종속적 비평형 다중표본 계획법의 연구

A Study of Dependent Nonstationary Multiple Sampling Plans

In this paper, nonstatiomrry multiple sampling plans are discussed which are difficult to solve by analytical method when there exists dependency between the sample data. The initial solution is found by the sequential npling plan using the sequential probability ration test. The number of accep nee and rejection in each step of the multiple sampling plan e found by grouping the sequential sampling plan’s solution initially. The optimal multiple sampling plans are found by simulation. Four search methods are developed to find the optimum sampling plans satisfying the Type I and Type II error probabilities. The performance of the sampling plans is measured and their algorithms are also shown. To consider the nonstationarγ property of the dependent sampling plan, simulation method is used for finding the lot rejection and acceptance probability function. As a numerical example Markov chain model is inspected. Effects of the dependency factor and search methods are compared to analyze the sampling results by changing their parameters.