A Proposed Framework for Developing FMEA Method Using Pythagorean Fuzzy CODAS
The purpose of this research article is to develop a hybridization between the Failure Mode and Effect Analysis (FMEA) method and the Combinative Distance-Based Assessment (CODAS) method under Pythagorean Fuzzy environment. The traditional FMEA procedure is based on the multiplication between the...
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| Main Author: | |
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| Other Authors: | , , , , |
| Format: | Artículo |
| Language: | en_US |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://doi.org/10.3390/sym13122236 https://www.mdpi.com/2073-8994/13/12/2236 |
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| Summary: | The purpose of this research article is to develop a hybridization between the Failure Mode
and Effect Analysis (FMEA) method and the Combinative Distance-Based Assessment (CODAS)
method under Pythagorean Fuzzy environment. The traditional FMEA procedure is based on the
multiplication between the parameters of severity, occurrence, and detectability where everyone
has equal relative importance; therefore, different combinations of these parameters can generate
the same result creating uncertainty in the analysis. In this mode, the hybridization proposed in
this research deal with relative importance of each parameter; in the fact to have a more suitable
combination which consider the level of knowledge of the experts in the assessment. Finally, a
numerical case was carried out concerning the public transportation service to validate our proposal;
the results show that 31 failure modes and potential risks can be evaluated using user perceptions, a
dominant with high level of knowledge about the public transportation service and an apprentice or
common user, as team of experts and exploiting the subjectivity of the information in a mathematical
model. Also, we compare the results with a variation of the proposed model with the multi-criteria
method multi-objective optimization method by relationship analysis (MOORA); it was observed
that the convergence of the failure modes depends on the nature of the mathematical model even
under the same conditions at the start. |
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