A new process capability index (PCI) control chart for monitoring the process mean using repetitive sampling is presented. The design of the proposed control chart is based on an unbiased estimator Ë†Ïƒ = . s c4 of the process standard deviation for a normally distributed quality characteristic. The formulae for the in-control and out-of-control average run length and the standard deviation of the run length (SDRL) are derived. Tables of in-control and out-of-control average run length (ARL) and SDRL for various shifts, Î´ are presented. The proposed control chart outperforms existing control chart in detecting relatively small process mean shifts in terms of ARLs and SDRLs. Numerical example is presented to demonstrate the application of the proposed chart.
Purpose â€“ The purpose of this paper is to propose a double exponentially weighted moving average control
chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the
efficiency of detecting small process mean shift.
Design/methodology/approach â€“ The algorithm for the implementation of the proposed chart is developed
and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs
are presented for various process mean shift. The performance of the proposed chart is investigated in terms of
the average run-length for small process mean shift and compared with the existing DEWMA control chart.
Numerical examples are given as illustration of the design and implementation of the proposed chart.
Findings â€“ The proposed control chart ismore efficient than the existing DEWMA control chart in the detection
of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift.
However, the performance of the proposed chart relatively deteriorates for large smoothing constants.
Practical implications â€“ The application of repetitive sampling in the control chart literature is gaining
wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in
the detection of small process mean shift by process control personnel.
Originality/value â€“ This paper fills a gap in the literature by examining the performance of the repetitive
sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in
the literature, however, its use based on the DEWMA statistic has not been considered in this context.
Â This paper proposes a process capability index-based control chart for variables using the Downton estimator with a specified Cp value. The proposed chart is able to address the issue of control and capability simultaneously. We also provide a control chart constant to construct the process capability index-based control chart. A numerical example is presented to demonstrate the application of the proposed chart, and the effect of non-normality is discussed. The result shows that the proposed control chart performs better in monitoring and assessing processes, and eliminates the usual two-stage procedure reflected in the literature
Control charts are important tools in statistical process control used to monitor shift in process mean and variance. This paper proposes a control chart for monitoring the process mean using the Downton estimator and provides table of constant factors for computing the control limits for sample size (n â‰¤ 10). The derived control limits for process mean were compared with control limits based on range statistic. The performance of the proposed control charts was evaluated using the average run length for normal and non-normal process situations. The obtained results showed that the XD control chart, using the Downton statistic, performed better than Shewhart Xbar chart using range statistic for detection of small shift in the process mean when the process is non-normal and compares favourably well with Shewhart Xbar chart that is normally distributed.
An efficient alternative to the S control chart for detecting shifts of small magnitude in the process variability using a moving average based on the sample standard deviation s statistic is proposed. Control limit factors are derived for the chart for different values of sample size and span w. The performance of the moving average S chart is compared to the S chart in terms of average run length. The result shows that the performance of moving average S chart for varying values of w outweigh those of the S chart for small and moderate shifts in process variability
Â In this paper cumulative Sum (CUSUM) chart is applied to monitor increase (changes) in the number of HIV/AIDS incidences in Nigeria using the screening result of HIV/AIDS data in Oyo state. The designed scheme is apply to demonstrate the application of the chart and evaluate the performance of the chart in the non manufacturing area. From the evaluation, the chart has a good potential as a SPC tool for monitoring changes in the number of infectious diseases in Nigeria