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研究生:林佳臻
研究生(外文):Lin, Chia Chen
論文名稱:基於製程良率之計量型兩計畫驗收抽樣系統
論文名稱(外文):Developing a Two-plan Sampling System for Variables Based on Process Yield
指導教授:吳建瑋吳建瑋引用關係
指導教授(外文):Wu, Chien Wei
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:67
中文關鍵詞:驗收抽樣計畫兩計畫驗收抽樣系統正常檢驗加嚴檢驗製程能力指標
外文關鍵詞:Acceptance Sampling PlansTwo-plan Sampling systemNormal InspectionTightened InspectionProcess Capability Indices
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驗收抽樣計畫為品質管制中重要之工具,其可作為買賣雙方間判定貨批是否允收之決策準則。其中一種為「兩計畫驗收抽樣系統」,係由加嚴型與正常型單次驗收抽樣計畫搭配轉換機制而組成,此系統由加嚴檢驗開始,當貨批在加嚴檢驗中連續 次允收即可轉換至正常檢驗,若正常檢驗被拒絕第一次後 次內又被拒絕,則需轉換回加嚴檢驗,此系統較傳統型驗收抽樣計畫更具效率與彈性。
產品品質之衡量,除驗收抽樣計畫之外,運用統計理論分析生產流程穩定度之「製程能力指標」亦是當今廣為應用之方法,其用於評估產品在生產中的製程能力水準以及追蹤與改善產品在生產中的異常因子。其中,雙邊製程能力指標 與單邊製程能力指標 與 (簡稱為 )被業界廣泛使用。
因此,本論文提出計量型之新型態兩計畫驗收抽樣系統,參數為相同樣本數與相異允收臨界值,記為 ,分為兩大部分:第一部分結合指標 ,第二部分則結合指標 ,藉由結合單邊與雙邊製程能力指標以提升本論文之實用價值。此研究除針對各型態之計量型兩計畫驗收抽樣系統進行操作特性曲線與平均抽樣數之分析外,更與傳統驗收抽樣計畫進行比較。最後,藉由操作實際案例,提供使用者在應用此驗收抽樣系統時之程序及準則,以凸顯本研究之貢獻。

Acceptance sampling plans can provide the vendor and the buyer a decision rule for lot sentencing to meet their requirements of product quality. One of them is two-plan sampling system, which consists of single sampling plans with normal and tightened inspections. The system begins from tightened inspection, and switch to normal inspection if lots in a raw are all accepted. Then if there is an additional lot is rejected in the next lots after a rejection under normal inspection, it needs to turn back to tightened inspection. Therefore, it is also called tightened-normal- tightened (TNT) sampling system.
Process capability indices can provide measures on the ability of reproducing product units that meet the specifications, and the widely used capability indices are and ( and ). So, several variables single sampling plans have been developed based on process capability indices for controlling the lot or process fraction defective recently.
For above reasons, we developed a variables TNT sampling system with new type in this paper. It can be divided into two parts, one is based on and the other one is based on . Combining two kinds of process capability indices can enhance the practical value of this paper. The results of sampling systems indicate that the proposed sampling system is more efficient and flexible than traditional acceptance sampling plans. Lastly, we analyzed a practical case to assist users to learn more from the proposed sampling systems.

致謝 i
摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
表目錄 vii
符號說明 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 5
1.3 研究架構 5
第二章 文獻回顧 8
2.1 驗收抽樣計畫 8
2.2 驗收抽樣計畫之分類 11
2.2.1 以「數據性質」之分類 11
2.2.2 以「檢驗方式」之分類 12
2.3 兩計畫驗收抽樣系統 17
2.4 驗收抽樣計畫之衡量方式 19
2.4.1 操作特性曲線 20
2.4.2 平均抽樣樣本數 21
2.5 製程能力分析與指標 22
2.5.1製程能力指標與製程良率之關係 25
2.6 雙邊製程能力指標 29
2.6.1雙邊製程能力指標 之估計式 29
2.6.2雙邊製程能力指標 之抽樣分配 29
2.6.3雙邊製程能力指標 之假設檢定 31
2.7 單邊製程能力指標 32
2.7.1單邊製程能力指標 之估計式 32
2.7.2單邊製程能力指標 之抽樣分配 33
2.7.3單邊製程能力指標 之假設檢定 33
第三章 基於製程能力指標之計量型兩計畫驗收抽樣系統 35
3.1 雙邊製程能力指標 之 驗收抽樣系統 35
3.1.1 系統設計概念及執行步驟 36
3.1.2 系統之允收機率函數 38
3.1.3 系統參數數學模型 39
3.1.4 求解結果分析與討論 40
3.2 單邊製程能力指標 之 驗收抽樣系統 43
3.2.1 系統設計概念及執行步驟 43
3.2.2 系統之允收機率函數 45
3.2.3 系統參數數學模型 46
3.2.4 求解結果分析與討論 47
第四章 比較分析與探討 51
4.1 系統參數 之探討 51
4.2 之 抽樣系統與文獻方法比較 53
4.2.1 操作特性曲線 53
4.2.2 平均抽樣樣本數 54
4.3 之 抽樣系統與文獻方法比較 55
4.3.1 操作特性曲線 55
4.3.2 平均抽樣樣本數 56
第五章 實際案例 58
5.1 雙邊規格之案例 58
5.2 單邊規格之案例 60
第六章 結論與未來展望 63
6.1 結論 63
6.2 未來展望 64
參考文獻 65


中文文獻:
1.李景文 (1980)。抽樣檢驗。華泰圖書文物公司。
2.張有成 (1983)。抽樣檢驗:增訂版。中華民國品質管制學會。
英文文獻:
1.Aslam M., Wu, C. W., Azam, M. and Jun, C. H. (2016). Switching variable sampling based on the process capability index. Journal of Engineering Research. DOI:10.1080/03610926.2015.1004092.
2.Aslam, M., Yen, C. H., Chang, C. H. and Jun, C. H. (2013). Multiple states repetitive group sampling plans with process loss consideration. Applied Mathematical Modelling, 37(20), 9063-9075.
3.Balamurali, S. and Jun, C. H. (2009). Designing of a variables two-plan system by minimizing the average sample number. Journal of Applied Statistics, 36(10), 1159-1172.
4.Calvin, T. W. (1977). TNT zero acceptance number sampling. American Society for Quality Control Annual Technical Conference Transaction, 24, 35-39.
5.Chou, Y. M. and Owen, D. B. (1989). On the distributions of the estimated process capability indices. Communications in Statistics-Theory and Methods, 18(12), 4549-4560.
6.Dodge, H. F. and Romig, H. (1929). A method of sampling inspection. Bell System Technical Journal, 8(4), 613-631.
7.Juran, J. M. (1974). Quality Control Handbook, 3rd ed. McGraw-Hill, New York.
8.Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41-52.
9.Kurniati, N., Yeh, R. H. and Wu, C. W. (2015). Designing a variables two-plan sampling system of type for controlling process fraction nonconforming with unilateral specification limit. International Journal of Production Research, 53(7), 2011-2025.
10.Leone, F. C., Nelson, L. S. and Nottingham, R. B. (1961). The folded normal distribution. Technometrics, 3(4), 543-550.
11.Montgomery, D. C. (2009). Introduction to Statistical Quality Control, 6th. John Wiley and Sons, New York.
12.Muthuraj, D. and Senthilkumar, D. (2006). Designing and construction of tightened-normal-tightened variables sampling scheme. Journal of Applied Statistics, 33(1), 101-111.
13.Pearn, W. L. and Chen, K. S. (2002). One-sided capability indices and : decision making with sample information. International Journal of Quality & Reliability Management, 19(3), 221-245.
14.Pearn, W. L., Lin, P. C. and Chen, K. S. (2004). The index for asymmetric tolerances: Implications and inference. Metrika, 60(2), 119-136.
15.Pearn, W. L. and Shu, M. H. (2003). Manufacturing capability control for multiple power-distribution switch processes based on modified MPPAC. Microelectronics Reliability, 4(6), 963-975.
16.Pearn, W. L. and Wu, C. W. (2006). Critical acceptance values and sample sizes of a variables sampling plan for very low fraction of defectives. Omega, 34(1), 90-101.
17.Pearn, W. L. and Wu, C. W. (2007). An effective decision making method for product acceptance. Omega, 35(1), 12-21.
18.Seidel, W. (1997). Is sampling by variables worse than sampling by attributes? A decision theoretic analysis and a new mixed strategy for inspecting individual lots. Sankhya: The Indian Journal of Statistics, Series B, 96-107.
19.Senthilkumar, D. and Muthuraj, D. (2010) Construction and selection of Tightened-Normal-Tightened variables sampling scheme of type TNTVSS . Journal of Applied Statistics, 37(3), 375-390.
20.Soundararajan, V. and Vijayaraghavan, R. (1992). Construction and selection of tightened-normal-tightened sampling inspection scheme of type TNT-(n1, n2; c). Journal of Applied Statistics, 19(3), 339-349.
21.Vännman, Kerstin. (1997) Distribution and moments in simplified form for a general class of capability indices. Communications in statistics-theory and methods, 26, 159-179.
22.Vijayaraghavan, R. and Soundararajan, V. (1996). Procedures and tables for the selection of tightened-normal-tightened (TNT-(n;c1,c2)) sampling schemes. Journal of Applied Statistics, 23(1), 69-80.
23.Wu, C. W., Aslam, M. and Jun, C. H. (2012). Variables sampling inspection scheme for resubmitted lots based on the process capability index . European Journal of Operational Research, 217(3), 560-566.
24.Wu, C. W., Aslam, M. and Jun, C. H. (2016). Developing a variables two-plan sampling system for product acceptance determination. Communications in Statistics-Theory and Methods, just-accepted, 00-00.

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