Inspection tables for single acceptance sampling with crisp and fuzzy formulation of quality limits
International Journal of Quality & Reliability Management
ISSN: 0265-671X
Article publication date: 1 October 2018
Abstract
Purpose
The purpose of this paper is to construct innovative exact and approximative sampling plans for acceptance sampling in statistical quality control. These sampling plans are determined for crisp and fuzzy formulation of quality limits, various lot sizes and common α- and β-levels.
Design/methodology/approach
The authors use generalized fuzzy hypothesis testing to determine sampling plans with fuzzified quality limits. This test method allows a consideration of the indifference zone related to expert opinion or user priorities. In addition to the exact sampling plans calculated with the hypergeometric operating characteristic function, the authors consider approximative sampling plans using a little known, but excellent operating characteristic function. Further, a comprehensive sensitivity analysis of calculated sampling plans is performed, in order to examine how the inspection effort depends on crisp and fuzzy formulation of quality limits, the lot size and specifications of the producer’s and consumer’s risks.
Findings
The results related the parametric sensitivity analysis of the calculated sampling plans and the conclusions regarding the approximation quality provide the user a comprehensive basis for a direct implementation of the sampling plans in practice.
Originality/value
The constructed sampling plans ensure the simultaneous control of producer’s and consumer’s risks with the smallest possible inspection effort on the one hand and a consideration of expert opinion or user priorities on the other hand.
Keywords
Citation
Chukhrova, N. and Johannssen, A. (2018), "Inspection tables for single acceptance sampling with crisp and fuzzy formulation of quality limits", International Journal of Quality & Reliability Management, Vol. 35 No. 9, pp. 1755-1791. https://doi.org/10.1108/IJQRM-03-2017-0034
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited