Abstract
In this paper, two new control charts have been proposed, one is shewhart-type and other one is EWMA-type control chart. The proposed control charts are based on the exponential type estimator for mean proposed by Noor-ul-Amin and Hanif (2012). We name them as DS-Shewhart control chart and DS-EWMA control chart. The results shows that the DS-Shewhart control chart shows more efficient results to traditional/simple Shewhart and EWMA control charts whereas, the DS-EWMA control chart shows more efficient results to traditional Exponentially Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) control charts because they uses the information from two phase sampling with two auxiliary variables. The proposed control charts can be used for efficient monitoring of the production process in manufacturing industries. The control limits of the proposed chart are based on estimator, its mean square errors and bias. A simulated example has been used to compare the proposed and traditional/simple EWMA and CUSUM control charts performance based on the average run length-out of control (ARL 1 ). It is observed that the proposed chart performs better than existing EWMA and CUSUM control charts. At the end of the paper a real life implementation of the proposed control charts is also provided.
Highlights
Grant & Leavenworth (1979) describe the “Statistical Process Control (SPC)” as a “useful and important tool used commonly in engineering field to monitor the overall process.” SPC can be applied to all kinds of engineering operations
We call it as Double sampling (DS)-Exponentially Weighted Moving Average (EWMA) control chart as it is based on two phase sampling with two auxiliary variables
The exponentially weighted moving average (EWMA) control chart is applied on the samples and results are compared with DS- EWMA chart
Summary
Grant & Leavenworth (1979) describe the “Statistical Process Control (SPC)” as a “useful and important tool used commonly in engineering field to monitor the overall process.” SPC can be applied to all kinds of engineering operations. Grant & Leavenworth (1979) describe the “Statistical Process Control (SPC)” as a “useful and important tool used commonly in engineering field to monitor the overall process.”. Montgomery (2007) states that the processes that are operating in the presence of assignable/special causes can be abbreviated as out of control. Gupta & Gupta (2009) defined the statistical quality control as one of the most useful and economically important applications of the theory of sampling in the industrial field. Statistical Process Control is usually referred as “SPC”. It is a method which includes monitoring, controlling and refining of a process. 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. The exponential ratio type estimator is used when the auxiliary variable and the variable of interest is positively or negatively correlated
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