A Potential Failure Mode and Effect Analysis Method of Electromagnet Based on Intuitionistic Fuzzy Number in Manufacturing Systems

Abstract

Failure mode and effect analysis (FMEA) is a systematic activity in the stage of product design and process design. However, the traditional FMEA has some shortcomings in practical application, such as too many evaluation languages, uncertain weights of influencing factors, and uncertain weights of evaluation members. This paper presents an FMEA evaluation method in manufacturing system based on similarity measure, nonlinear programming model, and intuitionistic fuzzy number (IFN). Firstly, the IFN is used to evaluate failure mode, which overcomes the defect of traditional FMEA evaluation value. Secondly, the weight of failure evaluation team members is solved according to the concept of similarity measure to make up for the blank of evaluation members’ weight aiming at the shortage of unknown weight. Then, the definition of consensus measure is introduced to make the evaluators reach a consensus, and the weights of influencing factors of failure modes (FMs) are calculated. Finally, the weights of evaluators and influencing factors are calculated by IFN algorithm and score function, and the score value of each FM is obtained to rank instead of risk priority number (RPN). The objectivity and practicability of the new method are verified by the example of failure mode for an attractive electromagnet manufacturing system.

WITHDRAWN: A reliability analysis method for industrial robots based on double hierarchy hesitant fuzzy linguistic term set and TODIM

“…Pang J et al proposed to design a new intuitionistic fuzzy evaluation number under the intuitionistic fuzzy environment. The subordination degree and non-subordination degree of each failure mode influencing factor in each language granularity are evaluated respectively, which can deal with the fuzzy evaluation under the condition of uniform distribution of preference levels [13]. Wang L et al used cloud model (CM) to improve FMEA in order to reduce uncertainty, randomness and ambiguity in the evaluation process.…”

Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm

“…For these nine failure modes, we use the calculation results of three methods for comparison. The first is the new method proposed in this paper, the second is the method used in Reference [19], and the last is traditional FMEA. They are, respectively, recorded as Sort 1, Sort 2, and Sort 3, as shown in Figure 7.…”

“…This proves that these two methods can analyze the failure modes that need to be prevented most. As for the ranking of the later failure modes, the reason is that the weights of the influencing factors calculated by the two methods are different [19] by comparing the matrix of influencing factors in pairs. In this case, we compared the new proposed method.…”

“…On the other hand, there are many ways to confirm the influencing factors and the weight of evaluation members in many research fields. Pang et al [19] used the similarity measure method to calculate the distance between evaluation information and its center point, normalized it to obtain the weight of evaluation members, and constructed a nonlinear programming model to solve the weight of influencing factors according to the pairwise comparison matrix of influencing factors. Boral et al [20] used the fuzzy analytic hierarchy process (FAHP) and modified fuzzy multi-attribute ideal real comparative analysis (modified FMAIRCA) to calculate the fuzzy relative importance among the influencing factors so as to obtain the weight of the influencing factors.…”

An Intelligent Evaluation Method of Supply-Demand Matching Degree Based on ELECTRE III and VIKOR in Cloud Manufacturing Platform

“…Manufacturing resource matching model is developed on the evaluation of Intuitionistic numbers. Let a set 𝑥 = (𝑥 1 , 𝑥 2 , ⋯ , 𝑥 𝑛 ) be a finite universe of discourse, an intuitionistic fuzzy set 𝑄 in is defined as 𝑄 = {⟨𝑥, 𝜇 𝑥 (𝑥), 𝜈 𝑥 (𝑥)⟩|𝑥 ∈ 𝑋} [59]. where 𝜇 𝑋 (𝑥) and 𝜈 𝑋 (𝑥) denote, respectively, membership and non-membership of the element 𝑥 in 𝑋 to, and 𝜇 𝑋 (𝑥)ϵ[0,1] , 𝜈 𝑋 (𝑥)𝜖[0,1] , 0 ≤ 𝜇 𝑋 (𝑥) + 𝜈 𝑋 (𝑥) ≤ 1.…”