A multivariate synthetic double sampling T2 control chart

In this article, we propose a multivariate synthetic double sampling T^2 chart to monitor the mean vector of a multivariate process. The proposed chart combines the double sampling (DS) T^2 chart and the conforming run length (CRL) chart. On the whole, the proposed chart performs better than its standard counterparts, namely, the Hotelling's T^2, DS T^2, and synthetic T^2 charts, in terms of the average run length (ARL) and average number of observations to sample (ANOS). The proposed chart also outperforms the multivariate exponentially weighted moving average (MEWMA) chart for moderate and large shifts but the latter is more sensitive than the former towards small shifts. For a variable sample size chart, like the synthetic DS T^2 chart, ANOS is a more meaningful performance measure than ARL. ANOS relates to the actual number of observations sampled but ARL merely deals with the number of sampling stages taken. Interpretation based on ARL is more complicated as either n"1 or n"1+n"2 observations are taken in each sampling stage.

[1]  Rassoul Noorossana,et al.  Phase II monitoring of multivariate simple linear profiles , 2010, Comput. Ind. Eng..

[2]  Jianbo Yu,et al.  Using Minimum Quantization Error chart for the monitoring of process states in multivariate manufacturing processes , 2009, Comput. Ind. Eng..

[3]  Patrick D. Bourke,et al.  Detecting a shift in fraction nonconforming using runlength control charts with 100% inspection , 1991 .

[4]  Francisco Aparisi,et al.  Double sampling hotelling's T2 charts , 2008, Qual. Reliab. Eng. Int..

[5]  Marcela A. G. Machado,et al.  Control charts for monitoring the mean vector and the covariance matrix of bivariate processes , 2009 .

[6]  Jean-Jacques Daudin,et al.  Double sampling X charts , 1992 .

[7]  A. Grigoryan,et al.  Multivariate double sampling |S| charts for controlling process variability , 2005 .

[8]  Antonio Fernando Branco Costa,et al.  Synthetic control charts with two-stage sampling for monitoring bivariate processes , 2007 .

[9]  Antonio Fernando Branco Costa,et al.  Bivariate control charts with double sampling , 2008 .

[10]  D. T. Shirke,et al.  A Multivariate Synthetic Control Chart for Monitoring Process Mean Vector , 2008 .

[11]  Trevor A Spedding,et al.  A Synthetic Control Chart for Detecting Small Shifts in the Process Mean , 2000 .

[12]  Ruey-Shiang Guh,et al.  An effective application of decision tree learning for on-line detection of mean shifts in multivariate control charts , 2008, Comput. Ind. Eng..

[13]  Antonio Fernando Branco Costa,et al.  The synthetic control chart based on two sample variances for monitoring the covariance matrix , 2009, Qual. Reliab. Eng. Int..

[14]  Michael B. C. Khoo,et al.  Optimal Statistical Design of a Multivariate EWMA Chart Based on ARL and MRL , 2006 .

[15]  William H. Woodall,et al.  Evaluating and Improving the Synthetic Control Chart , 2002 .

[16]  Francisco Aparisi,et al.  The Design and Performance of the Multivariate Synthetic-T 2 Control Chart , 2009 .

[17]  Zhang Wu,et al.  A Multivariate Synthetic Control Chart for Monitoring the Process Mean Vector of Skewed Populations Using Weighted Standard Deviations , 2009, Commun. Stat. Simul. Comput..

[18]  D. T. Shirke,et al.  A Multivariate Synthetic Control Chart for Process Dispersion , 2008 .

[19]  Hassen Taleb,et al.  Control charts applications for multivariate attribute processes , 2009, Comput. Ind. Eng..

[20]  Philippe Castagliola,et al.  A synthetic double sampling control chart for the process mean , 2010 .

[21]  Philippe Castagliola,et al.  Optimal designs of the multivariate synthetic chart for monitoring the process mean vector based on median run length , 2011, Qual. Reliab. Eng. Int..

[22]  Douglas C. Montgomery,et al.  Statistical quality control : a modern introduction , 2009 .

[23]  Chuen-Sheng Cheng,et al.  Using neural networks to detect the bivariate process variance shifts pattern , 2011, Comput. Ind. Eng..

[24]  D. He,et al.  Multivariate multiple sampling charts , 2005 .