工業界在進料或產品量產時，由於受到時間與人力的限制，必須藉由抽樣檢驗計畫隨機抽取一定數量之樣本，經過檢驗或測試後，根據其結果再依統計方法判定此批量是否達到允收的標準。
　　
　　本研究針對現行MIL-STD-105單次抽樣檢驗計劃的允收過程，以模糊檢定(Fuzzy hypothesis)的方式取代明確檢定(Crisp hypothesis,檢定H0: p AQL 與 H1: p > AQL)，再依照現行抽樣檢驗計劃對生產者與消費者風險的定義，將生產者與消費者風險延伸至模糊檢定可適用之形式，並利用模糊歸屬函數建構模糊抽樣檢驗計劃，另進行該計劃與MIL-STD-105在降低生產者與消費者風險表現上之比較分析。

　　Inspection for acceptance sampling plan is carried out at many stages in manufacturing. In many instances,sampling inspection is used because the cost of 100% inspection is prohibitive.

　　In this thesis, a fuzzily formulated hypothesis is presented to replace the crisp hypothesis testing (H0: p AQL vs. H1: p > AQL) in order to modify the current MIL-STD-105 attribute acceptance sampling plan. In particular, we redefine the producer’s risk and the consumer’s risk instead of the probability of type I and type II errors, respectively.

　　Then, the fuzzy membership functions are used to establish the fuzzy attribute acceptance sampling plan and their acceptance numbers, powers and OC curves are compared with those of MIL-STD-105 attribute acceptance sampling plan.

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