Abstract
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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Tay, K.M., Lim, C.P. (2010). On the Use of Fuzzy Inference Systems for Assessment and Decision Making Problems. In: Jain, L.C., Lim, C.P. (eds) Handbook on Decision Making. Intelligent Systems Reference Library, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13639-9_10
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DOI: https://doi.org/10.1007/978-3-642-13639-9_10
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