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...

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Main Authors: Tay, K.M, Lim, C.P
Format: Article
Language:English
Published: Springer-Verlag Berlin Heidelberg 2010
Subjects:
Online Access:http://ir.unimas.my/id/eprint/3042/
http://ir.unimas.my/id/eprint/3042/1/Tay.pdf
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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.
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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