk factors is determined based on the 2-tuple linguistic variables weighting method according to the expert weight and the result of the expert's subjective relative weight.Based on the evaluation result of the risk factor of the machining center failure mode,the objective weight of the risk factor is determined according to the concept of similarity.The combination of subjective and objective weight is used to determine the weight of failure mode risk factors.Finally,based on the idea of interval 2-tuple hybrid weighted distance,the interval binary semantic synthesis distance between the fault mode of the machining center and the reference Semantic Group is obtained by introducing the calculated risk factor weight.According to the calculated distance,the risk grade of failure mode is sorted,and the priority of failure mode risk of machining center is obtained.