Abstract
Abstract Rectifying Average Outgoing Quality Limit (AOQL) acceptance sampling plans that minimize the mean inspection cost per lot of the process average quality were originally designed by Dodge and Romig for inspection by attributes. Plans for inspection by variables were then proposed; such plans may be more economically efficient than the corresponding attribute sampling plans. The new AOQL variable sampling plans, which minimize the mean inspection cost per lot of the process average quality when the remainder of the rejected lots are inspected, are introduced in this article. The new plans are based on the usage of the exponentially weighted moving average statistic, and the economic advantages of the new plans over the existing plans with respect to savings in the cost of the inspection are discussed. The economic efficiency of the new plans is evaluated using cost models that consider differences in both variable and fixed costs. The methods for the calculation of the proposed plans have been implemented in a free software, i.e., the contributed package LTPDvar for the R computing environment.
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