(3.235.108.188) 您好!臺灣時間:2021/03/03 19:26
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:蔡火炼
研究生(外文):FLORENCE LEONY
論文名稱:以製程損失在非常態分配資料下選擇製程
論文名稱(外文):Process Selection Based on Process Loss under Non-Normal Data
指導教授:林真如林真如引用關係
指導教授(外文):LIN, CHEN-JU
口試委員:陳雲岫孔令傑
口試委員(外文):CHEN, YUN-SHIOWKUNG, LING-CHIEH
口試日期:2020-07-13
學位類別:碩士
校院名稱:元智大學
系所名稱:工業工程與管理學系
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:2020
畢業學年度:108
語文別:英文
論文頁數:141
外文關鍵詞:multiple comparisonsprocess incapability indexbootstrapp-value
相關次數:
  • 被引用被引用:0
  • 點閱點閱:26
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
Chapter 1. Introduction 1
1.1 Background and Motivation 1
1.2 Research Objectives 3
1.3 Research Structure 3
Chapter 2. Literature Review 6
2.1 Process Capability Indices under Normal Data 6
2.1.1 Variance-Based 6
2.1.2 Yield-Based 8
2.1.3 Loss-Based 9
2.2 Process Capability Indices under Non-Normal Data 12
2.2.1 Variance-Based 12
2.2.2 Yield-Based 13
2.2.3 Loss-Based 14
2.3 PCI-based Process/ Supplier Selection 15
2.3.1 Under Normal Data 15
2.3.2 Under Non-Normal Data 18
2.4 Bootstrap Methods for Testing Ratio of Two Variances 19
2.5 Summary 20
Chapter 3. Methodology 21
3.1 Problem Statement 21
3.2 Simple Bonferroni Adjustment 22
3.3 The Cpp-based PO Bootstrap method 23
3.4 The Cpp-based F Distribution Method 26
Chapter 4. Simulation Analysis 28
4.1 Parameter Setting 28
4.1.1 Normal Distribution 28
4.1.2 Weibull Distribution 31
4.1.3 Uniform Distribution 32
4.1.4 Lognormal Distribution 33
4.1.5 Beta Distribution 35
4.1.6 Gamma Distribution 37
4.2 Type I Error Analysis 39
4.2.1 Type I Error under Normal Distribution 40
4.2.2 Type I Error under Weibull Distribution 47
4.2.3 Type I Error under Uniform Distribution 51
4.2.4 Type I Error under Lognormal Distribution 55
4.2.5 Type I Error under Beta Distribution 59
4.2.6 Type I Error under Gamma Distribution 69
Chapter 5. Power Analysis 76
5.1 Sensitivity Analysis on Combinations of Cia and Cip 76
5.1.1 Power under Normal distribution 76
5.1.2 Power under Weibull distribution 79
5.1.3 Power under Uniform distribution 81
5.1.4 Power under Lognormal distribution 84
5.1.5 Power under Beta distribution 86
5.1.6 Power under Gamma distribution 91
5.2 Sensitivity Analysis on Number of Worse Processes 94
5.2.1 Power minimum under Normal distribution 94
5.2.2 Power minimum under Weibull distribution 96
5.2.3 Power minimum under Uniform distribution 97
5.2.4 Power minimum under Lognormal distribution 98
5.2.5 Power minimum under Beta distribution 99
5.2.6 Power minimum under Gamma distribution 101
Chapter 6. Conclusions 103
6.1 Conclusion 103
6.2 Limitation and Future Research 104

[1]Ahmed, S.E. (2005). Assessing the process capability index for non-normal processes. Journal of Statistical Planning and Inference, 129(1–2), 195–206.
[2]Bonferroni, C.E. (1936). Teoria statistica delle classi e calcolo delle probabilità. Pubblicazioni Del R Istituto Superiore Di Scienze Economiche E Commericiali Di Firenze, 8, 1–62
[3]Boos, D.D. & Brownie, C. (1989). Bootstrap methods for testing homogeneity of variances. Technometrics, 31, 69–82.
[4]Boyles, R.A. (1991). The Taguchi capability index. Journal of Quality Technology, 23, 17–26.
[5]Boyles, R.A. (1994). Process capability with asymmetric tolerance. Communication in Statistics-Simulation and Computation, 23, 615-643.
[6]Burch, B.D. (2012). Nonparametric Bootstrap Confidence Intervals for Variance Components Applied to Interlaboratory Comparisons. Journal of Agricultural, Biological, and Environmental Statistics, 17(2), 228–245.
[7]Chan, L.K., Cheng, S.W., & Spiring, F.A. (1988). A new measure of process capability: Cpm. Journal of Quality Technology, 20(3), 162–175.
[8]Chan, L.K., Xiong, Z., & Zhang, D. (1990). On the asymptotic distributions of some process capability indices. Communications in Statistics – Theory and Methods, 19(1), 11–18.
[9]Chen, J.-P. & Chen, K.S. (2004). Comparison of two process capabilities by using indices Cpm: an application to a color STN display. International Journal of Quality & Reliability Management, 21(1). 90–101.
[10]Chen, J.-P. & Ding, C.G. (2001). A new process capability index for non-normal distributions. International Journal of Quality and Reliability Management, 18(7), 762–770.
[11]Chen, J.-P. & Tong, L.-I. (2003). Bootstrap confidence interval of the difference between two process capability indices. International Journal of Advanced Manufacturing Technology, 21, 249–256.
[12]Chen, K.S. (1998). Estimation of the process incapability index. Communications in Statistics – Theory and Methods, 27(5), 1263–1274.
[13]Chen, K.S. & Chen, K.L. (2006). Supplier selection by testing process incapability indices. International Journal of Production Research, 44(3), 589–600.
[14]Chen, K.L., Chen, K.S., & Li, R.K. (2005a). Suppliers capability and price analysis chart. International Journal of Production Economics, 98, 315–327.
[15]Chen, K.S., Chen, K.L., & Li, R.K. (2005b). Contract manufacturer selection by using the process incapability index Cpp. The International Journal of Advanced Manufacturing Technology, 26, 686–692.
[16]Chen, K.S. & Pearn, W.L. (1997). An application of non-normal process capability indices. Quality and Reliability Engineering International, 13, 355–360.
[17]Cheng, S.W. (1994). Practical implementation of the process capability indices. Quality Engineering, 7(2), 239–259.
[18]Cho, J.J., Han, J.H., & Lee, I.P. (1999). Better bootstrap confidence intervals for process incapability index Cpp. Journal of Korean Data & Information Science Society, 10(2), 341–357.
[19]Choi, K.C., Nam, K.H., & Park, D.H. (1995). Estimation of capability index based on bootstrap method. Microelectronics Reliability, 36(9), 1141–1153.
[20]Chou, C.-Y., Lin, Y.-C., Chang, C.-L., & Chen C-H. (2006). On the bootstrap confidence intervals of the process incapability index Cpp. Reliability Engineering and System Safety, 91(4), 452–459.
[21]Chou, Y.-M. & Owen, D.B. On the distributions of the estimated process capability indices. Communications in Statistics – Theory and Methods, 18(12), 4549–4560.
[22]Chou, Y.-M. (1994). Selecting a better supplier by testing process capability indices. Quality Engineering, 6(3), 427–438.
[23]Clement,s J.A. (1989) Process capability calculations for non-normal distributions. Quality Progress, 22(9), 95–100.
[24]Daniels, L., Edgar, B., Burdick, R.K., & Hubele, N.F. (2004). Using confidence intervals to compare process capability indices. Quality Engineering, 17(1), 23–32.
[25]Efron, B. & Tibshirani, R. (1986). Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Statistical Science, 1, 54 –75.
[26]Franklin, L.A. & Wasserman, G.S. (1992). Bootstrap lower confidence limits for capability indices. Journal of Quality Technology, 24(4), 196–210.
[27]Greenwich, M. & Jahr-Schaffrath, B.L. (1995). A process incapability index. International Journal of Quality and Reliability Management, 12(4), 58–71.
[28]Hall, P. & Wilson, S. R. (1991). Two guidelines for bootstrap hypothesis testing. Biometrics 47(2), 757–762.
[29]Huang, D.-Y., Lee, R.F. (1995). Selecting the largest capability index from several quality control processes. Journal of Statistical Planning and Inference, 46(3), 335–346.
[30]Hubele, N.F., Berrado, A., & Gel, E.S. (2005). A Wald test for comparing multiple capability indices. Journal of Quality Technology, 37(4), 304–307.
[31]Johnson, N.L., Kotz, S., & Pearn, W.L. (1994). Flexible process capability indices. Pakistan Journal of Statistics, 10(1A), 23–31.
[32]Johnson, T. (1991). A new measure of process capability related to Cpm (M.S. thesis). North Carolina University, Raleigh.
[33]Johnson, T. (1992). The Relationship of Cpm to Squared Error Loss. Journal of Quality Technology, 24, 211–215.
[34]Juran Institute. (1990). The tools of quality, part IV: Histograms. Quality Progress, 9, 75–78.
[35]Juran, J.M. (1974). Quality Control Handbook. New York: McGraw-Hill.
[36]Kane, V.E. (1986). Process capability indices. Journal of Quality Technology, 18, 41–52.
[37]Kanichukattu, J.K. & Luke, J.A. (2013). Comparison between two process capability indices using generalized confidence intervals. International Journal of Advanced Manufacturing Technology, 69, 2793–2798.
[38]Ke, et al. (2009). Assessing non-normally distributed processes by interval estimation of the incapability index Cpp. Quality and Reliability Engineering International, 25, 427–437.
[39]Kotz, S. & Johnson, N.L. (1993). Process Capability Indices. London: Chapman & Hall.
[40]Lee, J.C., Hung, H.N., Pearn, W.L., & Kueng, T.L. (2002). On the distribution of the estimated process yield index Spk. Quality and Reliability Engineering International, 18(2), 111–116.
[41]Lin, C.-J., & Kuo, H.-H. (2014). Multiple comparisons with the best for supplier selection. Quality and Reliability Engineering International, 30, 1083–1092.
[42]Lin, C.-J., & Pearn, W.L. (2011). Group selection for production yield among k manufacturing lines. Journal of Statistical Planning and Inference, 141, 1510–1518.
[43]Lin, G.H. (2004). Upper limits of the estimated incapability index: a practical application on the reliability assessment of printed circuit boards. The International Journal of Advanced Manufacturing Technology, 24, 841–846.
[44]Lin, G.H. (2005). Process reliability assessment with a bayesian approach. The International Journal of Advanced Manufacturing Technology, 25, 392–395.
[45]Luceño, A. (1996). A process capability index with reliable confidence intervals. Communications in Statistics – Simulation and Computation, 25(1), 235–245.
[46]Marron, J.S. & Wand, M.P. (1992). Exact mean integrated squared error. The Annals of Statistics, 20(2), 712–736.
[47]Ng, K.K. & Tsui, K.-L. (1992). Expressing variability and yield with a focus on the customer. Quality Engineering, 5(2), 255–267.
[48]Pan, J.N. & Wu, S.L. (1997). Process capability analysis for non-normal relay test data. Microelectronics Reliability, 37(3), 421–428.
[49]Pearn, W.L., Chang, Y.C., & Wu, C.-W. (2006). Multiple-process performance analysis chart based on process loss indices. International Journal of Systems Science, 37(7), 429–435.
[50]Pearn, W.L., Chang, Y.C., & Wu, C.-W. (2006). Multiple-process performance based on expected loss with asymmetric tolerances. Journal of Applied Statistics, 33(10), 1105–1120.
[51]Pearn, W.L. & Chen, K.S. (1997). A practical implementation of the process capability index Cpk. Quality Engineering, 9(4), 721–737.
[52]Pearn, W.L., Chen K.L., Ko, C.H. (1999). A practical implementation of the process incapability index Cpp. Journal of the Chinese Institute of Industrial Engineers, 16(4), 519–531.
[53]Pearn, W.L., Hung, H.N., & Cheng, Y.C. (2009). Supplier selection for one-sided processes with unequal sample sizes. European Journal of Operational Research, 195(2), 381–393.
[54]Pearn, W.L., Ko, C.H., & Wang, K.H. (2002). A multiprocess performance analysis chart based on incapability index Cpp: and application to the chip resistor. Microelectronics Reliability, 42(7), 1121–1125.
[55]Pearn, W.L., Kotz, S., & Johnson, N.L. (1992) Distributional and inferential properties of process capability indices. Journal of Quality Technology, 24(4), 216–231.
[56]Pearn, W.L. & Lin, G.H. (2001). On the reliability of the estimated process incapability index. Quality and Reliability Engineering International, 17, 279–290.
[57]Pearn, W.L. & Lin, G.H. (2001). Estimated incapability index: reliability and dicision making with sample information. Quality and Reliability Engineering International, 18, 141–147.
[58]Pearn, W.L., & Lin, P.C. (2004). Testing process performance based on capability index Cpk with critical values. Computers & Industrial Engineering, 47, 351–369.
[59]Pearn, W.L, Wu, C.W., & Lin, H.C. (2004). Procedure for supplier selection based on Cpm applied to super twisted nematic liquid crystal display processes. International Journal of Production Research, 42(13), 2719–2734.
[60]Polansky, A.M. (2003). Supplier selection based on bootstrap confidence regions of process capability indices. International Journal of Reliability, Quality and Safety Engineering, 10(1), 1–14.
[61]Polansky, A.M. (2006). Permutation methods for comparing process capabilities. Journal of Quality Technology, 38(3), 254–266.
[62]Saha, M., Dey, S., & Maiti, S.S. (2018). Parametric and non-parametric bootstrap confidence intervals of CNpk for Exponential power distribution. Journal of Industrial and Production Engineering.
[63]Somerville, S.E. & Montgomery, D.C. (1996-97). Process capability indices and non-normal distributions. Quality Engineering, 9(2), 305–316.
[64]Taguchi, G. (1985). A tutorial on quality and assurance: the Taguchi methods. ASA Annual Meeting, Las Vegas, NV.
[65]Tang, L.C. & Than, S.E. (1999). Computing process capability indices for non-normal data: a review and comparative study. Quality and Reliability Engineering International, 15, 339–353.
[66]Thorpe, D.P., Holland, B. (2000). Some multiple comparison procedures for variances from non-normal populations. Computational Statistics & Data Analysis, 35, 171–199.
[67]Tong, L.-I., Chen, H.-T., & Tai, Y.-F. (2008). Constructing BCa bootstrap confidence interval for the difference between two non-normal process capability indices CNpmk. Quality Engineering, 20, 209–220.
[68]Tseng, S.T. & Wu, T.Y. (1991). Selecting the best manufacturing process. Journal of Quality Technology, 23(1), 53–62.
[69]Tsui, K.-L. (1997). Interpretation of process capability indices and some alternatives. Quality Engineering, 9(4), 587–596.
[70]Sun, J., Chernick, M.R., & LaBudde, R.A. (2011). A bootstrap test for comparing two variances: simulation of size and power in small samples. Journal of Biopharmaceutical Statistics, 21, 1079–1093.
[71]Vӓnnman, K. (1995). A unified approach to capability indices. Statistica Sinica, 5, 805–820.
[72]Westfall, P.H. & Young, S.S. (1993). Resampling-Based Multiple Testing. Wiley, New York.
[73]Wu, C.-W. & Huang, P.H. (2010). Generalized confidence intervals for comparing the capability of two processes. Communications in Statistics – Theory and Methods, 39(13), 2351–2364.
[74]Wu, C.-W. & Lin, T.-Y. (2009). A bayesian procedure for assessing process performance based on the third-generation capability index. Journal of Applied Statistics, 36(11), 1205–1223.
[75]Wu, C.-W., Shiau, J.-J.H., Pearn, W.L., & Hung, H.-N. (2016). A bayesian approach for group supplier selections based on the popular process-capability-index Cpk. Quality Technology & Quantitative Management, 13(2), 109–123.
[76]Wu, C.-W., Shu, M.H., Pearn, W.L., & Liu, K.H. (2008). Bootstrap approach for supplier selection based on production yield. International Journal of Production Research, 46(18), 5211–5230.
[77]Wu, H.-H., Swain, J.J., & Farrington, P.A. & Messimer SL. (1999). A weighted variance capability index for general non-normal processes. Quality and Reliability Engineering International, 15(5), 397–402.
[78]Wu, H.-H. & Swain, J.J. (2001). A Monte Carlo comparison of capability indices when processes are non-normally distributed. Quality and Reliability Engineering International, 17, 219–231.

電子全文 電子全文(網際網路公開日期:20250730)
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關論文
 
無相關期刊
 
無相關點閱論文
 
系統版面圖檔 系統版面圖檔