Browsing by Author "Ahmad, Liaquat"

Now showing 1 - 5 of 5
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    A control chart for multivariate poisson distribution using repetitive sampling
    (Taylor and Francis Group, 2016) Aslam, Muhammad; Rao, Srinivasa G.; Ahmad, Liaquat; Jun, Chi-Hyuck
    Control charts using repetitive group sampling have attracted a great deal of attention during the last few years. In the present article, we attempt to develop a control chart for the multivariate Poisson distribution using the repetitive group sampling scheme. In the proposed control chart, the monitoring statistic from the multivariate Poisson distribution has been used for the quick detection of the deteriorated process to avoid losses. The control coefficients have been estimated using the specified in-control average run lengths. The procedure of the proposed control chart has been explained by using the real-world example and a simulated data set. It has been observed that the proposed control chart is an efficient development for the quick detection of the nonrandom change in the manufacturing process.
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    Control charts for monitoring process capability index using median absolute deviation for some popular distributions
    (Multidisciplinary Digital Publishing Institute, 2019) Aslam, Muhammad; Rao, G. Srinivasa; AL-Marshadi, Ali Hussein; Ahmad, Liaquat; Jun, Chi-Hyuck
    A control chart monitoring the process capability index (PCI) using median absolute deviation (MAD) is proposed to analyze the industrial process performance. Extensive simulation studies were carried out to evaluate the performance of MAD-based PCI control charts under the low, moderate, and high asymmetric conditions when the process characteristic follows Weibull, log-normal, and gamma distributions. The performance of the proposed control charts was evaluated based on the average run lengths. The practical implementation of the proposed charts was also illustrated with industrial data.
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    Monitoring circuit boards products in the presence of indeterminacy
    (Elsevier, 2021) Aslam, Muhammad; Shafqat, Ambreen; Ahmad, Liaquat; Sherwani, Rehan Ahmad Khan; Rao, Srinivasa G.
    In this article a repetitive group sampling control has been introduced for the neutrosophic statistics under the Conway-Maxwell-Poisson (CoM-Poisson) distribution. The suggested chart has been compared with the existing plan using simulated data generated from neutrosophic COM-Poisson distribution. The practical implementation of the suggested chart has also been expounded using the data from the manufacturing of the electric circuit boards. Overall, the results demonstrate that the suggested chart will be a proficient addition in the control chart literature. It is also observed that the suggested chart is an ideal chart when applied under appropriate conditions.
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    A new control chart using GINI CPK
    (Taylor & Francis, 2020) Aslam, Muhammad; Rao, G. S; Ahmad, Liaquat; Jun, Chi-Hyuck
    Process capability indices (PCIs) have been extensively applied to study product potential and performance. The quality control engineers use these process capability indices greatly to magnify the actual performance of the process from the predetermined specifications of the product. A control chart for the process monitoring is developed using the Gini’s mean difference as a measure of variability under the Weibull distribution. We consider the control chart process capability index, Cpk has been used for the efficient monitoring of the manufacturing process. It has been observed that the proposed chart is comparatively better than the existing chart. An example of the practical application of the proposed chart has also been presented.
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    Two-stage sampling plan using process loss index under neutrosophic statistics
    (Taylor & Francis, 2019) Rao, Srinivasa G.; Aslam, Muhammad; Khan, Nasrullah; Ahmad, Liaquat
    This article develops the designing of two-stage process loss using neutrosophic statistics (NS). The neutrosophic operating characteristic for the two-stage sampling is developed under NS. Neutrosophic plan parameters are obtained using non-linear optimization using the neutrosophic statistical interval method for the constraints. A comparative study is carried out with the existing scheme. Some tables are provided and explained with an example under uncertainty.