On the Use of Fuzzy Inference systems for assessment and decision making problems
The Fuzzy Inference System (FIS) is a popular paradigm for undertaking assessment/measurement and decision problems. In practical applications, it is important to ensure the monotonicity property between the attributes (inputs) and the measuring index (output) of an FIS-based assessment/ measurement...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Springer-Verlag Berlin Heidelberg
2010
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| Online Access: | http://ir.unimas.my/id/eprint/3042/ http://ir.unimas.my/id/eprint/3042/1/Tay.pdf |
| _version_ | 1848835130737557504 |
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| author | Tay, K.M Lim, C.P |
| author_facet | Tay, K.M Lim, C.P |
| author_sort | Tay, K.M |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | The Fuzzy Inference System (FIS) is a popular paradigm for undertaking assessment/measurement and decision problems. In practical applications, it is important to ensure the monotonicity property between the attributes (inputs) and the measuring index (output) of an FIS-based assessment/ measurement model. In this chapter, the sufficient conditions for an FIS-based model to satisfy the monotonicity property are first investigated. Then, an FIS-based Risk Priority Number (RPN) model for Failure Mode and Effect Analysis (FMEA) is examined. Specifically, an FMEA framework with a monotonicity-preserving FIS-based RPN model that fulfils the sufficient conditions is proposed. A case study pertaining to the use of the proposed FMEA framework in the semiconductor industry is presented. The results obtained are discussed and analyzed. |
| first_indexed | 2025-11-15T06:02:59Z |
| format | Article |
| id | unimas-3042 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:02:59Z |
| publishDate | 2010 |
| publisher | Springer-Verlag Berlin Heidelberg |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-30422021-07-05T15:03:19Z http://ir.unimas.my/id/eprint/3042/ On the Use of Fuzzy Inference systems for assessment and decision making problems Tay, K.M Lim, C.P TK Electrical engineering. Electronics Nuclear engineering The Fuzzy Inference System (FIS) is a popular paradigm for undertaking assessment/measurement and decision problems. In practical applications, it is important to ensure the monotonicity property between the attributes (inputs) and the measuring index (output) of an FIS-based assessment/ measurement model. In this chapter, the sufficient conditions for an FIS-based model to satisfy the monotonicity property are first investigated. Then, an FIS-based Risk Priority Number (RPN) model for Failure Mode and Effect Analysis (FMEA) is examined. Specifically, an FMEA framework with a monotonicity-preserving FIS-based RPN model that fulfils the sufficient conditions is proposed. A case study pertaining to the use of the proposed FMEA framework in the semiconductor industry is presented. The results obtained are discussed and analyzed. Springer-Verlag Berlin Heidelberg 2010 Article NonPeerReviewed text en http://ir.unimas.my/id/eprint/3042/1/Tay.pdf Tay, K.M and Lim, C.P (2010) On the Use of Fuzzy Inference systems for assessment and decision making problems. Handbook on Decision Making, 4. pp. 233-246. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Tay, K.M Lim, C.P On the Use of Fuzzy Inference systems for assessment and decision making problems |
| title | On the Use of Fuzzy Inference systems for assessment and decision making problems |
| title_full | On the Use of Fuzzy Inference systems for assessment and decision making problems |
| title_fullStr | On the Use of Fuzzy Inference systems for assessment and decision making problems |
| title_full_unstemmed | On the Use of Fuzzy Inference systems for assessment and decision making problems |
| title_short | On the Use of Fuzzy Inference systems for assessment and decision making problems |
| title_sort | on the use of fuzzy inference systems for assessment and decision making problems |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://ir.unimas.my/id/eprint/3042/ http://ir.unimas.my/id/eprint/3042/1/Tay.pdf |