| The Failure Modes,Effects and Criticality Analysis(FMECA)method is an engineering technology of recognizing,identifying,and eliminating known or potential failures,invalidations,errors,problems,and so on that exist in systems,designs,processes,and services before selling the product to the customer.The technology is used in the early stages of systems,design,processes and services,taking advantage of the existing valid data,historical documentation,and the expertise and experience of FMECA team members from various related field.Failure mode lookup and analysis before the risk occurs,which has resulted in a special application environment for the FMECA method-a highly uncertain analytical environment,including the ambiguities caused by inability to obtain all valid data;the vagueness and uncertainty between expert members caused by the complex and diverse background of the FMECA team members;and the vagueness and uncertainty of FMECA team members' judgment on failure mode.This complex uncertainty inevitably gives rise to the distortion and inaccuracies of the FMECA quantification analysis.Under the background of this application,this paper put forward a interval type-2 trapezoidal fuzzy FMECA method which can quantify the vagueness and uncertainty and improve the accuracy and validity of the quantitative analysis of FMECA method.Specific research methods and the main research results are as follows:(1)To build a quantitative model of vagueness and uncertainty information.First of all,taking the interval number which is in keeping with the human thinking and judgment ability,and quantizing vagueness and uncertainty data roughly,as the initial individual judgment information.Then,by accumulating and stacking this group of interval number given by the FMECA team members,finding the judgment interval expressing the highest degree of membership as the group judgment true value.Meanwhile taking into account the difference of data,which records intra-personal uncertainty and inter-personal uncertainty.Ultimately,computing the interval type-2 trapezoidal fuzzy group decision value which recording the consensus and differences of the team's determine,and the value is taken as the risk factor evaluation data for further FMECA analysis.(2)Proposed a interval type-2 trapezoidal fuzzy comprehensive comparison sorting method.By dividing the interval type-2 trapezoidal fuzzy membership function into two parts and compared from this two parts:one part is the actual value of the interval type-2 trapezoidal fuzzy number,that is the highest part of membership degree,and their comparison is made by the method of center of gravity;the other part is the vagueness and uncertainty part of the interval type-2 trapezoidal fuzzy number,that is the lower and decentralized part of membership degree,and constructing discrete parts comparison method based on the relative geometric space size and position of the membership function to compare their value.Integrating the compared results of these two parts and recording into different orders of magnitude,so that the comparison result not only retains the validity of the actual value of the interval type-2 trapezoidal fuzzy number but also fully considers the influence of the vagueness and uncertainty degree on the interval type-2 trapezoidal fuzzy number.(3)Proposed a interval type-2 trapezoidal fuzzy FMECA method.Through the construction of fuzzy information quantization model,we deal with vagueness and uncertainty in qualitative analysis of FMECA method and aggregated into group judgment evaluation data.Again by interval type-2 trapezoidal fuzzy comprehensive comparison method,from the two parts to compare the risk factor group evaluation values.Finally,according to the risk priority number(RPN)calculated value of the interval type-2 trapezoidal fuzzy FMECA method to find the failure mode with high risk and high priority,and completing the whole interval type-2 trapezoidal fuzzy FMECA method. |
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