A new system of skip-lot sampling plans having a provision for reducing normal inspection
The skip-lot sampling program can be used for reducing the amount of inspection on a product that has excellent quality history. Thus skip-lot sampling plans are designed to reduce inspection costs. Moreover, the skip-lot concept is sound and useful and is economically advantageous to use in the design of sampling plans. Hence, a new system of skip-lot sampling plans designated as the SkSP-V plan is developed in this paper. The proposed plan requires a return to normal inspection whenever a lot is rejected during sampling inspection, but has a provision for a reduced normal inspection upon demonstration of superior product quality. A Markov chain formulation and derivation of performance measures for this new plan are presented. The properties of SkSP-V plan are studied with single sampling plan as the reference plan. Advantages of this new plan are also discussed. Finally, certain cost models are given for the economic design of the SkSP-V plan. Copyright © 2010 John Wiley & Sons, Ltd.
Sampling Plan Adjustment for Inspection Error and Skip-Lot Plan
(This paper has been selected for presentation at the Journal of Quality Technology session of the 26th Annual Fall Technical Conference of the Chemical Division of the American Society for Quality Control and the Section of Physical and Engineering Sci..
Optimal Use of Control Charts for Controlling Current Production
A model is developed consisting of all the costs incurred when fraction-defective control charts are utilized to control current production: cost of sampling, cost of not detecting a change in the process, cost of false indication of change, and cost of re-adjusting detected changes. It is suggested that such control charts can be utilized in an optimal way, if those combinations of sample size, frequency of sampling and extent of control limits from process average will be used that provide the minimum total cost. It is further suggested that, by applying any specific cost data to this model, these optimal decision values can be easily evaluated by computer enumeration.