Nonstationarity in statistical process control - Issues, cases, ideas

Applied Stochastic Models in Business and Industry

Volumn 27, Issue 4, 2011, Pages 367-376

  Ketelaere, Bart De ^a,b   Mertens, Kristof ^a   Mathijs, Frank ^a   Diaz, Daniel Sabin ^a   Baerdemaeker, Josse De ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b Katholieke Universiteit Leuven   (Belgium)

Author keywords

nonstationarity; statistical process control; synergistic control

Indexed keywords

BIOLOGICAL PROCESS; INDUSTRIAL PROCESSS; NON-STATIONARITIES; PROCESS VARIABILITY; SPECIAL CAUSE; STATISTICAL PROCESS; SYNERGISTIC CONTROL; UNIVARIATE;

INDUSTRY; QUALITY CONTROL;

STATISTICAL PROCESS CONTROL;

EID: 80051795542     PISSN: 15241904     EISSN: 15264025     Source Type: Journal    
DOI: 10.1002/asmb.911     Document Type: Article

References (36)

1. Montgomery DC,. Introduction to statistical quality control. John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2005
2. Ferrer A,. Statistical Control of Measures and Processes. Comprehensive Chemometrics, Vol. 1, Brown S, Tauler R, Walczak R, (eds). Elsevier: Oxford, 2009; 97-126.
3. Ferrer A,. Multivariate statistical process control based on principal component analysis (MSPC-PCA): Some reflections and a case study in an autobody assembly process. Quality Engineering 2007; 19 (4): 311-326.
4. Wise BM, Gallagher MB, Bro R, Shaver JM, Windig W, Koch RC,. PLS toolbox 4.0 manual. Eigenvector research Inc.: WA, USA, 2006.
5. Kourti T,. Application of latent variable methods to process control and multivariate statistical process control in industry. International Journal of adaptive control and signal processing 2005; 19: 213-246. (Pubitemid 40680649)
6. Kourti T, MacGregor JF,. Multivariate SPC Methods for Process and Product Monitoring. Journal of Quality Technology 1996; 28 (4): 409-428. (Pubitemid 126588616)
7. Frost AR, Schofield CP, Beaulah SA, Mottram TT, Lines JA, Wathes CM,. A review of livestock monitoring and the need for integrated systems. Computers and Electronics in Agriculture 1997; 17: 139-159. (Pubitemid 127425728)
8. Wathes CM, Kristensen HH, Aerts JM, Berckmans D,. Is precision livestock farming an engineer's daydream or nightmare, an animal's friend or foe, and a farmer's panacea or pitfall?. Computers and Electronics in Agriculture 2008; 64: 2-10.
9. Noordhuizen J, Frankena K, Stassen E, Brand A,. Applied epidemiology in aid to dairy herd health programs. Proceedings of the XVII World Buiatric Congress and the 25th American Association of Bovine Practitioners Conference, Vol. 2, Williams EI, (ed.): St. Paul, MN, USA, 1992; 6-11.
10. Thysen I,. Monitoring bulk tank somatic cell counts by a multiprocess Kalman filter. Acta Agriculturae Scandinavica. Section A. Animal Science 1993; 43: 58-64.
11. Wrathall AE, Hebert CN,. Monitoring reproductive performance in the pig herd. Pig Veterinary Society Proceedings 1982; 9: 136-148.
12. Reneau JK, Lukas J,. Using statistical process control methods to improve herd performance. Veterinary Clinics of North America: Food Animal Practice 2006; 22: 171-193. (Pubitemid 43326207)
13. Mertens K,. An intelligent system for optimizing the production and quality of consumption eggs based on synergistic control. PhD thesis, Katholieke Universiteit Leuven, Belgium, 2009.
14. Devor R, Chang T, Sutherland W,. Statistical quality design and control: contemporary concepts and methods. Prentice Hall, Inc. Simon and Schuster: NJ, USA, 1992.
15. Hawkins D, Olwell D,. Cumulative Sum Charts and Charting for Quality Improvement-Statistics for Engineering and Physical Science. Springer-Verlag Inc.: New York, USA, 1998.
16. del Castillo E,. Statistical process adjustment for quality control (Wiley Series in Probability and Statistics). John Wiley & Sons Inc.: New York, USA, 2002.
17. Ostyn B, De Ketelaere B, Mertens K, Anthonis J, Zoons J, De Baerdemaeker J,. Control charts for online monitoring of non-stationary processes. Proceedings of the 3rd IFAC International Workshop on Bio-Robotics, Information Technology and Intelligent Control for Bioproduction Systems (BIO-ROBOTICS III): Sapporo, Japan, 2006.
18. Box GEP, Paniagua-Quinones C,. Two charts not one. Quality Engineering 2007; 19: 93-100.
19. Box GEP, Narasimhan S,. Rethinking Statistics for Quality Control. Quality Engineering 2010; 22 (2): 60-72.
20. Hoerl RG, Snee R,. Statistical Thinking and Methods in Quality Improvement: A Look to the Future. Quality engineering 2010; 22 (3): 119-129.
21. Box GEP, Jenkins GM, Reinsel GC,. Times Series Analysis. Forecasting and Control, 4thed. Wiley Inc.: New Jersey, 2006.
22. Chen Q, Kruger U, Leung AYT,. Cointegration Testing Method for Monitoring Nonstationary Processes. Industrial & Engineering Chemistry Research 2009; 48 (7): 3533-3543.
23. Mertens K, Vaesen I, Löffel J, Kemps B, Kamers B, Zoons J, Darius P, Decuypere E, De Baerdemaeker J, De Ketelaere B,. An intelligent control chart for monitoring of autocorrelated egg production process data based on a synergistic control strategy. Computers and Electronics in Agriculture 2009; 69 (art.nr. 2284): 100-111.
24. Lokhorst C,. Mathematical curves for the description of input and output variables of the daily production process in aviary housing systems for laying hens. Poultry Science 1996; 75: 838-848. (Pubitemid 126454185)
25. Nomikos P, MacGregor JF,. Multivariate SPC charts for monitoring batch processes. Technometrics 1994; 37: 41-59.
26. Ramaker HJ, van Sprang ENM,. Performance assessment and improvement of control charts for statistical batch process monitoring. Statistica Neerlandica 2005; 60 (3): 339-360.
27. Wold S,. Exponentially weighted moving principal components analysis and projections to latent structures. Chemometrics and Intelligent Laboratory Systems 1994; 23: 149-161. (Pubitemid 24144638)
28. Dayal BS, MacGregor JF,. Recursive exponentially weighted PLS and its applications to adaptive control and prediction. Journal of Process Control 1997; 7 (3): 169-179. (Pubitemid 127372162)
29. Qin SJ,. Recursive PLS algorithms for adaptive data monitoring. Comput. Chemical Engineering 1998; 22: 503-514. (Pubitemid 128714151)
30. Li W, Yue HH, Valle-Cervantes S, Qin SJ,. Recursive PCA for adaptive process monitoring. Journal of process control 2000; 10: 471-486.
31. Fortescue TR, Kershenbaum LS, Ydstie BE,. Implementation of self-tuning regulators with variable forgetting factors. Automatica 1981; 17: 831-835. (Pubitemid 12511922)
32. Choi SW, Martin EB, Morris AJ, Lee IB,. Adaptive Multivariate Statistical Process Control for Monitoring Time-Varying Processes. Industrial & Engineering Chemistry Research 2006; 45 (9): 3108-3118.
33. Barcelõ S, Vidal-Puig S, Ferrer A,. Comparison of Multivariate Statistical Methods for Dynamic Systems Modeling. Quality and Reliability Engineering International 2011; 27: 107-124.
34. Megahed FM, Woodall WH, Camelio JA,. A Review and Perspective on Control Charting with Image Data. Journal of Quality Technology 2011; 43 (2): 83-98.
35. Prats-Montalbán JM, de Juan A, Ferrer A,. Multivariate image analysis: A review with applications. Chemometrics and Intelligent Laboratory Systems 2011; 107: 1-23.
36. McGregor JF,. Using On-Line Process Data to lmprove Quality: Challenges for Statisticians. International Statistical Review 1997; 65 (3): 309-323.