Browsing by Author "AL-Marshadi, Ali Hussein"

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    Bootstrap confidence intervals of the modified process capability Index for weibull distribution
    (Springer, 2017) Kashif, Muhammad; Aslam, Muhammad; Rao, Srinivasa G.; AL-Marshadi, Ali Hussein; Jun, Chi-Hyuck
    The objective of the paper is to modify the existing process capability index (PCI) for a Weibull distribution and to construct bootstrap confidence intervals (BCIs) for the newly proposed index. Three BCIs that consist of standard, percentile and bias-corrected percentile bootstrap (BCPB) confidence intervals are constructed for the newly proposed index and the existing Pearn and Chen index. The efficiency of the newly proposed index CGPK is compared with Pearn and Chen index using their coverage probabilities and average widths. The coverage probabilities and average width of three BCIs were calculated using Monte Carlo simulation studies. The newly proposed index shows better performance than Pearn and Chen index. The results indicate that BCPB confidence interval was more efficient in both cases and outperform other two confidence intervals in all situations. The comparison of average width of BCPB apparently shows that the proposed index performed better in all cases. A real-life example is also provided for a practical application.
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    A nonparametric HEWMA-p control chart for variance in monitoring processes
    (Symmetry, 2019) Aslam, Muhammad; Rao, Gadde Srinivasa; AL-Marshadi, Ali Hussein; Jun, Chi-Hyuck
    Control charts are considered as powerful tools in detecting any shift in a process. Usually, the Shewhart control chart is used when data follows the symmetrical property of a normal distribution. In practice, the data from the industry may follow a non-symmetrical distribution or an unknown distribution. The average run length (ARL) is a significant measure to assess the performance of the control chart. The ARL may mislead when the statistic is computed from an asymmetric distribution. To handle this issue, in this paper, an ARL-unbiased hybrid exponentially weighted moving average proportion (HEWMA-p) chart is proposed for monitoring the process variance for a non-normal distribution or an unknown distribution. The efficiency of the proposed chart is compared with the existing chart in terms of ARLs. The proposed chart is more efficient than the existing chart in terms of ARLs. A real example is given for the illustration of the proposed chart in the industry.
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    A variable control chart based on process capability index under generalized multiple dependent state sampling
    (Institute of Electrical and Electronics Engineers, 2019) Rao, G. Srinivasa; Raza, Muhammad Ali; Aslam, Muhammad; AL-Marshadi, Ali Hussein; Jun, Chi-Hyuck
    This paper proposed a process capability index-based control chart under the new extended form of multiple-dependent state sampling (MDS) named generalized MDS (GMDS). The scheme is based on inner and outer control limits and utilizes the previous state of the samples. The performance comparisons of the proposed chart with the existing charts are made by using out-of-control ARL. The simulation study showed the superiority of the proposed chart over the existing PCI-based control charts under Shewhart and MDS schemes. An empirical illustration is also given to demonstrate the application of the proposed chart.