Fault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data

Reliability Engineering and System Safety

Volumn 100, Issue , 2012, Pages 102-114

  Debon A ^a   Carlos Garcia Diaz J ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Bootstrapping; Generalized additive models; Generalized linear models; ROC curve

Indexed keywords

BATH TEMPERATURES; BEST MODEL; BINARY DATA; BOOTSTRAPPING; CLASSIFICATION TREES; COMPARATIVE EVALUATIONS; DISTINCTIVE FEATURES; FAULT DETECTION AND DIAGNOSIS; GALVANIZED STEELS; GENERALIZED ADDITIVE MODEL; GENERALIZED LINEAR MODEL; GOODNESS-OF-FIT STATISTICS; HOT-DIP GALVANIZING; IN-PROCESS CONTROL; INVESTMENT PLAN; MANUFACTURING PROCESS; MODEL CLASSIFICATION; QUALITY REQUIREMENTS; RECEIVER OPERATING CHARACTERISTIC CURVES; ROBUST METHODS; ROC CURVES; STATISTICAL MODELS; STATISTICAL REGRESSION MODEL; STEEL COIL; STEEL STRIP; TIME HISTORY;

DESIGN; FAULT DETECTION; INDUSTRIAL ENGINEERING; INVESTMENTS; PRODUCTION ENGINEERING; STATISTICAL METHODS;

GALVANIZING;

EID: 84856332624     PISSN: 09518320     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ress.2011.12.022     Document Type: Article

References (40)

1. A. Agresti Categorical data analysis 2nd ed 2002 Wiley
2. F. Aparisi, and J.C. García-Díaz Design and optimization of EWMA control charts for in-control, indifference, and out-of-control regions Computers and Operations Research 34 7 2007 2096 2108 (Pubitemid 44879774)
3. Breiman L, Friedman J, Olshen R, Stone C. Classification and regression trees. Wadsworth International Group, Belmont, California, USA; 1984.
4. A. Debón, A. Carrión, E. Cabrera, and H. Solano Comparing risk of failure models in water supply networks using ROC curves Reliability & Engineering System Safety 95 1 2010 43 48
5. M. El Aroui, and C. Lavergne Generalized linear models in software reliability: parametric and semi-parametric approaches IEEE Transactions on Reliability 45 3 1996 463 470 (Pubitemid 126771056)
6. J. Faraway Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models 2006 Chapman Hall/crc
7. Faraway J. faraway: Functions and datasets for books by Julian Faraway R package version 1.0.4; 2009. URL 〈 http://www.maths.bath.ac.uk/∼jjf23/ 〉.
8. T. Fawcett An introduction to ROC analysis Pattern Recognition Letters 27 2006
9. García-Díaz JC. Fault detection and diagnosis in monitoring a hot dip galvanizing line using multivariate statistical process control. In: Safety reliability and risk analysis: theory, methods and applications, vol. 1. London: Taylor & Francis Group; 2009. p. 2014.
10. García-Díaz JC. Statistical methods for quality control of steel coils manufacturing process using glm models. In: AIP conference proceedings, vol. 1181. New York: American Institute of Physics; 2009. p. 299305.
11. R.-S. Guh A hybrid learning-based model for on-line detection and analysis of control chart patterns Computers & Industrial Engineering 49 2005 35 62 (August) (Pubitemid 41084181)
12. M. Hamada, and J. Nelder Generalized linear models for quality-improvement experiments Journal of Quality Technology 29 1 1997 292 304 (Pubitemid 127617648)
13. T. Hastie, R. Tibshirani, and J. Friedman The elements of statistical learning. Data mining, inference, and prediction 2001 Springer New York
14. T.J. Hastie, and R. Tibshirani Generalized Aditive Models 1990 Chapman-Hall London
15. Hawkins D. FIRM: formal inference-based recursive modeling. Technical Report 546, University of Minnesota, School of Statistics; 1997.
16. O. Himmelbau Fault detection and diagnosis in chemical and petrochemical process 1978 Elsevier Amsterdam
17. D. Hosmer, and S. Lemeshow Applied logistic regression 2nd ed 2000 Wiley
18. F. Ilinca, F. Ajersch, C. Baril, and F. Goodwin Numerical simulation of the galvanizing process during ga to gi transition International Journal for Numerical Methods in Fluids 53 2007 1646 1929
19. G. Kass An exploratory technique for investigating large quantities of categorical data Journal of Applied Statistics 29 2 1980 119 127
20. S. Lewis, D. Montgomery, and R. Myers Examples of designed experiments with nonnormal responses Journal of Quality Technology 33 3 2001 265 278
21. H. Liu, R. Davidson, and T. Apanasovich Spatial generalized linear mixed models of electric power outages due to hurricanes and ice storms Reliability Engineering & System Safety 93 6 2008 897 912 (Pubitemid 351305179)
22. H. Liu, R. Davidson, D. Rosowsky, and J. Stedinger Negative binomial regression of electric power outages in hurricanes Journal of Infrastructure Systems 11 2005 258
23. F. Martínez-De-Pisón, A. Pernía, E. Jiménez-Macias, and R. Fernández Overall model of the dynamic behaviour of the steel strip in an annealing heating furnace on a hot-dip galvanizing line Revista de Metalurgia 46 5 2010 405 420
24. P. McCullagh, and J. Nelder Generalized linear models 1989 Chapman and Hall London
25. D. Montgomery Introduction to statistical quality control 6th ed. 2009 John Wiley and Sons New York
26. R.H. Myers, D. Montgomery, and G. Vining Generalized linear models with applications in engineering and the sciences 2nd ed. 2010 Wiley New York
27. J. Ordieres-Meré, F. Martínez-de Pisón-Ascacibar, A. González-Marcos, and I. Ortiz-Marcos Comparison of models created for the prediction of the mechanical properties of galvanized steel coils Journal of Intelligent Manufacturing 21 2010 403 421
28. M. Pacella, Q. Semeraro, and A. Anglani Manufacturing quality control by means of a fuzzy art network trained on natural process data Engineering Applications of Artificial Intelligence 17 1 2004 83 96
29. A. Pernía-Espinoza, M. Castejón-Limas, A. González-Marcos, and V. Lobato-Rubio Steel annealing furnace robust neural network model Ironmaking & Steelmaking 32 5 2005 418 426 (Pubitemid 41560580)
30. J. Qinlan Programs for machine learning The Morgan Kaufmann series in machine learning 1993 Morgan Kaufmann
31. R Development Core Team. R: a language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria; 2009. ISBN: 3-900051-07-0. URL 〈 http://www.R-project.org 〉.
32. J. Roshan, and H. Adya Prediction of yield in a multi-product batch production environment Quality Engineering 14 1 2001 153 159 (Pubitemid 33025395)
33. Sellers K, Lotze T. COMPoissonReg: ConwayMaxwell Poisson (COM-Poisson) regression. R package version 0.3.4; 2011. URL 〈 http://CRAN.R-project.org/ package=COMPoissonReg 〉.
34. Sing T, Sander O, Beerenwinkel N, Lengauer T. ROCR: visualizing the performance of scoring classifiers. R package version 1.0-2; 2007. URL 〈 http://rocr.bioinf.mpi-sb.mpg.de/ 〉.
35. K. Skinner, D. Montgomery, and G. Runger Generalized linear model-based control charts for discrete semiconductor process data Quality and Reliability Engineering International 20 8 2004 777 786 (Pubitemid 40044116)
36. Sonquist J, Baker E, Morgan J. Searching for structure (alias-AID-III); an approach to analysis of substantial bodies of micro-data and documentation for a computer program (successor to the Automatic Interaction Detector Program). Ann Arbor, Institute for Social Research, University of Michigan; 1971.
37. N. Tang Characteristics of continuous galvanizing baths Metallurgical and Materials Transactions B 30 1999
38. Timofeev R. Classification and regression trees (cart). Theory and applications. Masters thesis, CASE Center of Applied Statistics and Economics, Humboldt University, Berlin; 2004.
39. W. Venables, and B.D. Ripley Modern applied statistics with S-PLUS 2002 Springer Nueva York
40. H. Zheng, D.Y. Gong, G. Wang, and P.J. ZhangLiu Software of predicting mechanical properties of strip steel by using bp networks Journal of Iron and Steel Research 19 7 2007 54 57