# 臺灣博碩士論文加值系統

(44.221.70.232) 您好！臺灣時間：2024/05/29 11:21

:::

### 詳目顯示

:

• 被引用:0
• 點閱:172
• 評分:
• 下載:0
• 書目收藏:0
 在製造工廠內，製程良率被當成標準的衡量準則已經很久。製程能力指標 可以精確地衡量常態性分配製程的良率。然而，欲以精確的數學方式推論得到 的自然估計之抽樣分配卻相當困難，因為該抽樣分配非常複雜。因此，多種近似估計方法都被開發，試圖解決以上難題。Pearn et al. (2010)利用二階條件泰勒展開式推導出一個近似估計量，他們利用臨界值(critical value)深入探討該近似估計量的性質。Chen (2005)則是利用拔靴法，模擬產生四種不同的信賴下界(the standard bootstrap (SB), the percentile bootstrap (PB), the biased-corrected percentile bootstrap (BCPB), and the bias-corrected and accelerated bootstrap (BCa))。Chen(2005)認為SB信賴下界比起其他三個信賴下界具有更高的涵蓋率，也就是說，SB信賴下界的績效優於其他三種拔靴法。這篇碩士論文中，我們比較Pearn et al. (2010)的近似估計量所產生的信賴下界，還有四種拔靴法(SB, PB, BCPB, and bootstrap-t (BT) methods)產生的信賴下界。實驗結果顯示Pearn et al. (2010)所產生的信賴下界有幾個優點：(1)在五種信賴下界中，其具有最高的涵蓋率，這也是最重要的優點，(2)Pearn et al. (2010)提出的是一種可解析函式(analytical function)，由此可知，由此法產生的信賴下界所存在的誤差能夠被衡量，但是拔靴法地信賴下界卻無法衡量誤差(3)Pearn et al. (2010)提供唯一的信賴下界，但是拔靴法提供振動的信賴下界且無法預測。綜合以上理由，我們認為由Pearn et al. (2010)所產生的信賴下界比起拔靴法更優良。
 Process yield has been a common and standard criterion in manufacturing industry for a long time. The yield index provides an exact measure on the production yield of normal processes. However, the sampling distribution of estimated is analytically intractable, therefore the approximating approach is considered. Chen (2005) applied the famous boot-strap method, a nonparametric but effective simulation technique, to deal with the intractabil-ity. Chen (2005) utilized four bootstrap methods to conduct lower confidence bound (LCB) and noted that the standard bootstrap (SB) method outperforms the other three in coverage proportion. Moreover, Pearn et al. (2010) used the convolution method based upon the se-cond-order approximation by Taylor expansion to estimate the yield index . In this thesis, we compared coverage proportions and LCBs based on the convolution and the bootstrap approximation. The results revealed that the CP incurred by the LCB obtained from the convolution approximation outperforms the one from the bootstrap method.
 中文摘要 iAbstract ii誌謝 iiiContents ivList of Tables vList of Figures vi1. Introduction 12. Literature review 43. Convolution method for the estimated 83.1 The estimator 83.2 Determine the minimal required sample size 93.3 Lower confidence bounds and coverage proportion 174 Bootstrap methodology 194.1 Lower confidence bounds of bootstrap methodology 20A. Standard Bootstrap (SB) method 20B. Percentile Bootstrap (PB) method 20C. Bias-Corrected Percentile Bootstrap (BCPB) method 21D. Bootstrap-t (BT) method 214.2 Lower confidence bounds and coverage proportions based on the bootstrap method 225 Performance comparisons of convolution and bootstrapping methods 26Reference 35Appendix 38
 1. Boyles, R. A. (1991). The Taguchi capability index. Journal of Quality Technology, 23(1), 17-26.2. Boyles, R. A. (1994). Process capability with asymmetric tolerances. Communications in Statistics-Simulation and Computation, 23(3), 615-643.3. Chan, L. K., Cheng, S. W. and Spiring, F. A. (1988). A new measure of process capability Cpm. Journal of Quality Technology, 20(3), 162-175.4. Chen, S. M. and Hsu, N. F. (2005). The asymptotic distribution of the process capability index Cpmk. Communications in Statistics: Theory and Methods. 24(5), 1279-1291.5. Chen, J. P. and Tong, L. I. (2003). Bootstrap confidence interval of the difference between two process capability indices. International Journal of Advanced Manufacturing Technology, 21, 249-256.6. Chen, J. P. (2005). Comparing four lower confidence limits for process yield index . International Journal of Advanced Manufacturing Technology. 26(5), 609-614.7. Choi, K. C., Nam, K. H. and Park, D. H. (1996). Estimation of capability index based on bootstrap method. Microelectronics Reliability, 36(9), 1141-1153.8. Efron, B. (1979). Bootstrap methods: another look at the Jackknife. The Annals of Statis-tics, 7, 1-26.9. Efron, B. (1981). Nonparametric standard errors and confidence intervals. Canadian Journal of Statistics. 9, 139-172.10. Efron, B. (1982). The Jackknife, the bootstrap and other resampling plans. Society for In-dustrial and Applied Mathematics, Philadelphia, PA.11. Efron, B. and Tibshirani, R. J. (1986). Bootstrap methods for standard errors, confidence interval, and other measures of statistical accuracy. Statistical Science, 1, 54-77.12. Franklin, L. A. and Wasserman, G. S. (1992). Bootstrap lower confidence limits for capa-bility indices. Journal of Quality Technology, 24(4), 196-210.13. Hsiang, T. C. and Taguchi, G. (1985). A tutorial on quality control and assurance – the Taguchi methods. ASA Annual Meeting, Las Vegas, Nevada.14. Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41-52.15. Lee, J. C., Hung, H. N., Pearn, W. L. and Kueng, T. L. (2002). On the distribution of the estimated process yield index . Quality and Reliability Engineering International, 18(2), 111-116.16. Pearn, W. L., Kotz, S. and Johnson, N. L. (1992). Distributional and inferential properties of process capability indices. Journal of Quality Technology, 24(4), 216-231.17. Pearn, W. L., Lin, G. H. and Chen, K. S. (1998). Distributional and inferential properties of the process accuracy and process precision indices. Communications in Statistics: Theory and Methods, 27(4), 985-1000.18. Pearn, W. L. and Lin, P. C. (2002). Computer program for calculating the p-value in test-ing process capability index Cpmk. Quality and Reliability Engineering International, 18(4), 333-342.19. Pearn, W. L. and Shu, M. H. (2003). Lower confidence bounds with sample size infor-mation for Cpm with application to production yield assurance. International Journal of Production Research, 41(15), 3581-3599.20. Pearn, W. L., Lin, G. H. and Wang, K. H. (2004a). Normal approximation to the distribu-tion of the estimated yield index . Quality and Quantity, 38(1), 95-111.21. Pearn, W. L., Wu, C. /W. and Lin, H. C. (2004b). Procedure supplier selection based on Cpm applied to super twisted nematic liquid crystal display processes. International Journal of Production Research, 42(13), 2719-2734.22. Pearn, W. L., Wu, C. W. and Wang, K. H. (2005). Capability measure for asymmetric tol-erance non-normal processes applied to speaker driver manufacturing. The International Journal of Advanced Manufacturing Technology, 25(5-6), 506-515.23. Pearn, W. L., Chang, Y. C. and Wu, C. W. (2005). Bootstrap approach for estimating pro-cess quality yield with application to light emitting diodes. The International Journal of Advanced Manufacturing Technology, 25(5-6), 560-570.24. Pearn, W. L. and Cheng, Y. C. (2007). Estimating process yield based on for multi-ple samples. International Journal of Production Research, 45(1), 49-64.25. Pearn, W. L., Hui, N. H., Ya, C. C. and Gu, H. L. (2010). Procedure of convolution meth-od for estimating production yield with sample size information. International Journal of Production Research, 48(5), 1245-1265.26. Wright, P. A. (1998). The probability density function of process capability index Cpmk. Communications in Statistics – Theory and Methods, 27(7), 1781-1789.27. Wu, C. W., Shu, M. H., Pearn, W. L. and Liu, K. H. (2008). Bootstrap approach for sup-plier selection based on production yield. International Journal of Production Research, 46(18), 5211-5230.28. Wu, C. W. and Liao, M. Y. (2012). Generalized inference for measuring process yield with the contamination of measurement errors – quality control for silicon wafer manufacturing processes in semiconductor industry. IEEE Transactions on semiconductor manufacturing, 25(2), 272-283.
 國圖紙本論文
 連結至畢業學校之論文網頁點我開啟連結註: 此連結為研究生畢業學校所提供，不一定有電子全文可供下載，若連結有誤，請點選上方之〝勘誤回報〞功能，我們會盡快修正，謝謝！
 推文當script無法執行時可按︰推文 網路書籤當script無法執行時可按︰網路書籤 推薦當script無法執行時可按︰推薦 評分當script無法執行時可按︰評分 引用網址當script無法執行時可按︰引用網址 轉寄當script無法執行時可按︰轉寄

 1 以複式模擬法構建單一製程能力指標Cpmk之信賴下限及兩個製程能力指標Cpmk差異的信賴區間 2 製程能力指標Cpm和Cpp的統計推論與應用 3 單邊規格產品族製程能力指標 4 以複式模擬法構建製程良率之信賴區間 5 以複式模擬法構建非對稱規格區間下兩個製程能力指標C"pmk值差異之信賴區間 6 非對稱規格區間之製程能力指標的統計性質 7 非常態分配下製程能力指標之區間估計：以服務業應用為例 8 模糊推論於製程能力評估之研究 9 以複式模擬法建構兩個製程能力指標CNpmk差異之信賴區間 10 使用渴望函數的非對稱製程能力指標 11 多項品質特性產品之製程能力分析-以STN-LCD前段製程為例 12 以複式模擬法構建兩個製程能力指標Spmk差異值之信賴區間 13 以複式模擬法構建非常態下兩個製程能力指標CNpk差異值之信賴區間 14 製程能力指標Cpmk的應用 15 多變量製程能力指標之研究

 無相關期刊

 1 單邊規格多品質特性製程能力指標CpuT的信賴下限 2 雙邊規格多品質特性製程能力指標CpkT的信賴下界 3 製程能力指標Spk的近似不偏估計量 4 螞蟻族群演算法於電影拍攝排程之應用 5 問卷分析遺失值估計問題的探討 6 支援實習教師學習與工作的行動學習系統之介面設計與評鑑 7 市場動盪不安下的公司治理效應—以Moody’s公司治理報告為例 8 台灣上市櫃公司IPO之動機與財務結構之研究 9 ESCO產業之比較分析 10 駕駛者安全關鍵資訊之探究 11 求解大規模資料包絡分析問題 12 具工單等級之液晶注入排程問題研究 13 雙邊規格CNpk信賴下界複式抽樣計算方法 14 發展下一世代環保微影光罩結構材料 15 田口方法運用於太陽能光電模組散熱片設計研究

 簡易查詢 | 進階查詢 | 熱門排行 | 我的研究室