Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm
The extent of failure evaluation depends on the complexity and significance of electronic products. However, traditional failure mode and effect analysis (FMEA) has many shortcomings, which brings large difficulty to failure evaluating work. This paper uses the double hierarchy hesitant fuzzy lingui...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/14/12/2555 |
| _version_ | 1797431418271301632 |
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| author | Jinkun Dai Jihong Pang Qiang Luo Qianbing Huang |
| author_facet | Jinkun Dai Jihong Pang Qiang Luo Qianbing Huang |
| author_sort | Jinkun Dai |
| collection | DOAJ |
| description | The extent of failure evaluation depends on the complexity and significance of electronic products. However, traditional failure mode and effect analysis (FMEA) has many shortcomings, which brings large difficulty to failure evaluating work. This paper uses the double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) and the K-means clustering algorithm to improve the shortcomings of traditional FMEA. The DHHFLTS is a set of language terms based on the symmetry method and uniform language granularity. Firstly, we determine the product failure mode and set up an evaluation team after formulating an evaluation symmetrical language set. The psychological changes of the evaluators can be truly expressed by using the DHHFLTS. Secondly, the entropy weight method is used to calculate the weight of the evaluation members. The evaluation information of the evaluation personnel on the failure mode is aggregated based on the weight of the evaluation members. Then, the K-means clustering algorithm is used to calculate the distance between failure modes and each cluster center point by using the normalized weight of influencing factors and the evaluation distance of each evaluator. Finally, the evaluation of an electromagnet failure mode is taken as an example to prove the objectivity and practicability of the new method. |
| first_indexed | 2024-03-09T09:44:44Z |
| format | Article |
| id | doaj.art-67c5449a95ed422588c08d49ed332046 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-09T09:44:44Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-67c5449a95ed422588c08d49ed3320462023-12-02T00:39:49ZengMDPI AGSymmetry2073-89942022-12-011412255510.3390/sym14122555Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering AlgorithmJinkun Dai0Jihong Pang1Qiang Luo2Qianbing Huang3College of Business, Shaoxing University, Shaoxing 312000, ChinaCollege of Business, Shaoxing University, Shaoxing 312000, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaThe extent of failure evaluation depends on the complexity and significance of electronic products. However, traditional failure mode and effect analysis (FMEA) has many shortcomings, which brings large difficulty to failure evaluating work. This paper uses the double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) and the K-means clustering algorithm to improve the shortcomings of traditional FMEA. The DHHFLTS is a set of language terms based on the symmetry method and uniform language granularity. Firstly, we determine the product failure mode and set up an evaluation team after formulating an evaluation symmetrical language set. The psychological changes of the evaluators can be truly expressed by using the DHHFLTS. Secondly, the entropy weight method is used to calculate the weight of the evaluation members. The evaluation information of the evaluation personnel on the failure mode is aggregated based on the weight of the evaluation members. Then, the K-means clustering algorithm is used to calculate the distance between failure modes and each cluster center point by using the normalized weight of influencing factors and the evaluation distance of each evaluator. Finally, the evaluation of an electromagnet failure mode is taken as an example to prove the objectivity and practicability of the new method.https://www.mdpi.com/2073-8994/14/12/2555failure evaluationDHHFLTSK-means clustering algorithmFMEAentropy weight method |
| spellingShingle | Jinkun Dai Jihong Pang Qiang Luo Qianbing Huang Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm Symmetry failure evaluation DHHFLTS K-means clustering algorithm FMEA entropy weight method |
| title | Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm |
| title_full | Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm |
| title_fullStr | Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm |
| title_full_unstemmed | Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm |
| title_short | Failure Evaluation of Electronic Products Based on Double Hierarchy Hesitant Fuzzy Linguistic Term Set and K-Means Clustering Algorithm |
| title_sort | failure evaluation of electronic products based on double hierarchy hesitant fuzzy linguistic term set and k means clustering algorithm |
| topic | failure evaluation DHHFLTS K-means clustering algorithm FMEA entropy weight method |
| url | https://www.mdpi.com/2073-8994/14/12/2555 |
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