Acceptance single sampling plan with fuzzy parameter
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CitationJamkhaneh, E. B., Sdeghpour-Gildeh, B. ve Yari, G. (2009). Acceptance single sampling plan with fuzzy parameter. Maltepe Üniversitesi. s. 142.
Single sampling plan for acceptance or rejecting a lot is an important subject in statistical quality control. This plan is one of the sampling method for acceptance or rejection which is along with classical attribute quality characteristic. This plan has a sample size n and acceptance number c. If the number of defective items is less than or equals to c, the lot will be accepted. However, the fraction of defective items (quality characteristic) in a lots is not often exact and certain. Estimations and personal judgments are the useful response for inexactness and ambiguity. In different acceptance sampling plan the fraction of defective items (p), is considered as a precise value, but this precision is not true in real world and decision making problems, and there also exist some uncertainty in the value of p obtained from experiment, personal judgment or estimation. The theory of fuzzy sets is widely used in solving problems in which parameter or quantities cannot be expressed precisely. The theory is a powerful and well-known tool to formulate and analyze the uncertainty resulting from ambiguity and personal judgment. In dealing with the above problem we tried to restore the uncertainty existing in the problem by defining the imprecise parameter as a fuzzy number, and achieve a result with a higher certainty. With this definition, the number of defective items in the sample has a fuzzy binomial probability distribution. In this paper we discuss the acceptance single sampling plan when the fraction of nonconforming products is a fuzzy number. We have shown that the operating characteristic (OC) curve of the plan is like a band having high and low bounds whose width depends on the ambiguity proportion parameter in the lot when that sample size and acceptance number is fixed. When the acceptance number equals zero, this band is convex for different n s and for large n, the convexity will be more. Finally we have given some examples and then compared the OC bands for some values of c.
SourceInternational Conference of Mathematical Sciences
- Makale Koleksiyonu 
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