Improved FMEA method based on linguistic weighted geometric operator and fuzzy priority sequence

Abstract

The invention discloses an improved FMEA method based on language weighted geometric operators and fuzzy prioritization, aiming at the problems of uncertain expert evaluation information and equivalent expert weight in traditional failure mode and effect analysis (FMEA) risk assessment methods, a method based on group language information is proposed Gathered improved FMEA method. First, regard the three major risk factors assessed by FMEA as linguistic variables, and introduce the language weighted geometry (LWG) operator to directly perform algebraic operations on the expert assessment results, overcoming the drawbacks of fuzzy theory that requires secondary conversion and loss of decision-making information; on this basis Above all, using the fuzzy priority algorithm, an expert weight calculation formula based on the consistency degree of expert ranking is proposed, and the experts who deviate from the group priority are given lower weights to reduce the impact of unfairness on the evaluation results. Taking the failure mode risk assessment of a CNC machine tool bedside box as an example, the effectiveness and practicability of the method are verified.

Description

technical field [0001] The invention relates to the improvement field of language weighted geometric operator and fuzzy priority, in particular to an improved FMEA method based on language weighted geometric operator and fuzzy priority. Background technique [0002] FMEA (Failure Mode and Effects Analysis) is a systematic and preventive reliability analysis technique. It is a systematic procedure for analyzing products or services to identify potential failure modes, failure causes and their impact on system performance. The FMEA method determines the reliability risk of different failure modes by defining and calculating the risk priority number (RPN), based on the severity (Occurrence, O), frequency of occurrence (Severity, S) and fault detection of potential failure modes Difficulty (Detection, D) is evaluated by three risk factors to obtain the risk priority number (RiskPriorityNumber, RPN) of the failure mode, and then determine the risk order of different failure modes...

AI Technical Summary

Problems solved by technology

[0003] Although the FMEA method has been considered to be the most effective preventive measure in advance, it has the following shortcomings in the actual use process: 1) The traditional FMEA method requires experts to use numerical scoring to evaluate risk factors, but due to the ambiguity and uncertainty of human thinking 2) The traditional FMEA method gives all experts the same scoring weight, but in practice, although experts have a deep understanding of the research object, their scoring is often based on their own experience and Differences in knowledge, experience, and knowledge will lead to great differences in RPN; 3) The traditional FMEA method takes the product of the three risk factors O, S, and D as the RPN value, that is, the weights of the three are considered equal, which is in It is difficult to establish in practical application

[0006] 1. Fuzzy theory needs to determine fuzzy numbers and their membership functions in advance, but there is no unified selection criterion in theory, and it can only be based on the experience of researchers, which has a certain degree of subjectivity

[0007] 2. The fuzzy method needs a non-fuzzy process at the end, which can easily lead to the loss of useful information [11] , reducing the accuracy of FMEA analysis in some cases

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