A New Robust Control Method for Autocorrelation Processes
The premise of conventional process control chart is that process indicators are independent and identically distributed.However,in practice,many data show complex char-acteristics such as the coexistence of abnormal values and autocorrelation,which makes the conventional control chart ineffective.How to solve these problems has become a hot topic in process control research.In view of this,the following technologies are adopted in this study:1)DAM weight function is used to reduce the weight of outliers in the autocorrelation process,and a robust ARMA model is constructed to extract autocorrelation,and then the interference free residual is obtained;2)The residuals control chart is constructed by using the undisturbed residuals,and its control center line and upper and lower limits are improved robustly to finally construct the robust residuals control chart.Both simulation experiments and empirical anal-ysis show that compared with conventional process control charts and huber control charts,the DAM tailed robust control chart proposed in this study are anti-interference and have better ability to identify outliers in the autocorrelation process monitoring with outliers.
process controlrobust statisticsDAM weight functionabnormal value
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