This paper deals with a novel method of estimating the process spread (σ) in the construction of Shewhart control chart for means, basing ona new estimatederived from the confidence interval (CI) of sample range. The classical estimate ( /d2,n)of σ for a normally distributed data is utilized to arrive at anew estimateproposed as the weighted sum of the lower, middle and upper values of the 100(1-α) %CI for the process rangebasing on sample range.The weights are defined as inversely proportional to the absolute bias from the target spread. It is shown by simulation that the new estimate is more consistent than the classical point estimate based on /d2,n. It is also shown that the chart performs better in terms of β-risk when the new estima...
Standard Shewhart X control charts with estimated control limits are widely used in practice. There ...
The presence of outliers and contaminations in the output of the process highly affects the performa...
The interconnection between confidence interval estimation and statistical decision making with cont...
This paper deals with a novel method of estimating the process spread (σ) in the construction of She...
The probability of a false alarm rate (type I risk) in Shewhart control charts based on a normal dis...
Shewhart control charts are among the most popular control charts used to monitor process dispersion...
A control chart for detecting shifts in the variance of a process is developed for the case where th...
Control charts are extensively used in many real world applications. Since process parameters are ra...
Several recent studies have shown that the number of Phase I samples required for a Phase II control...
Although the Shewhart chart is widely used in practice because of its simplicity, applying this cont...
A number of processes to which statistical control is applied are subject to various effects that ca...
Nonparametric or distribution-free charts can be useful in statistical process control problems when...
The Shewhart and the Bonferroni-adjustment S control charts are usually applied to monitor the stand...
Nonparametric or distribution-free charts can be useful in statistical process control when there is...
Control chart is a powerful technique that can be of immense use in an industrial process in many wa...
Standard Shewhart X control charts with estimated control limits are widely used in practice. There ...
The presence of outliers and contaminations in the output of the process highly affects the performa...
The interconnection between confidence interval estimation and statistical decision making with cont...
This paper deals with a novel method of estimating the process spread (σ) in the construction of She...
The probability of a false alarm rate (type I risk) in Shewhart control charts based on a normal dis...
Shewhart control charts are among the most popular control charts used to monitor process dispersion...
A control chart for detecting shifts in the variance of a process is developed for the case where th...
Control charts are extensively used in many real world applications. Since process parameters are ra...
Several recent studies have shown that the number of Phase I samples required for a Phase II control...
Although the Shewhart chart is widely used in practice because of its simplicity, applying this cont...
A number of processes to which statistical control is applied are subject to various effects that ca...
Nonparametric or distribution-free charts can be useful in statistical process control problems when...
The Shewhart and the Bonferroni-adjustment S control charts are usually applied to monitor the stand...
Nonparametric or distribution-free charts can be useful in statistical process control when there is...
Control chart is a powerful technique that can be of immense use in an industrial process in many wa...
Standard Shewhart X control charts with estimated control limits are widely used in practice. There ...
The presence of outliers and contaminations in the output of the process highly affects the performa...
The interconnection between confidence interval estimation and statistical decision making with cont...