消費者在選擇比較產品與服務時最重要的決策因子為品質，利用統計方法於品質工程的應用之中，通常會將資料分類為屬性資料或是變數資料，而允收抽樣為廣泛應用在品質工程中一個最重要的統計方法，允收抽樣計畫中描述所需的樣本數目與接受或是拒絕一批貨的條件。本篇論文提出一個在卜瓦松分布重複批量的屬性抽樣計畫，此抽樣計畫以數值方式衡量品質特徵，並在相同的生產者風險與客戶風險水準下，與傳統單一樣本抽樣計畫相比具有較小的樣本數優勢，這個是相當有利的基礎，尤其是產品品質檢驗是耗成本與具破壞性的狀況。本研究完成不同參數組合中，並配合生產者風險與客戶風險下，所需樣本數與臨界接受值的表格，並且比較基於卜瓦松分布複批量的屬性抽樣計畫的行為，加以呈現與討論，最後並以一個數值範例用來描述所提出的基於卜瓦松分布複批量的屬性抽樣計畫在實際環境中的應用。

The most important consumer decision factors in the selection among competing products and services is quality. In the application of statistical methods to quality engineering, it is typical to classify data on quality characteristics as either attributes or variables data. One of the most important statistical tools widely used for this purpose is acceptance sampling. Acceptance sampling plans state the required sample size and the required acceptance or rejection criteria for lots sentencing. This thesis proposes resubmitted lots with single sampling plan (RSSP) by attributes under the conditions of Poisson distribution. Attributes RSSP under Poisson distribution will measure the quality characteristics on a numerical scale, with several advantages of having smaller sample size than traditional Single Sampling Plan under the same level of protection for both producer and customer. This is especially beneficial when the inspection is costly and destructive. For study purpose, tables for the required sample size and critical acceptance value of various combinations of quality levels, producer’s risk and consumer’s risk are constructed. Furthermore, the behaviors of the RSSP under Poisson distribution with various conditions are also shown and discussed. A numerical example is provided to illustrate and demonstrate how to use the RSSP under Poisson distribution in the real applications.

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