In this paper, we study the applicability of the monotone output property and the output resolution property in fuzzy assessment models to two industrial Failure Mode and Effect Analysis (FMEA) problems. First, the effectiveness of the monotone output property in a single-input fuzzy assessment model is demonstrated with a proposed fuzzy occurrence model. Then, the usefulness of the two properties to a multi-input fuzzy assessment model, i.e., the Bowles fuzzy Risk Priority Number (RPN) model, is assessed. The experimental results indicate that both the fuzzy occurrence model and Bowles fuzzy RPN model are able to fulfill the monotone output property, with the derived conditions (in Part I) satisfied. In addition, the proposed rule refinement technique is able to improve the output resolution property of the Bowles fuzzy RPN model.Keywords Assessment models · Monotone output property · Output resolution property · Failure mode and effect analysis · Risk priority number
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b s t r a c tThe focus of this paper is on the production processes of Edible Bird Nest (EBN) in Sarawak, Malaysia. Sarawak and Sabah (two states of Malaysia in the Borneo Island) are known as the second ranked resource area (after Indonesia) of the world for EBN production. In spite of the popularity of EBN as a food source and the important economic status of the EBN industry, the use of a quality and risk assessment tool for the production of EBN is new. As such, the implementation of an advanced quality and risk assessment tool, i.e., the fuzzy Failure Mode and Effect Analysis (FMEA) methodology, for EBN processing is described in this paper. Data and information are gathered from several EBN production sites, and fuzzy FMEA is adopted to analyze the collected data/information. It is worth mentioning that the EBN production in Sarawak is relatively traditional. As such, this work makes an important contribution to modernization of the EBN production industry in Sarawak, i.e., to improve the production process and ensure the quality of EBN via the use of a formal quality and risk assessment tool. Besides, this paper contributes to a new application of fuzzy FMEA to the agriculture and food domain.
An assessment model is a mathematical model that produces a measuring index, either in the form of a numerical score or a category to a situation/object, with respect to the subject of measure. From the numerical score, decision can be made and action can be taken. To allow valid and useful comparisons among various situations/objects according to their associated numerical scores to be made, the monotone output property and the output resolution property are essential in fuzzy inferencebased assessment problems. We investigate the conditions for a fuzzy assessment model to fulfill the monotone output property using a derivative approach. A guideline on how the input membership functions should be tuned is also provided. Besides, the output resolution property is defined as the derivative of the output of the assessment model with respect to its input. This derivative should be greater than the minimum resolution required. From the derivative, we suggest improvements to the output resolution property by refining the fuzzy production rules.
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