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A Single Input Rule Modules Connected Fuzzy FMEA Methodology for Edible Bird Nest Processing

  • Chian Haur Jong
  • Kai Meng Tay
  • Chee Peng Lim
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 223)

Abstract

Despite of the popularity of the fuzzy Failure Mode and Effects Analysis (FMEA) methodology, there are several limitations in combining the Fuzzy Inference System (FIS) and the Risk Priority Number (RPN) model. Two main limitations are: (1) it is difficult and impractical to form a complete fuzzy rule base when the number of required rules is large; and (2) fulfillment of the monotonicity property is a difficult problem. In this paper, a new fuzzy FMEA methodology with a zero-order Single Input Rule Modules (SIRMs) connected FIS-based RPN model is proposed. An SIRMs connected FIS is adopted as an alternative to the traditional FIS to reduce the number of fuzzy rules required in the modeling process. To preserve the monotonicity property of the SIRMs-connected FIS-based RPN model, a number of theorems in the literature are simplified and adopted as the governing equations for the proposed fuzzy FMEA methodology. A case study relating to edible bird nest (EBN) processing in Sarawak (together with Sabah, known as the world’s number two source area of bird nest after Indonesia) is reported. In short, the findings in this paper contribute towards building a new fuzzy FMEA methodology using the SIRM s connected FIS-based RPN model. Besides that, the usefulness of the simplified theorems in a practical FMEA application is demonstrated.

Keywords

Failure Mode and Effect Analysis Fuzzy reasoning Single-input-rule-modules connected fuzzy inference system Mmonotonicity property Edible bird nest 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Chian Haur Jong
    • 1
  • Kai Meng Tay
    • 1
  • Chee Peng Lim
    • 2
  1. 1.Universiti Malaysia SarawakKota SamarahanMalaysia
  2. 2.Centre for Intelligent Systems ResearchDeakin UniversityGeelongAustralia

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