This thesis is concerned with economic designs of rectifying sampling inspection plans based on a correlated variable. In rectifying inspection, all of the items for rejected lots are subjected to acceptance inspection. If an item fails to meet the predetermined inspection specifications, it is rejected and excluded from shipment. In some situations, however, the inspection on the quality characteristic of interest is destructive or very costly, it may be economical to use another variable that is correlated with the quality characteristic of interest and relatively inexpensive to measure as the correlated variable.
Two models of rectifying inspection plans based on a correlated variable are considered depending on whether the quality characteristic of interest is variables or attributes. For the two models, the expected profit per lot is derived which involves the profit and the costs of misclassification errors, sampling and screening inspections. The optimum values of sample size, critical value for sampling plan, and cutoff value on the correlated variable are jointly obtained by maximizing the expected profit. Numerical examples and studies are perfomed to compare rectifying sampling inspection based on a correlated variable with sampling plan based on a quality characteristic of interest and screening procedure(complete inspection) based on a correlated variable.
