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Original Articles

Shift detection and source identification in multivariate autocorrelated processes

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Pages 835-859 | Received 12 Sep 2007, Accepted 11 Aug 2008, Published online: 17 Nov 2008

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Huu Du Nguyen, Adel Ahmadi Nadi, Kim Duc Tran, Philippe Castagliola, Giovanni Celano & Kim Phuc Tran. (2023) The Shewhart-type RZ control chart for monitoring the ratio of autocorrelated variables. International Journal of Production Research 61:20, pages 6746-6771.
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Roberto Campos Leoni, Marcela Aparecida Guerreiro Machado & Antonio Fernando Branco Costa. (2016) The T2 chart with mixed samples to control bivariate autocorrelated processes. International Journal of Production Research 54:11, pages 3294-3310.
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J. Kim, K.N. Al-Khalifa, M.K. Jeong, A.M.S. Hamouda & E.A. Elsayed. (2014) Multivariate statistical process control charts based on the approximate sequential χ2 test. International Journal of Production Research 52:18, pages 5514-5527.
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Liping Liu, Yizhong Ma & Yiliu Tu. (2013) Multivariate setup adjustment with fixed adjustment cost. International Journal of Production Research 51:5, pages 1392-1404.
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Arthur B. Yeh, Bo Li & Kaibo Wang. (2012) Monitoring multivariate process variability with individual observations via penalised likelihood estimation. International Journal of Production Research 50:22, pages 6624-6638.
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Daniel Ashagrie Tegegne, Daniel Kitaw Azene & Eshetie Berhan Atanaw. (2022) Design multivariate statistical process control procedure in the case of Ethio cement. International Journal of Quality & Reliability Management 39:7, pages 1617-1636.
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Yaping Li, Haiyan Li, Zhen Chen & Ying Zhu. (2022) An Improved Hidden Markov Model for Monitoring the Process with Autocorrelated Observations. Energies 15:5, pages 1685.
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Sotiris Bersimis, Aggeliki Sgora & Stelios Psarakis. (2021) A robust meta‐method for interpreting the out‐of‐control signal of multivariate control charts using artificial neural networks. Quality and Reliability Engineering International 38:1, pages 30-63.
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Miao Xu, Bo Zhu, Chunmei Chen & Yuwei Wan. (2022) On-line Recognition of Abnormal Patterns in Bivariate Autocorrelated Process Using Random Forest. Computers, Materials & Continua 73:1, pages 1707-1722.
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Mohammad Hadi Doroudyan & Seyed Taghi Akhavan Niaki. (2021) Pattern recognition in financial surveillance with the ARMA-GARCH time series model using support vector machine. Expert Systems with Applications 182, pages 115334.
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Yu-wei Wan & Bo Zhu. (2021) Abnormal patterns recognition in bivariate autocorrelated process using optimized random forest and multi-feature extraction. ISA Transactions 109, pages 102-112.
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Shumei Chen & Jianbo Yu. (2019) Deep recurrent neural network‐based residual control chart for autocorrelated processes. Quality and Reliability Engineering International 35:8, pages 2687-2708.
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Yuehjen E. Shao & Shih-Chieh Lin. (2019) Using a Time Delay Neural Network Approach to Diagnose the Out-of-Control Signals for a Multivariate Normal Process with Variance Shifts. Mathematics 7:10, pages 959.
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Ponnusamy Venkumar. 2019. Industry 4.0 and Hyper-Customized Smart Manufacturing Supply Chains. Industry 4.0 and Hyper-Customized Smart Manufacturing Supply Chains 263 293 .
Zhu Bo, Liu Beibei, Wan Yuwei & Zhao Shengran. (2018) Recognition of control chart patterns in auto-correlated process based on random forest. Recognition of control chart patterns in auto-correlated process based on random forest.
Zhen He, Zhiqiong Wang, Fugee Tsung & Yanfen Shang. (2016) A control scheme for autocorrelated bivariate binomial data. Computers & Industrial Engineering 98, pages 350-359.
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Felipe Domingues Simões, Roberto Campos Leoni, Marcela Aparecida Guerreiro Machado & Antonio Fernando Branco Costa. (2016) Synthetic charts to control bivariate processes with autocorrelated data. Computers & Industrial Engineering 97, pages 15-25.
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Yuehjen E. Shao. (2016) Using a Computational Intelligence Hybrid Approach to Recognize the Faults of Variance Shifts for a Manufacturing Process. Journal of Industrial and Intelligent Information.
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Roberto Campos Leoni, Marcela Aparecida Guerreiro Machado & Antonio Fernando Branco Costa. (2015) Simultaneous Univariate X_bar Charts to Control Bivariate Processes with Autocorrelated Data. Quality and Reliability Engineering International 31:8, pages 1641-1648.
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Roberto Campos Leoni, Antonio Fernando Branco Costa & Marcela Aparecida Guerreiro Machado. (2015) The effect of the autocorrelation on the performance of the T 2 chart. European Journal of Operational Research 247:1, pages 155-165.
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Roberto Campos Leoni, Antonio Fernando Branco Costa, Bruno Chaves Franco & Marcela Aparecida Guerreiro Machado. (2015) The skipping strategy to reduce the effect of the autocorrelation on the T 2 chart’s performance. The International Journal of Advanced Manufacturing Technology 80:9-12, pages 1547-1559.
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Roberto Campos Leoni, Antonio Fernando Branco Costa & Marcela Aparecida Guerreiro Machado. (2014) AVALIAÇÃO DO DESEMPENHO DE GRÁFICOS SIMULTÂNEOS UNIVARIADOS DE X E T2 DE HOTELLING EM PROCESSOS BIVARIADOS COM AUTOCORRELAÇÃO. AVALIAÇÃO DO DESEMPENHO DE GRÁFICOS SIMULTÂNEOS UNIVARIADOS DE X E T2 DE HOTELLING EM PROCESSOS BIVARIADOS COM AUTOCORRELAÇÃO.
Yuehjen E. Shao. (2014) Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches. Abstract and Applied Analysis 2014, pages 1-9.
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A. Ghiasabadi, R. Noorossana & A. Saghaei. (2013) Identifying change point of a non-random pattern on control chart using artificial neural networks. The International Journal of Advanced Manufacturing Technology 67:5-8, pages 1623-1630.
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Yuehjen E. Shao & Chia-Ding Hou. (2013) Hybrid Artificial Neural Networks Modeling for Faults Identification of a Stochastic Multivariate Process. Abstract and Applied Analysis 2013, pages 1-10.
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Chi Zhang & Zhen He. 2013. Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012). Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) 225 232 .
Wafik Hachicha & Ahmed Ghorbel. (2012) A survey of control-chart pattern-recognition literature (1991–2010) based on a new conceptual classification scheme. Computers & Industrial Engineering 63:1, pages 204-222.
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Stelios Psarakis. (2011) The use of neural networks in statistical process control charts. Quality and Reliability Engineering International 27:5, pages 641-650.
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