Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance
Abstract Failure mode and effects analysis (FMEA) has been widely used for potential risk modeling and management. Expert evaluation is used to model the risk priority number to determine the risk level of different failure modes. Dempster–Shafer (D–S) evidence theory is an effective method for unce...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-05-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-12360-9 |
| _version_ | 1811250943418695680 |
|---|---|
| author | Yusong Yuan Yongchuan Tang |
| author_facet | Yusong Yuan Yongchuan Tang |
| author_sort | Yusong Yuan |
| collection | DOAJ |
| description | Abstract Failure mode and effects analysis (FMEA) has been widely used for potential risk modeling and management. Expert evaluation is used to model the risk priority number to determine the risk level of different failure modes. Dempster–Shafer (D–S) evidence theory is an effective method for uncertain information modeling and has been adopted to address the uncertainty in FMEA. How to deal with conflicting evidence from different experts is an open issue. At the same time, different professional backgrounds of experts may lead to different weights in modeling the evaluation. How to model the relative weight of an expert is an important problem. We propose an improved risk analysis method based on triangular fuzzy numbers, the negation of basic probability assignment (BPA) and the evidence distance in the frame of D–S evidence theory. First, we summarize and organize the expert’s risk analysis results. Then, we model the expert’s assessments based on the triangular fuzzy numbers as BPAs and calculate the negation of BPAs. Third, we model the weight of expert based on the evidence distance in the evidence theory. Finally, the Murphy’s combination rule is used to fuse the risk assessment results of different experts and calculate the new risk priority number (RPN). At the end of this paper, we apply the proposed method to analyze seventeen failure modes of aircraft turbine blades. The experimental results verify the rationality and effectiveness of this method. |
| first_indexed | 2024-04-12T16:12:18Z |
| format | Article |
| id | doaj.art-edfd259b2ef34853882e5a422628d388 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-12T16:12:18Z |
| publishDate | 2022-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-edfd259b2ef34853882e5a422628d3882022-12-22T03:25:51ZengNature PortfolioScientific Reports2045-23222022-05-0112111310.1038/s41598-022-12360-9Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distanceYusong Yuan0Yongchuan Tang1School of Big Data and Software Engineering, Chongqing UniversitySchool of Big Data and Software Engineering, Chongqing UniversityAbstract Failure mode and effects analysis (FMEA) has been widely used for potential risk modeling and management. Expert evaluation is used to model the risk priority number to determine the risk level of different failure modes. Dempster–Shafer (D–S) evidence theory is an effective method for uncertain information modeling and has been adopted to address the uncertainty in FMEA. How to deal with conflicting evidence from different experts is an open issue. At the same time, different professional backgrounds of experts may lead to different weights in modeling the evaluation. How to model the relative weight of an expert is an important problem. We propose an improved risk analysis method based on triangular fuzzy numbers, the negation of basic probability assignment (BPA) and the evidence distance in the frame of D–S evidence theory. First, we summarize and organize the expert’s risk analysis results. Then, we model the expert’s assessments based on the triangular fuzzy numbers as BPAs and calculate the negation of BPAs. Third, we model the weight of expert based on the evidence distance in the evidence theory. Finally, the Murphy’s combination rule is used to fuse the risk assessment results of different experts and calculate the new risk priority number (RPN). At the end of this paper, we apply the proposed method to analyze seventeen failure modes of aircraft turbine blades. The experimental results verify the rationality and effectiveness of this method.https://doi.org/10.1038/s41598-022-12360-9 |
| spellingShingle | Yusong Yuan Yongchuan Tang Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance Scientific Reports |
| title | Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance |
| title_full | Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance |
| title_fullStr | Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance |
| title_full_unstemmed | Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance |
| title_short | Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance |
| title_sort | fusion of expert uncertain assessment in fmea based on the negation of basic probability assignment and evidence distance |
| url | https://doi.org/10.1038/s41598-022-12360-9 |
| work_keys_str_mv | AT yusongyuan fusionofexpertuncertainassessmentinfmeabasedonthenegationofbasicprobabilityassignmentandevidencedistance AT yongchuantang fusionofexpertuncertainassessmentinfmeabasedonthenegationofbasicprobabilityassignmentandevidencedistance |