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.
A New System of Skip-Lot Sampling Plans including Resampling
Skip-lot sampling plans have been widely used in industries to reduce the inspection efforts when products have good quality records. These schemes are known as economically advantageous and useful to minimize the cost of the inspection of the final lots. A new system of skip-lot sampling plan called SkSP-R is proposed in this paper. The performance measures for the proposed SkSP-R plan are derived using the Markov chain formulation. The proposed plan is found to be more efficient than the single sampling plan and the SkSP-2 plan.
Economic Design of Fraction Defective Control Charts
An expected cost model for the fraction defective control chart for the case where there are several out-of-control states is developed. A procedure is presented for determining the sample size, control limit or critical region, and interval between samples which minimizes the expected cost of control per unit of product. The expected cost of control consists of the cost of sampling, the cost of investigating and possibly correcting the process when an out-of-control condition is indicated, and the cost of producing defective product. Direct search techniques are used to optimize the expected cost function. Numerical examples and sensitivity analysis of the model are presented.