MS/M.Phil DQM (Economics and Qualitative Management

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Browsing MS/M.Phil DQM (Economics and Qualitative Management by Author "Hafiz Zain Pervaiz"

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    A NEW HYBRID EXPONENTIALLY WEIGHTED MOVING AVERAGE CONTROL CHART USING MIXTURE RATIO ESTIMATOR OF MEAN
    (UMT.Lahore, 2020) Hafiz Zain Pervaiz
    The Control charts are the most important tool of Statistical Process Control (SPC) tool kit. It is commonly used to differentiate between the “assignable and un-assignable causes.”The purpose of the effective process monitoring system is to detect the presence of an “assignable cause.” The control charts are of different types. Some are “memory control charts” and other is “memory-less control charts.”Shewhart are memory-less control charts and are being used to detect a large size shift whereas the memory type charts are used for dealing with small size shifts. The use of statistical quality control charts in different fields of life revealed that the most of the control charts are structured to cater information about the quality characteristic/ studied variable. If we are able to acquire some information about some other variable(s) which is correlated with our variable of interest, we can enhance the efficiency of the control chart by the efficient charting statistic. The additional information is known as auxiliary information and the variable providing the additional information is referred as auxiliary variable. This additional/auxiliary information is used at different points in survey sampling to estimate the unknown parameters. Whenever the auxiliary information is used in the parameter estimation process, the precision of the estimating the parameter is improved. In this thesis, we proposed A New Hybrid Exponentially Weighted Moving Average HEWMA control chart. The proposed control chart is based ona mixture ratio estimator of 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 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.