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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
We have proposed a New Hybrid Exponentially Weighted Moving Average HEWMA control chart. The proposed control chart is based on a mixture ratio estimator of the mean using a single auxiliary variable and a single auxiliary attribute (Moeen et al., 2012). We call it as Z- HEWMA control chart. The proposed control chart performance is evaluated using out-of-control-Average Run Length (ARL1). The control limits of the proposed chart is based on the estimator, its mean square errors. A simulated data is used to compare the proposed Z-HEWMA, traditional/simple EWMA chart and CUSUM control chart. From this study, the fact is revealed that Z-HEWMA control chart shows more efficient results as compared to traditional/simple EWMA and CUSUM control charts. The Z-HEWMA chart can be used for efficient monitoring of the production process in manufacturing industries where auxiliary information about a numerical variable and an attribute is available.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
We have proposed a New Hybrid Exponentially Weighted Moving Average HEWMA control chart. The proposed control chart is based on a mixture ratio estimator of the mean using a single auxiliary variable and a single auxiliary attribute (Moeen et al., 2012). We call it as Z- HEWMA control chart. The proposed control chart performance is evaluated using out-of-control-Average Run Length (ARL1). The control limits of the proposed chart is based on the estimator, its mean square errors. A simulated data is used to compare the proposed Z-HEWMA, traditional/simple EWMA chart and CUSUM control chart. From this study, the fact is revealed that Z-HEWMA control chart shows more efficient results as compared to traditional/simple EWMA and CUSUM control charts. The Z-HEWMA chart can be used for efficient monitoring of the production process in manufacturing industries where auxiliary information about a numerical variable and an attribute is available.