Model-based clustering for integrated circuit yield enhancement

European Journal of Operational Research

Volumn 178, Issue 1, 2007, Pages 143-153

  Hwang, Jung Yoon ^a   Kuo, Way ^b  

^a SAMSUNG Electronics   (South Korea)

^b University of Tennessee Knoxville   (United States)

Author keywords

Quality control; Stochastic processes

Indexed keywords

DATA REDUCTION; NORMAL DISTRIBUTION; PROCESS CONTROL; QUALITY CONTROL; RANDOM PROCESSES; SEMICONDUCTOR MATERIALS;

LOCAL DEFECTS; POISSON PROCESSES; ROOT-CAUSE ANALYSIS;

INTEGRATED CIRCUITS;

EID: 33750830235     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2005.11.032     Document Type: Article

References (29)

1. Atherton L.F., and Atherton R.W. Wafer Fabrication: Factory Performance and Analysis (1995), Kluwer Academic Publishers, Boston
2. Banfield J.D., and Raftery A.E. Ice floe identification in satellite images using mathematical morphology and clustering about principal curves. Journal of American Statistical Association 87 417 (1992) 7-16
3. Banfield J.D., and Raftery A.E. Model-based Gaussian and non-Gaussian clustering. Biometrics 49 3 (1993) 803-821
4. Baron M., Lakshminarayan C.K., and Chen Z. Markov random fields in pattern recognition for semiconductor manufacturing. Technometrics 43 1 (2001) 66-72
5. Campbell J.G., Fraley C., Murtagh F., and Raftery A.E. Linear flaw defection in woven textiles using model-based clustering. Pattern Recognition Letters 18 (1997) 1539-1548
6. Celeux G., and Govaert G. A classification EM algorithm for clustering and two stochastic versions. Computational Statistics & Data Analysis 14 (1992) 315-332
7. Celeux G., and Govaert G. Gaussian parsimonious clustering models. Pattern Recognition 28 5 (1995) 781-793
8. Chen F.L., and Lin S.F. A neural-network approach to recognize defect spatial pattern in semiconductor fabrication. IEEE Transactions on Semiconductor Manufacturing 13 3 (2000) 366-373
9. Cressie N.A.C. Statistics for Spatial Data (1993), John Wiley & Sons, New York
10. Cunningham S., and MacKinnon S. Statistical methods for visual defect metrology. IEEE Transactions on Semiconductor Manufacturing 11 1 (1998) 48-53
11. Daley D.J., and Vere-Jones D. An Introduction to the Theory of Point Processes (2003), Springer, New York
12. Dasgupta A., and Raftery A.E. Detecting features in spatial point processes with clutter via model-based clustering. Journal of American Statistical Association 93 441 (1998) 294-302
13. C. Fraley, A.E. Raftery, How many clusters? Which clustering method? Answers via model-based cluster analysis, Technical Report 329, Department of Statistics, University of Washington, 1998.
14. C. Fraley, A.E. Raftery, Model-based clustering, discriminant analysis, and density estimation, Technical Report 380, Department of Statistics, University of Washington, 2000.
15. Gleason S.S., Tobin K.W., Karnowski T.P., and Lakhani F. Rapid yield learning through optical defect and electrical test analysis. Proceedings of SPIE-The International Society for Optical Engineering 3332 (1998) 232-242
16. Hansen C.K., and Thyregod P. Use of wafer maps in integrated circuit manufacturing. Microelectronics Reliability 38 (1998) 1155-1164
17. Hansen M.H., Nair V.N., and Friedman F.J. Monitoring wafer map data from integrated circuit fabrication processes for spatially clustered defects. Technometrics 39 3 (1997) 241-253
18. Hastie T., and Stuetzle W. Principal curves. Journal of American Statistical Association 84 406 (1989) 502-516
19. Kim K.O., and Kuo W. A unified model incorporating yield, burn-in and reliability. Naval Research Logistics 51 2 (2004) 704-719
20. Kuo W., Chien W.K., and Kim T. Reliability, Yield, and Stress Burn-in (1998), Kluwer Academic Publishers, Boston
21. Lewis P.A.W., and Sheldler G.S. Simulation of nonhomogeneous Poisson processes by thinning. Naval Research Logistics Quarterly 26 (1979) 403-413
22. S.L. Riley, Optical inspection of wafers using large-area defect detection and sampling, in: International Workshop on Defect and Tolerance in VLSI systems, 1992, pp. 12-21.
23. Schwarz G. Estimating the dimension of a model. The Annals of Statistics 6 2 (1978) 461-464
24. Stanford D., and Raftery A.E. Finding curvilinear features in spatial point patterns: Principal curve clustering with noise. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 6 (2000) 601-609
25. Taam W., and Hamada M. Detecting spatial effects from factorial experiments: An application from integrated circuit manufacturing. Technometrics 35 2 (1993) 149-160
26. Tobin K.W., Gleason S.S., Karnowski T.P., and Guidry D. Using SSA to measure the efficacy of automated defect data gathering. Micro 16 (1998) 27-33
27. C. Weber, Yield learning and the sources of profitability in semiconductor manufacturing and process development, in: IEEE International Symposium on Semiconductor Manufacturing Conference, Proceedings, 2002, pp. 324-329.
28. Kim K.O., Kuo W., and Luo W. A relation model of gate oxide yield and reliability. Microelectronics Reliability 44 3 (2004) 425-434
29. Kuo W., and Kim T. An overview of manufacturing yield and reliability modeling for semiconductor products. Proceedings of the IEEE 87 8 (1999) 1329-1346