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研究生:Yeneneh Tamirat Negash
研究生(外文):Yeneneh Tamirat Negash
論文名稱:製程良率分析於單變量與多變量剖面資料
論文名稱(外文):Process Yield Analysis for Single and Multivariate Profiles
指導教授:王福琨王福琨引用關係
指導教授(外文):Professor Fu-Kwun Wang
口試委員:王福琨
口試委員(外文):Professor Fu-Kwun Wang
口試日期:2015-06-02
學位類別:博士
校院名稱:國立臺灣科技大學
系所名稱:工業管理系
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:英文
論文頁數:185
中文關鍵詞:剖面資料製程良率雙邊規格單邊規格自我相關比率檢定統計量多重比較方法
外文關鍵詞:profilesprocess–yield indexone-sided specificationstwo-sided specificationsautocorrelationratio test statisticmultiple comparisons with the best
相關次數:
  • 被引用被引用:0
  • 點閱點閱:238
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  • 下載下載:31
  • 收藏至我的研究室書目清單書目收藏:0
在許多工業應用中,若製程或產品的品質的特徵是由一個反應變數和一個或多個解釋變數的關係以函數來解釋之,則稱為剖面資料。單一的剖面資料可能包含數百或數千剖面。確保具有剖面資料的製程良率是非常重要的任務。
本論文提出製程良率分析於剖面資料及其供應商選擇的應用研究。本研究包含了八個議題的研究成果,在第二章是處理傳統製程良率於資料具相關性的研究。第三章和第四章處理製程良率於剖面資料具自我相關與剖面資料間具自我相關的研究。在剖面資料遵循自相相關回歸模型AR(1)下得到近似製程能力指標 的信賴下界。第五章中提出於單邊製程規格線性剖面資料時,互相獨立常態分配下的新指標 和 及常態分配下的新指標 和 ,這些指標可以提升製程產出的精確度。此外建構近似常態分配的兩個指標 和 。第七章與第八章是線性剖面於雙邊製規格和單邊規格時,以比率檢定統計量為基礎的指標,來比較兩個供應商的製程良率,有比率檢定統計的統計性質與提供在特訂的檢定力和信心水準下剖面資料數量的計算。第九章是利用多重比較方法對於多個供應商( )的製程良率評選。最後是結論以及對於未來研究的建議。
In many industrial applications, the quality of a process or product can be characterized by a functional relationship between a response variable and one or more explanatory variables which is referred to as profile. A single profile may contain hundred or thousand data points. Assuring the process capability for profiles to meet the requirement is a very important task.
This dissertation presents contributions within the field of process yield analysis, profile monitoring, and process selection for profiles. Eight papers one in each chapter are incorporated in this dissertation. In Chapter 2 the distribution for the process-yield index Spk is developed for autocorrelated process data. Thus, the lower confidence bound can be easily obtained for decision making. The aim of Chapters 3 and 4 is to evaluate the process yield for autocorrelation between profiles and correlation within a profile respectively. We derive an approximate lower confidence bound for the process-yield index SpkA;AR(1) when linear profiles follow an autoregressive model AR(1). In Chapter 5 two new indices CTpuA and CTplA for mutually independent normality and two new indices CTpuA;pc and CTplA;pc for multivariate normality are proposed to measure the process capability for multivariate linear profiles with one-sided specifications. These indices can provide an exact measure of the process yield. The approximate normal distributions for CTpuA and CTplA are constructed. Chapters 6 & 7 propose the ratio test statistic based on the process yield index to compare two suppliers for linear profiles with two-sided and one-sided specification limits respectively. The statistical properties of the ratio test statistic are presented. Critical values of the tests are calculated to determine the selection decisions. The number of profiles required for a designated selection power and confidence level is also investigated. Chapters 8 and 9 propose the multiple comparisons with the best method based on the process-yield index to tackle process selection problem among K (k>=2) alternatives. The power analysis is conducted. The required numbers of profiles for different power levels are also provided. Finally, the achievement and contributions of this dissertation are summarized in Chapter 10.
Table of Content
摘要 i
Abstract ii
Acknowledgement iii
Table of Content v
List of Figures viii
List of Tables ix
Chapter 1 1
Introduction 1
1.1 Process Capability 1
1.2 Profile Analysis and Applications 2
1.3 Process Capability Indices for Profiles 4
1.4 Research Objectives 8
1.4.1 Specific Objectives 8
1.5 Organization 9
References 11
Chapter 2 14
Lower Confidence Bound for Process-Yield Index
with Autocorrelated Process Data 14
Abstract 14
2.1 Introduction 14
2.2 Process-Yield Index with Autocorrelated Process Data 16
2.3 Simulation Study 20
2.4 Illustrative Examples 29
2.5 Conclusion 32
References 32
Chapter 3 35
Process Yield Analysis for Autocorrelation between
Linear Profiles 35
Abstract 35
3.1 Introduction 35
3.2 Process-yield Index and Lower Confidence Limit 37
3.3 Simulation Study 41
3.4 Illustrative Example 44
3.5 Conclusion 49
References 50
Appendix 51
Chapter 4 56
Process Yield Analysis for Linear Within-Profile
Autocorrelation 56
Abstract 56
4.1 Introduction 56
4.2 Process-Yield Index for Within-Profile Autocorrelation 59
4.3 Simulation Study 63
4.4 Illustrative Example 67
4.5 Conclusion 68
References 68
Appendix: 70
Chapter 5 73
Process Yield for Multivariate Profiles with One-Sided
Specifications 73
Abstract 73
5.1 Introduction 73
5.2 Process Yield Indices for Multivariate Linear Profiles 75
5.2.1 Mutually Independent Normality Case 75
5.3.2 Multivariate Normality Case 81
5.3 Simulation Study 83
5.4 Illustrative Examples 90
5.5 Conclusions and Future Research 93
References 94
Chapter 6 96
Implementing the Ratio Test Statistic to Compare Two
Suppliers for Linear Profiles 96
Abstract 96
6.1 Introduction 96
6.2 Review on the Process-Yield Index for Linear Profiles 97
6.3 Proposed Method 99
6.3.1 Statistical Properties of the Ratio Test Statistic 99
6.3.2 Testing Cases 102
6.3.3 The Number of Profiles Required 106
6.4 Comparison Study 107
6.5 Illustrative Examples 109
6.6 Conclusion 112
References 112
Chapter 7 114
Process Selection for Linear Profiles with One-Sided
Specifications Based on the Ratio Test Statistic 114
Abstract 114
7.1 Introduction 115
7.2 Process Yield Indices for Linear Profiles with
One-Sided Specifications 116
7.3 Supplier Selection Procedure 121
7.3.1 Ratio Test Statistic 121
7.3.2 Selection Determination 124
7.3.3 The number of Profiles Required 129
7.4 Illustrative Examples 131
7.5 Conclusion 133
References 133
Appendix: 134
Chapter 8 137
Multiple Comparisons with the Best for Supplier
Selection with Linear Profiles 137
Abstract 137
8.1 Introduction 137
8.2 The Process-Yield Index SpkA for Linear Profiles 139
8.3 An MCB Method for Supplier Selection 141
8.4 Performance Analysis 143
8.4.1 Statistical Power Analysis 143
8.4.2 The Number of Profiles Required 146
8.4.3 Simulation Study 148
8.5 Illustrative Examples 149
8.6 Summary and Concluding Remarks 152
References 152
Chapter 9 154
Multiple Comparisons with the Best for Process Selection
for Linear Profiles with One-Sided Specifications 154
Abstract 154
9.1 Introduction 154
9.2 The Process-Yield Indices for Linear Profiles
with One-Sided Specifications 155
9.3 An MCB Method for Supplier Selection 158
9.4 Performance Analysis 160
9.4.1 Power Analysis 160
9.4.2 The Number of Profiles Required 161
9.5 Illustrative Example 164
9.6 Conclusion 165
References 166
Chapter 10 168
Conclusion and Future Study 168
10.1 Conclusion 168
10.2 Future Study 170
Brief Introduction of the Author 171
Chapter 1
References

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5.Boyles, R.A., Process capability with asymmetric tolerances. Communications in Statistics-Simulation and Computation, 1994. 23(3): p. 615-635.
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7.Constable, G. and J. Hobbs. Small samples and non-normal capability. in ASQC Quality Congress Transactions. 1992.
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10.Kotz, S. and N.L. Johnson, Process capability indices. 1993: CRC Press.
11.Pearn, W. and S. Kotz, Encyclopedia and handbook of process capability indices: a comprehensive exposition of quality control measures. 2006: World Scientific Hackensack, NJ.
12.Shore, H., Process capability analysis when data are autocorrelated. Quality Engineering, 1997. 9(4): p. 615-626.
13.Zhang, N.F., Estimating process capability indexes for autocorrelated data. Journal of Applied Statistics, 1998. 25(4): p. 559-574.
14.Wallgren, E., Confidence limits for the process capability index C pk for autocorrelated quality characteristics, in Frontiers in Statistical Quality Control 6. 2001, Springer. p. 312-331.
15.Wallgren, E., A generalization of the Taguchi capability index for data generated by a first order moving average process. Statistical Mtehods, 2001. 3(1): p. 1-16.
16.Noorossana, R., Process capability analysis in the presence of autocorrelation. Quality and Reliability Engineering International, 2002. 18(1): p. 75-77.
17.Vännman, K. and M. Kulahci, A model‐free approach to eliminate autocorrelation when testing for process capability. Quality and reliability engineering international, 2008. 24(2): p. 213-228.
18.Lovelace, C.R., et al., Lower confidence limits for process capability indices Cp and Cpk when data are autocorrelated. Quality and Reliability Engineering International, 2009. 25(6): p. 663-700.
19.Sun, J., S. Wang, and Z. Fu, Process capability analysis and estimation scheme for autocorrelated data. Journal of Systems Science and Systems Engineering, 2010. 19(1): p. 105-127.
20.Lundkvist, P., K. Vännman, and M. Kulahci, A comparison of decision methods for C pk when data are autocorrelated. Quality Engineering, 2012. 24(4): p. 460-472.
21.Noorossana, R., A. Saghaei, and A. Amiri, Statistical analysis of profile monitoring. Vol. 865. 2011: John Wiley & Sons.
22.Montgomery, D.C., Statistical Quality Control: A Modern Introduction. 2013, Singapore: Wiley.
23.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
24.Jin, J. and J. Shi, Feature-preserving data compression of stamping tonnage information using wavelets. Technometrics, 1999. 41(4): p. 327-339.
25.Kang, L. and S.L. Albin, On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 2000. 32(4): p. 418-426.
26.Walker, E. and S.P. Wright, Comparing curves using additive models. Journal of Quality Technology, 2002. 34(1): p. 118-129.
27.Gupta, S., D. Montgomery, and W. Woodall, Performance evaluation of two methods for online monitoring of linear calibration profiles. International Journal of Production Research, 2006. 44(10): p. 1927-1942.
28.Amiri, A., W.A. Jensen, and R.B. Kazemzadeh, A case study on monitoring polynomial profiles in the automotive industry. Quality and Reliability Engineering International, 2010. 26(5): p. 509-520.
29.Paynabar, K. and J. Jin, Characterization of non-linear profiles variations using mixed-effect models and wavelets. IIE Transactions, 2011. 43(4): p. 275-290.
30.Chang, S.I., et al., Statistical process control for monitoring nonlinear profiles: a six sigma project on curing process. Quality Engineering, 2012. 24(2): p. 251-263.
31.Parker, P.A., et al. A single-vector force calibration method featuring the modern design of experiments. in 39 th AIAIA Aerospace Sciences Meeting and Exhibit, Reno Nevada. 2001.
32.Eyvazian, M., et al., Phase II monitoring of multivariate multiple linear regression profiles. Quality and Reliability Engineering International, 2011. 27(3): p. 281-296.
33.Chou, S.H., Quality engineering applications on single and multiple nonlinear profiles, in Industrial and Manufacturing Systems Engineering. 2014, Kansan State: Manhattan, Kansas.
34.Shahriari, H. and M. Sarrafian. Assessment of process capability in linear profiles. in Proceedings of the 6th International Industrial Engineering Conference, Tehran, Iran (in Farsi). 2009.
35.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
36.Hosseinifard, S.Z. and B. Abbasi, Process capability analysis in non normal linear regression profiles. Communications in Statistics-Simulation and Computation, 2012. 41(10): p. 1761-1784.
37.Ebadi, M. and H. Shahriari, A process capability index for simple linear profile. International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): p. 857-865.
38.Wang, F.K., A Process Yield for Simple Linear Profiles. Quality Engineering, 2014. 26(3): p. 311-318.
39.Wang, F.K. and Y.C. Guo, Measuring process yield for nonlinear profiles. Quality and Reliability Engineering International, 2014. 30(8): p. 1333-1339.
40.Ebadi, M. and A. Amiri, Evaluation of process capability in multivariate simple linear profiles. Scientia Iranica, 2012. 19(6): p. 1960-1968.
41.Wang, F.K., Process yield for multivariate linear profiles. Quality Technology and Quantitative Management, 2014(in press).
42.Albing, M., Contributions to process capability indices and plots, in Mathematics. 2008, Luleå University of Technology: Sweden.
43. Wang, F.K., Process yield analysis for a process with profiles. Working Paper, National Taiwan University of Science and Technology, Taipei, Taiwan, 2015.

Chapter 2
References

1.Boyles, R.A., Process capability with asymmetric tolerances. Communications in Statistics-Simulation and Computation, 1994. 23(3): p. 615-635.
2.Montgomery, D.C., Statistical Quality Control: A Modern Introduction. 2013, Singapore: Wiley.
3.Psarakis, S. and G. Papaleonida, SPC procedures for monitoring autocorrelated processes. Quality Technology and Quantitative Management, 2007. 4(4): p. 501-540.
4.Scagliarini, M., Estimation of C p for autocorrelated data and measurement errors. Communications in Statistics-Theory and Methods, 2002. 31(9): p. 1647-1664.
5.Shore, H., Process capability analysis when data are autocorrelated. Quality Engineering, 1997. 9(4): p. 615-626.
6.Zhang, N.F., Estimating process capability indexes for autocorrelated data. Journal of Applied Statistics, 1998. 25(4): p. 559-574.
7.Wallgren, E., Confidence limits for the process capability index C pk for autocorrelated quality characteristics, in Frontiers in Statistical Quality Control 6. 2001, Springer. p. 312-331.
8.Wallgren, E., A generalization of the Taguchi capability index for data generated by a first order moving average process. Statistical Mtehods, 2001. 3(1): p. 1-16.
9.Noorossana, R., Process capability analysis in the presence of autocorrelation. Quality and Reliability Engineering International, 2002. 18(1): p. 75-77.
10.Vännman, K. and M. Kulahci, A model‐free approach to eliminate autocorrelation when testing for process capability. Quality and Reliability Engineering International, 2008. 24(2): p. 213-228.
11.Lovelace, C.R., et al., Lower confidence limits for process capability indices Cp and Cpk when data are autocorrelated. Quality and Reliability Engineering International, 2009. 25(6): p. 663-700.
12.Sun, J., S. Wang, and Z. Fu, Process capability analysis and estimation scheme for autocorrelated data. Journal of Systems Science and Systems Engineering, 2010. 19(1): p. 105-127.
13.Lundkvist, P., K. Vännman, and M. Kulahci, A comparison of decision methods for Cpk when data are autocorrelated. Quality Engineering, 2012. 24(4): p. 460-472.
14.Lee, J., et al., On the distribution of the estimated process yield index Spk. Quality and Reliability Engineering International, 2002. 18(2): p. 111-116.
15.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.

Chapter 3

References
1.Kang, L. and S.L. Albin, On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 2000. 32(4): p. 418-426.
2.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
3.Noorossana, R., A. Saghaei, and A. Amiri, Statistical analysis of profile monitoring. Vol. 865. 2011: John Wiley & Sons.
4.Chuang, S.C., et al., A framework for nonparametric profile monitoring. Computers & Industrial Engineering, 2013. 64(1): p. 482-491.
5.Ghahyazi, M.E., S.T.A. Niaki, and P. Soleimani, On the monitoring of linear profiles in multistage processes. Quality and Reliability Engineering International, 2014. 30(7): p. 1035-1047.
6.Li, Z. and Z. Wang, An exponentially weighted moving average scheme with variable sampling intervals for monitoring linear profiles. Computers & Industrial Engineering, 2010. 59(4): p. 630-637.
7.Noorossana, R., M. Eyvazian, and A. Vaghefi, Phase II monitoring of multivariate simple linear profiles. Computers & Industrial Engineering, 2010. 58(4): p. 563-570.
8.Noorossana, R., A. Vaghefi, and M. Dorri, Effect of non‐normality on the monitoring of simple linear profiles. Quality and Reliability Engineering International, 2011. 27(4): p. 425-436.
9.Zhang, Y., et al., Control charts for monitoring linear profiles with within‐profile correlation using Gaussian process models. Quality and Reliability Engineering International, 2014. 30(4): p. 487-501.
10.Kazemzadeh, R., R. Noorossana, and A. Amiri, Phase II monitoring of autocorrelated polynomial profiles in AR (1) processes. Scientia Iranica Transaction E: Industrial Engineering, 2010. 17(1): p. 12-24.
11.Noorossana, R., A. Amiri, and P. Soleimani, On the monitoring of autocorrelated linear profiles. Communications in Statistics—Theory and Methods, 2008. 37(3): p. 425-442.
12.Soleimani, P., R. Noorossana, and A. Amiri, Simple linear profiles monitoring in the presence of within profile autocorrelation. Computers & Industrial Engineering, 2009. 57(3): p. 1015-1021.
13.Shahriari, H. and M. Sarrafian. Assessment of process capability in linear profiles. in Proceedings of the 6th International Industrial Engineering Conference, Tehran, Iran (in Farsi). 2009.
14.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
15.Hosseinifard, S.Z. and B. Abbasi, Process capability analysis in non normal linear regression profiles. Communications in Statistics-Simulation and Computation, 2012. 41(10): p. 1761-1784.
16.Ebadi, M. and H. Shahriari, A process capability index for simple linear profile. International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): p. 857-865.
17.Wang, F.K., A Process Yield for Simple Linear Profiles. Quality Engineering, 2014. 26(3): p. 311-318.
18.Wang, F.K. and Y.C. Guo, Measuring process yield for nonlinear profiles. Quality and Reliability Engineering International, 2014. 30(8): p. 1333-1339.
19.Shore, H., Process capability analysis when data are autocorrelated. Quality Engineering, 1997. 9(4): p. 615-626.
20.Zhang, N.F., Estimating process capability indexes for autocorrelated data. Journal of Applied Statistics, 1998. 25(4): p. 559-574.
21.Wallgren, E., Confidence limits for the process capability index Cpk for autocorrelated quality characteristics, in Frontiers in Statistical Quality Control 6. 2001, Springer. p. 312-331.
22.Wallgren, E., A generalization of the Taguchi capability index for data generated by a first order moving average process. Statistical Methods, 2001. 3(1): p. 1-16.
23.Noorossana, R., Process capability analysis in the presence of autocorrelation. Quality and Reliability Engineering International, 2002. 18(1): p. 75-77.
24.Vännman, K. and M. Kulahci, A model‐free approach to eliminate autocorrelation when testing for process capability. Quality and Reliability Engineering International, 2008. 24(2): p. 213-228.
25.Lovelace, C.R., et al., Lower confidence limits for process capability indices Cp and Cpk when data are autocorrelated. Quality and Reliability Engineering International, 2009. 25(6): p. 663-700.
26.Sun, J., S. Wang, and Z. Fu, Process capability analysis and estimation scheme for autocorrelated data. Journal of Systems Science and Systems Engineering, 2010. 19(1): p. 105-127.
27.Lundkvist, P., K. Vännman, and M. Kulahci, A comparison of decision methods for C pk when data are autocorrelated. Quality Engineering, 2012. 24(4): p. 460-472.
28.Boyles, R.A., Brocess capability with asymmetric tolerances. Communications in Statistics-Simulation and Computation, 1994. 23(3): p. 615-635.
29.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.
30.Croarkin, C. and P. Tobias, NIST/SEMATECH e-handbook of statistical methods. NIST/SEMATECH. Available online: http://www. itl. nist. gov/div898/handbook, 2010.
31.Lee, J., et al., On the distribution of the estimated process yield index Spk. Quality and Reliability Engineering International, 2002. 18(2): p. 111-116.

Chapter 4
References

1.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
2.Noorossana, R., A. Saghaei, and A. Amiri, Statistical analysis of profile monitoring. Vol. 865. 2011: John Wiley & Sons.
3.Noorossana, R., A. Vaghefi, and M. Dorri, Effect of non‐normality on the monitoring of simple linear profiles. Quality and Reliability Engineering International, 2011. 27(4): p. 425-436.
4.Kang, L. and S.L. Albin, On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 2000. 32(4): p. 418-426.
5.Noorossana, R., A. Amiri, and P. Soleimani, On the monitoring of autocorrelated linear profiles. Communications in Statistics—Theory and Methods, 2008. 37(3): p. 425-442.
6.Kazemzadeh, R., R. Noorossana, and A. Amiri, Phase II monitoring of autocorrelated polynomial profiles in AR (1) processes. Scientia Iranica Transaction E: Industrial Engineering, 2010. 17(1): p. 12-24.
7.Jensen, W.A., J.B. Birch, and W.H. Woodall, Monitoring correlation within linear profiles using mixed models. Journal of Quality Technology, 2008. 40(2): p. 167-183.
8.Jensen, W.A. and J.B. Birch, Profile monitoring via nonlinear mixed models (vol 41, pg 18, 2009). Journal of Quality Technology, 2009. 41(3): p. 321-321.
9.Amiri, A., W.A. Jensen, and R.B. Kazemzadeh, A case study on monitoring polynomial profiles in the automotive industry. Quality and Reliability Engineering International, 2010. 26(5): p. 509-520.
10.Soleimani, P., R. Noorossana, and A. Amiri, Simple linear profiles monitoring in the presence of within profile autocorrelation. Computers & Industrial Engineering, 2009. 57(3): p. 1015-1021.
11.Qiu, P., C. Zou, and Z. Wang, Nonparametric profile monitoring by mixed effects modeling. Technometrics, 2010. 52(3).
12.Narvand, A., P. Soleimani, and S. Raissi, Phase II monitoring of auto-correlated linear profiles using linear mixed model. Journal of Industrial Engineering International, 2013. 9(1): p. 1-9.
13.Zhang, Y., et al., Control charts for monitoring linear profiles with within‐profile correlation using Gaussian process models. Quality and Reliability Engineering International, 2014. 30(4): p. 487-501.
14.Shahriari, H. and M. Sarrafian. Assessment of process capability in linear profiles. in Proceedings of the 6th International Industrial Engineering Conference, Tehran, Iran (in Farsi). 2009.
15.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
16.Hosseinifard, S.Z. and B. Abbasi, Process capability analysis in non normal linear regression profiles. Communications in Statistics-Simulation and Computation, 2012. 41(10): p. 1761-1784.
17.Ebadi, M. and H. Shahriari, A process capability index for simple linear profile. International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): p. 857-865.
18.Wang, F.K., A process yield for simple linear profiles. Quality Engineering, 2014. 26(3): p. 311-318.
19.Wang, F.K. and Y.C. Guo, Measuring process yield for nonlinear profiles. Quality and Reliability Engineering International, 2014. 30(8): p. 1333-1339.
20.Shore, H., Process capability analysis when data are autocorrelated. Quality Engineering, 1997. 9(4): p. 615-626.
21.Zhang, N.F., Estimating process capability indexes for autocorrelated data. Journal of Applied Statistics, 1998. 25(4): p. 559-574.
22.Wallgren, E., Confidence limits for the process capability index Cpk for autocorrelated quality characteristics, in Frontiers in Statistical Quality Control 6. 2001, Springer. p. 312-331.
23.Wallgren, E., A generalization of the Taguchi capability index for data generated by a first ordermoving average process. Statistical Mtehods, 2001. 3(1): p. 1-16.
24.Noorossana, R., Process capability analysis in the presence of autocorrelation. Quality and Reliability Engineering International, 2002. 18(1): p. 75-77.
25.Vännman, K. and M. Kulahci, A model‐free approach to eliminate autocorrelation when testing for process capability. Quality and Reliability Engineering International, 2008. 24(2): p. 213-228.
26.Lovelace, C.R., et al., Lower confidence limits for process capability indices Cp and Cpk when data are autocorrelated. Quality and Reliability Engineering International, 2009. 25(6): p. 663-700.
27.Sun, J., S. Wang, and Z. Fu, Process capability analysis and estimation scheme for autocorrelated data. Journal of Systems Science and Systems Engineering, 2010. 19(1): p. 105-127.
28.Lundkvist, P., K. Vännman, and M. Kulahci, A comparison of decision methods for Cpk when data are autocorrelated. Quality Engineering, 2012. 24(4): p. 460-472.
29.Boyles, R.A., Brocess capability with asymmetric tolerances. Communications in Statistics-Simulation and Computation, 1994. 23(3): p. 615-635.
30.Brockwell, P.J. and R.A. Davis, Introduction to time series and forecasting. 2002. New York: Springer. 978-0387953519.
31.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.
32.Schabenberger, O. and F.J. Pierce, Contemporary statistical models for the plant and soil sciences. 2010, Boca Raton: CRC press.

Chapter 5
References

1.Woodall, W.H., et al., Using control charts to monitor process and product quality profiles. Journal of Quality Technology, 2004. 36(3): p. 309-320.
2.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
3.Noorossana, R., A. Saghaei, and A. Amiri, Statistical analysis of profile monitoring. Vol. 865. 2011: John Wiley & Sons.
4.Eyvazian, M., et al., Phase II monitoring of multivariate multiple linear regression profiles. Quality and Reliability Engineering International, 2011. 27(3): p. 281-296.
5.Ebadi, M. and H. Shahriari, A process capability index for simple linear profile. International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): p. 857-865.
6.Hosseinifard, S.Z. and B. Abbasi, Process Capability Analysis in Non Normal Linear Regression Profiles. Communications in Statistics-Simulation and Computation, 2012. 41(10): p. 1761-1784.
7.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
8.Wang, F.K., Process yield for multivariate linear profiles. Quality Technology and Quantitative Management, 2014(in press).
9.Wang, F.K., A process yield for simple linear profiles. Quality Engineering, 2014. 26(3): p. 311-318.
10.Pearn, W.L., F.K. Wang, and C. Yen, Measuring production yield for processes with multiple quality characteristics. International Journal of Production Research, 2006. 44(21): p. 4649-4661.
11.Pearn, W.L., et al., Photolithography control in wafer fabrication based on process capability indices with multiple characteristics. Semiconductor Manufacturing, IEEE Transactions on, 2009. 22(3): p. 351-356.
12.Wang, F.K., Quality evaluation of a manufactured product with multiple characteristics. Quality and Reliability Engineering International, 2006. 22(2): p. 225-236.
13.Wang, F.K., A general procedure for process yield with multiple characteristics. Semiconductor Manufacturing, IEEE Transactions on, 2010. 23(4): p. 503-508.
14.Wang, F.K. and D. Chu, Process yield for a manufactured product. Quality Technology and Quantitative Management, 2013. 10(4): p. 483-494.
15.Wang, F.K. and T. Du, Using principal component analysis in process performance for multivariate data. Omega, 2000. 28(2): p. 185-194.
16.Wang, F.K., et al., Comparison of three multivariate process capability indices. Journal of Quality Technology, 2000. 32(3): p. 263-275.
17.Ebadi, M. and A. Amiri, Evaluation of process capability in multivariate simple linear profiles. Scientia Iranica, 2012. 19(6): p. 1960-1968.
18.Koltz, S. and N. Johnson, Process capability indices-a review. 1992-2000. Journal of Quality Technology, 2002. 34(1): p. 2-39.
19.Wu, C.W., W.L. Pearn, and S. Kotz, An overview of theory and practice on process capability indices for quality assurance. International Journal of Production Economics, 2009. 117(2): p. 338-359.
20.Pearn, W. and S. Kotz, Encyclopedia and handbook of process capability indices: a comprehensive exposition of quality control measures. 2006: World Scientific Hackensack, NJ.
21.Wu, C.W. and W.L. Pearn, Measuring manufacturing capability for couplers and wavelength division multiplexers. The International Journal of Advanced Manufacturing Technology, 2005. 25(5-6): p. 533-541.
22.Hsu, Y.C., W. Pearn, and Y.-F. Chuang, Sample size determination for production yield estimation with multiple independent process characteristics. European Journal of Operational Research, 2009. 196(3): p. 968-978.
23.Pearn, W.L., C. Wu, and M. Tsai, A note on “capability assessment for processes with multiple characteristics: a generalization of the popular index Cpk”. Quality and Reliability Engineering International, 2013. 29(2): p. 159-163.
24.Noorossana, R., M. Eyvazian, and A. Vaghefi, Phase II monitoring of multivariate simple linear profiles. Computers & Industrial Engineering, 2010. 58(4): p. 563-570.
25.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.
26.Zou, C., X. Ning, and F. Tsung, LASSO-based multivariate linear profile monitoring. Annals of operations research, 2012. 192(1): p. 3-19.
27.Li, J., F. Tsung, and C. Zou, Multivariate binomial/multinomial control chart. IIE Transactions, 2014. 46(5): p. 526-542.

Chapter 6
References
1.Kang, L. and S.L. Albin, On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 2000. 32(4): p. 418-426.
2.Noorossana, R., A. Saghaei, and A. Amiri, Statistical analysis of profile monitoring. Vol. 865. 2011: John Wiley & Sons.
3.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
4.Soleimani, P., A. Narvand, and S. Raissi, Online monitoring of auto correlated linear profiles via mixed model. International Journal of Manufacturing Technology and Management, 2013. 27(4): p. 238-250.
5.Adibi, A., D.C. Montgomery, and C.M. Borror, Phase II monitoring of linear profiles using a P-value approach. International Journal of Quality Engineering and Technology, 2014. 4(2): p. 97-106.
6.Zeng, L. and N. Chen, Bayesian hierarchical modeling for monitoring optical profiles in low-E glass manufacturing processes. IIE Transactions, 2015. 47(2): p. 109-124.
7.Weber, C.A., J.R. Current, and W. Benton, Vendor selection criteria and methods. European journal of operational research, 1991. 50(1): p. 2-18.
8.Ebadi, M. and A. Amiri, Evaluation of process capability in multivariate simple linear profiles. Scientia Iranica, 2012. 19(6): p. 1960-1968.
9.Ebadi, M. and H. Shahriari, A process capability index for simple linear profile. International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): p. 857-865.
10.Hosseinifard, S.Z. and B. Abbasi, Process capability analysis in non normal linear regression profiles. Communications in Statistics-Simulation and Computation, 2012. 41(10): p. 1761-1784.
11.Nemati Keshteli, R., et al., Functional process capability indices for circular profile. Quality and Reliability Engineering International, 2014. 30(5): p. 633-644.
12.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
13.Wang, F.K., Measuring the process yield for circular profiles. Quality and Reliability Engineering International, 2013, DOI: 10.1002/qre.1614.
14.Wang, F.K., A process yield for simple linear profiles. Quality Engineering, 2014. 26(3): p. 311-318.
15.Wang, F.K., Measuring the process yield for simple linear profiles with one‐sided specification. Quality and Reliability Engineering International, 2014. 30(8): p. 1145-1151.
16.Wang, F.K. and Y.C. Guo, Measuring process yield for nonlinear profiles. Quality and Reliability Engineering International, 2014. 30(8): p. 1333-1339.
17.Chou, Y.M., Selecting a better supplier by testing process capability indices. Quality Engineering, 1994. 6(3): p. 427-438.
18.Daniels, L., et al., Using confidence intervals to compare process capability indices. Quality Engineering, 2004. 17(1): p. 23-32.
19.Hubele, N.F., A. Berrado, and E.S. Gel, A Wald test for comparing multiple capability indices. Journal of quality technology, 2005. 37(4): p. 304-307.
20.Lin, C.J. and W.L. Pearn, Process selection for higher production yield based on capability index Spk. Quality and Reliability Engineering International, 2010. 26(3): p. 247-258.
21.Pearn, W.L. and C. Wu, Supplier selection critical decision values for processes with multiple independent lines. Quality and Reliability Engineering International, 2013. 29(6): p. 899-909.
22.Wu, C.W., M.Y. Liao, and T.T. Yang, Efficient methods for comparing two process yields–strategies on supplier selection. International Journal of Production Research, 2013. 51(5): p. 1587-1602.
23.Wang, F.K., The difference test statistic for two suppliers with linear profiles. Quality and Reliability Engineering International, 2014, DOI: 10.1002/qre.1726.
24.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.

Chapter 7
References
1.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
2.Noorossana, R., A. Saghaei, and A. Amiri, Statistical analysis of profile monitoring. Vol. 865. 2011: John Wiley & Sons.
3.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
4.Wang, F.K., Measuring the process yield for simple linear profiles with one‐sided specification. Quality and Reliability Engineering International, 2014. 30(8): p. 1145-1151.
5.Pearn, W.L., H. Hung, and Y.C. Cheng, Supplier selection for one-sided processes with unequal sample sizes. European Journal of Operational Research, 2009. 195(2): p. 381-393.
6.Pearn, W., et al., An effective powerful test for one-sided supplier selection problem. Journal of Statistical Computation and Simulation, 2011. 81(10): p. 1313-1331.
7.Hsu, Y.C., W. Pearn, and Y.F. Chuang, Sample size determination for production yield estimation with multiple independent process characteristics. European Journal of Operational Research, 2009. 196(3): p. 968-978.
8.Pearn, W.L., C. Wu, and M. Tsai, A note on “capability assessment for processes with multiple characteristics: a generalization of the popular index Cpk”. Quality and Reliability Engineering International, 2013. 29(2): p. 159-163.
9.Pearn, W.L., et al., An extension of the product acceptance determination for one‐sided process with multiple characteristics. Quality and Reliability Engineering International, 2013. 29(2): p. 277-284.
10.Pearn, W. and C. Wu, Supplier selection for multiple characteristics processes with one-sided specifications. Quality Technology and Quantitative Management, 2013. 10(1): p. 133-139.
11.Yum, B.J. and K.W. Kim, A bibliography of the literature on process capability indices: 2000–2009. Quality and Reliability Engineering International, 2011. 27(3): p. 251-268.
12.Spiring, F., Exploring process capability with Mathematica. Quality and Reliability Engineering International, 2011. 27(3): p. 369-387.
13.Grau, D., New process capability indices for one-sided tolerances. Quality Technology and Quantitative Management, 2009. 6(2): p. 107-124.
14.Grau, D., On the choice of a capability index for asymmetric tolerances. Quality Technology & Quantitative Management, 2010. 7(3): p. 301-319.
15.Grau, D., Process yield, process centering and capability indices for one-sided tolerance processes. Quality Technology and Quantitative Management, 2012. 9(2): p. 153-170.
16.Maiti, S.S., M. Saha, and A.K. Nanda, On generalizing process capability indices. Journal of Quality Technology and Quantitative Management, 2010. 7(3): p. 279-300.
17.Parchami, A. and M. Mashinchi, Testing the capability of fuzzy processes. Quality Technology and Quantitative Management, 2009. 6(2): p. 125-136.
18.Wang, F.K., Supplier selection for multiple linear profiles with one‐sided specifications. Quality and Reliability Engineering International, 2014.
19.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.
20.Amiri, A., C. Zou, and M.H. Doroudyan, Monitoring correlated profile and multivariate quality characteristics. Quality and Reliability Engineering International, 2014. 30(1): p. 133-142.

Chapter 8
References

1.Kang, L. and S.L. Albin, On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 2000. 32(4): p. 418-426.
2.Lin, C.J. and W.L. Pearn, Process selection for higher production yield based on capability index Spk. Quality and Reliability Engineering International, 2010. 26(3): p. 247-258.
3.Woodall, W.H., Current research on profile monitoring. Production, 2007. 17(3): p. 420-425.
4.Dickson, G.W., An analysis of vendor selection systems and decisions. 1996.
5.Olhager, J. and E. Selldin, Supply chain management survey of Swedish manufacturing firms. International Journal of Production Economics, 2004. 89(3): p. 353-361.
6.Hsu, B.M., C.Y. Chiang, and M.H. Shu, Supplier selection using fuzzy quality data and their applications to touch screen. Expert Systems with Applications, 2010. 37(9): p. 6192-6200.
7.Zhang, X., C. Lee, and S. Chen, Supplier evaluation and selection: a hybrid model based on DEAHP and ABC. International Journal of Production Research, 2012. 50(7): p. 1877-1889.
8.Lin, C.J. and W.L. Pearn, Group selection for production yield among k manufacturing lines. Journal of Statistical Planning and Inference, 2011. 141(4): p. 1510-1518.
9.Lin, C.J. and H.H. Kuo, Multiple comparisons with the best for supplier selection. Quality and Reliability Engineering International, 2014. 30(7): p. 1083-1092.
10.Pearn, W.L. and C. Wu, Supplier selection critical decision values for processes with multiple independent lines. Quality and Reliability Engineering International, 2013. 29(6): p. 899-909.
11.Tai, Y.T., W.L. Pearn, and S.K. You, An effective test for supplier selection evaluation with multiple characteristics. Journal of Testing and Evaluation, 2011. 39(6): p. 1165-1173.
12.Hosseinifard, S.Z. and B. Abbasi, Process capability analysis in non normal linear regression profiles. Communications in Statistics-Simulation and Computation, 2012. 41(10): p. 1761-1784.
13.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
14.Ebadi, M. and A. Amiri, Evaluation of process capability in multivariate simple linear profiles. Scientia Iranica, 2012. 19(6): p. 1960-1968.
15.Ebadi, M. and H. Shahriari, A process capability index for simple linear profile. International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): p. 857-865.
16.Wang, F.K., A process yield for simple linear profiles. Quality Engineering, 2014. 26(3): p. 311-318.
17.Wang, F.K. and Y.C. Guo, Measuring process yield for nonlinear profiles. Quality and Reliability Engineering International, 2014. 30(8): p. 1333-1339.
18.Horrace, W.C. and P. Schmidt, Multiple comparisons with the best, with economic applications. Journal of Applied Econometrics, 2000. 15(1): p. 1-26.
19.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.
20.Noorossana, R., M. Eyvazian, and A. Vaghefi, Phase II monitoring of multivariate simple linear profiles. Computers & Industrial Engineering, 2010. 58(4): p. 563-570.

Chapter 9
References

1.Zahra Hosseinifard, S. and B. Abbasi, Evaluation of process capability indices of linear profiles. International Journal of Quality & Reliability Management, 2012. 29(2): p. 162-176.
2.Wang, F.K., Measuring the process yield for simple linear profiles with one‐sided specification. Quality and Reliability Engineering International, 2014. 30(8): p. 1145-1151.
3.Pearn, W.L., H. Hung, and Y.C. Cheng, Supplier selection for one-sided processes with unequal sample sizes. European Journal of Operational Research, 2009. 195(2): p. 381-393.
4.Pearn, W., et al., An effective powerful test for one-sided supplier selection problem. Journal of Statistical Computation and Simulation, 2011. 81(10): p. 1313-1331.
5.Hsu, Y.C., W. Pearn, and Y.F. Chuang, Sample size determination for production yield estimation with multiple independent process characteristics. European Journal of Operational Research, 2009. 196(3): p. 968-978.
6.Pearn, W.L., C. Wu, and M. Tsai, A note on “capability assessment for processes with multiple characteristics: a generalization of the popular index Cpk”. Quality and Reliability Engineering International, 2013. 29(2): p. 159-163.
7.Pearn, W.L., et al., An extension of the product acceptance determination for one‐sided process with multiple characteristics. Quality and Reliability Engineering International, 2013. 29(2): p. 277-284.
8.Yum, B.J. and K.W. Kim, A bibliography of the literature on process capability indices: 2000–2009. Quality and Reliability Engineering International, 2011. 27(3): p. 251-268.
9.Grau, D., New process capability indices for one-sided tolerances. Quality Technology and Quantitative Management, 2009. 6(2): p. 107-124.
10.Grau, D., On the choice of a capability index for asymmetric tolerances. Quality Technology & Quantitative Management, 2010. 7(3): p. 301-319.
11.Grau, D., Process yield, process centering and capability indices for one-sided tolerance processes. Quality Technology and Quantitative Management, 2012. 9(2): p. 153-170.
12.Maiti, S.S., M. Saha, and A.K. Nanda, On generalizing process capability indices. Journal of Quality Technology and Quantitative Management, 2010. 7(3): p. 279-300.
13.Parchami, A. and M. Mashinchi, Testing the capability of fuzzy processes. Quality Technology and Quantitative Management, 2009. 6(2): p. 125-136.
14.Pearn, W. and C. Wu, Supplier selection for multiple characteristics processes with one-sided specifications. Quality Technology and Quantitative Management, 2013. 10(1): p. 133-139.
15.Wang, F.K., Supplier selection for multiple linear profiles with one‐sided specifications. Quality and Reliability Engineering International, 2014.
16.Wang, F.K., Y. Tamirat, and Y.S. Tsai, Process selection for linear profiles with one‐sided specifications based on the ratio test statistic. Quality and Reliability Engineering International, 2014.
17.R Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. 2012, ISBN 3-900051-07-0.
18.Amiri, A., A. Zand, and D. Soudbakhsh. Monitoring simple linear profiles in the leather industry (a case study). in Proceedings of the 2nd International Conference on Industrial Engineering and Operations Management, Kuala Lumpur, Malaysia, January. 2011.
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