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Time-Series Modeling for Statistical Process Control

Citations

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Cited by:

  1. Taras Lazariv & Wolfgang Schmid, 2019. "Surveillance of non-stationary processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(3), pages 305-331, September.
  2. Yue Fang & John Zhang, 1999. "Performance of control charts for autoregressive conditional heteroscedastic processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 701-714.
  3. Ioulia Papageorgiou, 2016. "Sampling from Correlated Populations: Optimal Strategies and Comparison Study," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(1), pages 119-151, May.
  4. Johannes Freiesleben & Nicolas Gu'erin, 2015. "Homogenization and Clustering as a Non-Statistical Methodology to Assess Multi-Parametrical Chain Problems," Papers 1505.03874, arXiv.org, revised Dec 2017.
  5. Gulser Koksal & Burcu Kantar & Taylan Ali Ula & Murat Caner Testik, 2008. "The effect of Phase I sample size on the run length performance of control charts for autocorrelated data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(1), pages 67-87.
  6. Hwarng, H. Brian, 2001. "Insights into neural-network forecasting of time series corresponding to ARMA(p,q) structures," Omega, Elsevier, vol. 29(3), pages 273-289, June.
  7. Samari, Goleen & Catalano, Ralph & Alcalá, Héctor E. & Gemmill, Alison, 2020. "The Muslim Ban and preterm birth: Analysis of U.S. vital statistics data from 2009 to 2018," Social Science & Medicine, Elsevier, vol. 265(C).
  8. Pearn, W.L. & Hsu, Ya-Chen, 2007. "Optimal tool replacement for processes with low fraction defective," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1116-1129, August.
  9. I. Civantos & J. García-Algarra, 2020. "Analysis of telecom service operation behavior with time series," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 25-34, March.
  10. George Box & Alberto Luceno, 2002. "Feedforward as a supplement to feedback adjustment in allowing for feedstock changes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(8), pages 1241-1254.
  11. Messaoud, Amor & Weihs, Claus & Hering, Franz, 2008. "Detection of chatter vibration in a drilling process using multivariate control charts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3208-3219, February.
  12. Ridley, D. & Duke, D., 2007. "Moving -window spectral model based statistical process control," International Journal of Production Economics, Elsevier, vol. 105(2), pages 492-509, February.
  13. P. Vellaisamy & S. Sankar & M. Taniguchi, 2003. "Estimation and Design of Sampling Plans for Monitoring Dependent Production Processes," Methodology and Computing in Applied Probability, Springer, vol. 5(1), pages 85-108, March.
  14. Jeffrey E. Jarrett & Xia Pan, 2007. "Monitoring Variability and Analyzing Multivariate Autocorrelated Processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(4), pages 459-469.
  15. Testik, Murat Caner & Sarikulak, Ozgun, 2021. "Change points of real GDP per capita time series corresponding to the periods of industrial revolutions," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
  16. Barbeito, Inés & Zaragoza, Sonia & Tarrío-Saavedra, Javier & Naya, Salvador, 2017. "Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data," Applied Energy, Elsevier, vol. 190(C), pages 1-17.
  17. Chen, Yikai & Durango-Cohen, Pablo L., 2015. "Development and field application of a multivariate statistical process control framework for health-monitoring of transportation infrastructure," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 78-102.
  18. Dong Han & Fugee Tsung & Yanting Li & Jinguo Xian, 2010. "Detection of changes in a random financial sequence with a stable distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(7), pages 1089-1111.
  19. Amira Dridi & Mohamed El Ghourabi & Mohamed Limam, 2012. "On monitoring financial stress index with extreme value theory," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 329-339, March.
  20. Li, Yanting & Wu, Zhenyu, 2020. "A condition monitoring approach of multi-turbine based on VAR model at farm level," Renewable Energy, Elsevier, vol. 166(C), pages 66-80.
  21. Ord, J. Keith & Koehler, Anne B. & Snyder, Ralph D. & Hyndman, Rob J., 2009. "Monitoring processes with changing variances," International Journal of Forecasting, Elsevier, vol. 25(3), pages 518-525, July.
  22. A. A. Kalgonda & S. R. Kulkarni, 2004. "Multivariate Quality Control Chart for Autocorrelated Processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(3), pages 317-327.
  23. W L Pearn & Y-C Hsu & J-J Horng Shiau, 2007. "Tool replacement policy for one-sided processes with low fraction defective," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1075-1083, August.
  24. Miguel Flores & Salvador Naya & Rubén Fernández-Casal & Sonia Zaragoza & Paula Raña & Javier Tarrío-Saavedra, 2020. "Constructing a Control Chart Using Functional Data," Mathematics, MDPI, vol. 8(1), pages 1-26, January.
  25. Croux, C. & Gelper, S. & Mahieu, K., 2010. "Robust Control Charts for Time Series Data," Discussion Paper 2010-107, Tilburg University, Center for Economic Research.
  26. Timothy M. Young & Ampalavanar Nanthakumar & Hari Nanthakumar, 2021. "On the Use of Copula for Quality Control Based on an AR(1) Model," Mathematics, MDPI, vol. 9(18), pages 1-13, September.
  27. A. Snoussi, 2011. "SPC for short-run multivariate autocorrelated processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2303-2312.
  28. Weihs, Claus & Theis, Winfried & Messaoud, Amor & Hering, Franz, 2004. "Monitoring of the BTA Deep Hole Drilling Process Using Residual Control Charts," Technical Reports 2004,60, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  29. Žmuk Berislav, 2016. "Capabilities of Statistical Residual-Based Control Charts in Short- and Long-Term Stock Trading," Naše gospodarstvo/Our economy, Sciendo, vol. 62(1), pages 12-26, March.
  30. P. Vellaisamy & S. Sankar, 2005. "A Unified Approach for Modeling and Designing Attribute Sampling Plans for Monitoring Dependent Production Processes," Methodology and Computing in Applied Probability, Springer, vol. 7(3), pages 307-323, September.
  31. Croux, C. & Gelper, S. & Mahieu, K., 2010. "Robust Control Charts for Time Series Data," Other publications TiSEM 229a21da-3d8a-4764-9d78-5, Tilburg University, School of Economics and Management.
  32. Thaga K. & Kgosi P. M. & Gabaitiri L., 2007. "Max-Chart for Autocorrelated Processes," Stochastics and Quality Control, De Gruyter, vol. 22(1), pages 87-105, January.
  33. Marta Benková & Dagmar Bednárová & Gabriela Bogdanovská & Marcela Pavlíčková, 2023. "Use of Statistical Process Control for Coking Time Monitoring," Mathematics, MDPI, vol. 11(16), pages 1-30, August.
  34. Mohamed El Ghourabi & Amira Dridi & Mohamed Limam, 2015. "A new financial stress index model based on support vector regression and control chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(4), pages 775-788, April.
  35. West, David A. & Mangiameli, Paul M. & Chen, Shaw K., 1999. "Control of complex manufacturing processes: a comparison of SPC methods with a radial basis function neural network," Omega, Elsevier, vol. 27(3), pages 349-362, June.
  36. Dan Zhou & Liu Liu & Xin Lai, 2018. "The Improved EWMA Chart for Heteroscedasticity Process," Annals of Data Science, Springer, vol. 5(1), pages 21-27, March.
  37. M. Aminzadeh, 2009. "Sequential and non-sequential acceptance sampling plans for autocorrelated processes using ARMA(p,q) models," Computational Statistics, Springer, vol. 24(1), pages 95-111, February.
  38. Jinho Kim & Myong K. Jeong & Elsayed A. Elsayed, 2017. "Monitoring multistage processes with autocorrelated observations," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2385-2396, April.
  39. Schmid Wolfgang & Okhrin Yarema, 2003. "Tail behaviour of a general family of control charts," Statistics & Risk Modeling, De Gruyter, vol. 21(1/2003), pages 79-92, January.
  40. Gombay, Edit & Serban, Daniel, 2009. "Monitoring parameter change in time series models," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 715-725, April.
  41. Siu-Tong Au & Rong Duan & Siamak Hesar & Wei Jiang, 2010. "A framework of irregularity enlightenment for data pre-processing in data mining," Annals of Operations Research, Springer, vol. 174(1), pages 47-66, February.
  42. Zan Huang & Dennis K. J. Lin, 2009. "The Time-Series Link Prediction Problem with Applications in Communication Surveillance," INFORMS Journal on Computing, INFORMS, vol. 21(2), pages 286-303, May.
  43. Chen, Yikai & Corr, David J. & Durango-Cohen, Pablo L., 2014. "Analysis of common-cause and special-cause variation in the deterioration of transportation infrastructure: A field application of statistical process control for structural health monitoring," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 96-116.
  44. Dong Han & Fugee Tsung, 2005. "Comparison of the cuscore, GLRT and cusum control charts for detecting a dynamic mean change," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(3), pages 531-552, September.
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