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Volumn 29, Issue 4, 2013, Pages 362-376

A virtual metrology system based on least angle regression and statistical clustering

Author keywords

least angle regression; neural networks; semiconductor manufacturing; statistical distance; virtual metrology

Indexed keywords

CHEMICAL VAPOR DEPOSITIONS (CVD); HIGH-QUALITY STANDARDS; INDUSTRIAL PRODUCTION; LEAST ANGLE REGRESSIONS; SEMICONDUCTOR MANUFACTURING; STATISTICAL CLUSTERING; STATISTICAL DISTANCE; VIRTUAL METROLOGY;

EID: 84882448296     PISSN: 15241904     EISSN: 15264025     Source Type: Journal    
DOI: 10.1002/asmb.1948     Document Type: Article
Times cited : (24)

References (45)
  • 2
    • 34347398446 scopus 로고    scopus 로고
    • A novel virtual metrology scheme for predicting CVD thickness in semiconductor manufacturing
    • Hung M-H, Lin T-H, Cheng F-T, Lin R-C,. A novel virtual metrology scheme for predicting CVD thickness in semiconductor manufacturing. IEEE/ASME Transactions on Mechatronics 2007; 12: 308-316.
    • (2007) IEEE/ASME Transactions on Mechatronics , vol.12 , pp. 308-316
    • Hung, M.-H.1    Lin, T.-H.2    Cheng, F.-T.3    Lin, R.-C.4
  • 6
    • 84877023031 scopus 로고    scopus 로고
    • A Predictive Maintenance System for Epitaxy Processes based on Filtering and Prediction Techniques
    • (in press) Available from
    • Susto GA, Beghi A, DeLuca C,. A Predictive Maintenance System for Epitaxy Processes based on Filtering and Prediction Techniques. IEEE Transactions on Semiconductor Manufacturing 2012. (in press) Available from: http://ieeexplore.ieee.org/xpls/abs-all.jsp?arnumber=6242424&tag=1.
    • (2012) IEEE Transactions on Semiconductor Manufacturing
    • Susto, G.A.1    Beghi, A.2    Deluca, C.3
  • 7
    • 84882454280 scopus 로고    scopus 로고
    • ENIAC IMPROVE. Official Website Retrieved May 5
    • ENIAC IMPROVE. Official Website. In www.eniac-improve.eu, Retrieved May 5, 2012.
    • (2012)
  • 8
    • 84882452945 scopus 로고    scopus 로고
    • Project Profile IMPROVE Retrieved May 5
    • Project Profile IMPROVE. Eniac ju projects 120005. In www.eniac.eu/web/communication/publications.php, Retrieved May 5, 2012.
    • (2012) Eniac Ju Projects 120005
  • 18
    • 40749144475 scopus 로고    scopus 로고
    • On the interaction between measurement strategy and control performance in semiconductor manufacturing
    • Su A-J, Yu C-C, Ogunnaike BA,. On the interaction between measurement strategy and control performance in semiconductor manufacturing. Journal of Process Control 2008; 18: 266-276.
    • (2008) Journal of Process Control , vol.18 , pp. 266-276
    • Su, A.-J.1    Yu, C.-C.2    Ogunnaike, B.A.3
  • 20
    • 0026996349 scopus 로고
    • A comparison of statistically based and neural network models of plasma etch behaviour
    • San Francisco, CA
    • Himmel CD, Kim B, May GS,. A comparison of statistically based and neural network models of plasma etch behaviour. In International Semiconductor Manufacturing Science Symposium, San Francisco, CA, 1992; 124-129.
    • (1992) International Semiconductor Manufacturing Science Symposium , pp. 124-129
    • Himmel, C.D.1    Kim, B.2    May, G.S.3
  • 21
    • 0027592466 scopus 로고
    • Advantages of plasma etch modeling using neural networks over statistical techniques
    • Himmel CD, May GS,. Advantages of plasma etch modeling using neural networks over statistical techniques. IEEE Transactions on Semiconductor Manufacturing 1993; 6: 103-111.
    • (1993) IEEE Transactions on Semiconductor Manufacturing , vol.6 , pp. 103-111
    • Himmel, C.D.1    May, G.S.2
  • 22
    • 70349453596 scopus 로고    scopus 로고
    • An artificial neural network (p,d,q) model for timeseries forecasting
    • Khashei M, Bijari M,. An artificial neural network (p,d,q) model for timeseries forecasting. Expert Systems with Applications 2010; 37: 479-489.
    • (2010) Expert Systems with Applications , vol.37 , pp. 479-489
    • Khashei, M.1    Bijari, M.2
  • 24
    • 80655138971 scopus 로고    scopus 로고
    • A virtual metrology system for predicting CVD thickness with equipment variables and qualitative clustering
    • Toulouse
    • Susto GA, Beghi A, DeLuca C,. A virtual metrology system for predicting CVD thickness with equipment variables and qualitative clustering. In IEEE Conference on Emerging Technologies & Factory Automation, Toulouse, 2011; 1-4.
    • (2011) IEEE Conference on Emerging Technologies & Factory Automation , pp. 1-4
    • Susto, G.A.1    Beghi, A.2    Deluca, C.3
  • 28
    • 56349142439 scopus 로고    scopus 로고
    • Virtual metrology and feedback control for semiconductor manufacturing processes using recursive partial least squares
    • Khan AA, Moyne JR, Tilbury DM,. Virtual metrology and feedback control for semiconductor manufacturing processes using recursive partial least squares. Journal of Process Control 2008; 18: 961-974.
    • (2008) Journal of Process Control , vol.18 , pp. 961-974
    • Khan, A.A.1    Moyne, J.R.2    Tilbury, D.M.3
  • 31
    • 0032022388 scopus 로고    scopus 로고
    • Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm
    • Lu Y, Sundararajan N, Saratchandran P,. Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm. IEEE Transactions on Neural Networks 1998; 9: 308-318.
    • (1998) IEEE Transactions on Neural Networks , vol.9 , pp. 308-318
    • Lu, Y.1    Sundararajan, N.2    Saratchandran, P.3
  • 33
    • 0000442911 scopus 로고
    • The use and interpretation of principal component analysis in applied research
    • Rao CR,. The use and interpretation of principal component analysis in applied research. The Indian Journal of Statistics 1964; 26: 329-358.
    • (1964) The Indian Journal of Statistics , vol.26 , pp. 329-358
    • Rao, C.R.1
  • 34
    • 77249166490 scopus 로고    scopus 로고
    • Integrating support vector machine and genetic algorithm to implement dynamic wafer quality prediction system
    • Chou P-H, Wu M-J, Chen K-K,. Integrating support vector machine and genetic algorithm to implement dynamic wafer quality prediction system. Expert Systems with Applications 2010; 37: 4413-4424.
    • (2010) Expert Systems with Applications , vol.37 , pp. 4413-4424
    • Chou, P.-H.1    Wu, M.-J.2    Chen, K.-K.3
  • 37
    • 84866754326 scopus 로고    scopus 로고
    • Multilevel Kernel methods for virtual metrology in semiconductor manufacturing
    • Milan
    • Schirru A, Pampuri S, DeLuca C, DeNicolao G,. Multilevel Kernel methods for virtual metrology in semiconductor manufacturing. In IFAC World Congress, Milan, 2011; 11614-11621.
    • (2011) IFAC World Congress , pp. 11614-11621
    • Schirru, A.1    Pampuri, S.2    Deluca, C.3    Denicolao, G.4
  • 40
    • 84950445313 scopus 로고
    • Cross-validation of regression models
    • Available from: http://www.jstor.org/stable/2288403
    • Picard RR, Cook RD,. Cross-validation of regression models. Journal of the American Statistical Association 1984; 79: 575-583. Available from: http://www.jstor.org/stable/2288403.
    • (1984) Journal of the American Statistical Association , vol.79 , pp. 575-583
    • Picard, R.R.1    Cook, R.D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.