Browsing by Author "Aslam, Muhammad"
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Item An attribute control chart for multivariate Poisson distribution using multiple dependent state repetitive sampling(Wiley Online Library, 2019) Aldosari, Mansour Sattam; Aslam, Muhammad; Gadde Srinivasa Rao, Gadde Srinivasa; Jun, Chi‐HyuckIn this paper, an attribute control chart for a multivariate Poisson distribution using multiple dependent state repetitive sampling (MDSRS) is presented. The evaluation of the proposed control chart is given through the average run length (ARL). The proposed control chart performs better than the existing control chart based on repetitive sampling and that using multiple dependent state sampling in terms of ARLs. A real example and a simulation study are added to explain the procedure and to demonstrate the power of the proposed control chart.Item Bootstrap confidence intervals of CNpk for inverse Rayleigh and log-logistic distributions(Taylor & Francis, 2016) Rao, G. S; Aslam, Muhammad; Kantam, R. R. LIn this article bootstrap confidence intervals of process capability index as suggested by Chen and Pearn [An application of non-normal process capability indices. Qual Reliab Eng Int. 1997;13:355–360] are studied through simulation when the underlying distributions are inverse Rayleigh and log-logistic distributions. The well-known maximum likelihood estimator is used to estimate the parameter. The bootstrap confidence intervals considered in this paper consists of various confidence intervals. A Monte Carlo simulation has been used to investigate the estimated coverage probabilities and average widths of the bootstrap confidence intervals. Application examples on two distributions for process capability indices are provided for practical use.Item 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-HyuckThe 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.Item Burr-XII distribution parametric estimation and estimation of reliability of multicomponent stress-strength(Taylor and Francis, 2015) Rao, G. S; Aslam, Muhammad; Kundu, DebasisIn this paper, we estimate multicomponent stress-strength reliability by assuming Burr-XII distribution. The research methodology adopted here is to estimate the parameter using maximum likelihood estimation. Reliability is estimated using the maximum likelihood method of estimation and results are compared using the Monte Carlo simulation for small samples. Using real data sets we illustrate the procedure clearly.Item Comparing the efficacy of coefficient of variation control charts using generalized multiple dependent state sampling with various run-rule control charts(Springer Science and Business Media LLC, 2024) Rao, G. Srinivasa; Aslam, Muhammad; Alamri, Faten S.; Jun, Chi-HyuckThis paper aimed to develop a coefficient of variation (CV) control chart utilizing the generalized multiple dependent state (GMDS) sampling approach for CV monitoring. We conducted a comprehensive examination of this designed control chart in comparison to existing control charts based on multiple dependent state sampling (MDS) and the Shewhart-type CV control chart, with a focus on average run lengths. The results were then compared to run-rule control charts available in the existing literature. Additionally, we elucidated the implementation of the proposed control chart through concrete examples and a simulation study. The findings clearly demonstrated that the GMDS sampling control chart shows significantly superior accuracy in detecting process shifts when compared to the MDS sampling control chart. As a result, the control chart approach presented in this paper holds significant potential for applications in textile and medical industries, particularly when researchers seek to identify minor to moderate shifts in the CV, contributing to enhanced quality control and process monitoring in these domains.Item Comparing the efficacy of coefficient of variation control charts using generalized multiple dependent state sampling with various run-rule control charts(Springer Science and Business Media LLC, 2024) Rao, G. Srinivasa; Aslam, Muhammad; Alamri, Faten S.; Jun, Chi-HyuckThis paper aimed to develop a coefficient of variation (CV) control chart utilizing the generalized multiple dependent state (GMDS) sampling approach for CV monitoring. We conducted a comprehensive examination of this designed control chart in comparison to existing control charts based on multiple dependent state sampling (MDS) and the Shewhart-type CV control chart, with a focus on average run lengths. The results were then compared to run-rule control charts available in the existing literature. Additionally, we elucidated the implementation of the proposed control chart through concrete examples and a simulation study. The findings clearly demonstrated that the GMDS sampling control chart shows significantly superior accuracy in detecting process shifts when compared to the MDS sampling control chart. As a result, the control chart approach presented in this paper holds significant potential for applications in textile and medical industries, particularly when researchers seek to identify minor to moderate shifts in the CV, contributing to enhanced quality control and process monitoring in these domains.Item A control chart based on two-piece normal distribution using repetitive sampling(College of Statistical and Actuarial Sciences, University of the Punjab, 2018) Rao, Gadde Srinivas; Aslam, Muhammad; Azam, Muhammad; Jun, Chi - HyuckIn this manuscript, a control chart is designed for two-piece normal distribution using repetitive sampling. The necessary measures to determine the average run lengths for in control and out of control process are given. The average run lengths are presented for various specified parameters and shift constants. The efficiency of the proposed chart is compared with the existing control chart using single sampling. The application of the proposed chart is given with the help of an example.Item A control chart for multivariate poisson distribution using repetitive sampling(Taylor and Francis Group, 2016) Aslam, Muhammad; Rao, Srinivasa G.; Ahmad, Liaquat; Jun, Chi-HyuckControl 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.Item 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-HyuckA 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.Item Design of chart for a birnbaum saunders distribution under accelerated hybrid censoring(Taylor & Francis., 2018) Khan, Nasrullah; Rao, Srinivasa G.; Aslam, MuhammadIn this manuscript, attribute control chart for the Birnbaum Saunders distribution under the accelerated hybrid censoring is studied. We planned a new control chart is based on accelerated factor. The necessary measures to evaluate the performance of proposed control chart are given. The parameters of proposed control chart are determined such that the conditions are meet for average run length for in-control and shifted process. The average run length is used to study the performance of proposed control chart with the traditional Shewhart attribute control chart. An example is also given for demonstrate proposed method.Item The efficacy of process capability indices using median absolute deviation and their bootstrap confidence intervals(Springer, 2017) Kashif, Muhammad; Aslam, Muhammad; Jun, Chi-Hyuck; Al-Marshadi, Ali Hussein; Rao, Srinivasa G.The process capability indices (PCIs) Cp and C pk are commonly used in industry to measure the process performance.The implementation of these indices required that process should follow a normal distribution. However, in many cases the underlying processes are non-normal which influence the performance of these indices. In this paper, median absolute deviation (MAD)is used as a robust measure of variability in two PCIs, Cp and Cpk . Extensive simulation experiments were performed to evaluate the performance of MAD-based PCIs under low, moderate and high asymmetric condition of Weibull, Log-Normal and Gamma distributions. The point estimation of MAD-based estimator of Cp and Cpk is encouraging and showed a good result in case of Log- Normal and Gamma distributions, whereas these estimators perform very well in case of Weibull distribution. The comparison of quantile method and MAD method showed that the performance of MAD-based PCIs is better for Weibull and Log-Normal processes under low and moderate asymmetric conditions, whereas its performance for Gamma distribution remained unsatisfactory. Four bootstrap confidence intervals (BCIs) such as standard (SB), percentile (PB), bias-corrected percentile (BCPB) and percentile-t (PTB) were constructed using quantile and MAD methods under all asymmetric conditions of three distributions under study. The bias-corrected percentile bootstrap confidence interval (BCPB) is recommended for a quantile (PC)-based PCIs, whereas CIs were recommended for MAD-based PCIs under all asymmetric conditions of Weibull, Log-Normal and Gamma distributions. A real-life example is also given to describe and validate the application of proposed methodology.Item Estimation of reliability in a multicomponent stress–strength system for the exponentiated moment-based exponential distribution(Multidisciplinary Digital Publishing Institute, 2019) Rao, Srinivasa G.; Bhatti, Fiaz Ahmad; Aslam, Muhammad; Albassam, MohammedA multicomponent system of k components with independent and identically distributed random strengths X 1, X 2 , … X k , with each component undergoing random stress, is in working condition if and only if at least s out of k strengths exceed the subjected stress. Reliability is measured while strength and stress are obtained through a process following an exponentiated moment-based exponential distribution with different shape parameters. Reliability is gauged from the samples using maximum likelihood (ML) on the computed distributions of strength and stress. Asymptotic estimates of reliability are compared using Monte Carlo simulation. Application to forest data and to breaking strengths of jute fiber shows the usefulness of the model.Item Estimation of reliability in multicomponent stress–strength based on two parameter exponentiated weibull distribution(Taylor and Francis Group, 2017) Rao, Srinivasa G.; Aslam, Muhammad; Arif, Osama H.In this research article, we estimate the multicomponent stress–strength reliability of a system when strength and stress variates are drawn from an exponentiated Weibull distribution with different shape parameters α and β, and common shape and scale parameters γ and λ, respectively. We estimate the parameters by using maximum likelihood estimation (MLE) and hence the estimate of reliability obtained applying the MLE method of estimation when samples are drawn from stress and strength distributions. The small sample comparison of the reliability estimates is made through Monte Carlo simulation.Item Evaluation of bootstrap confidence intervals using a new non-normal process capability index(Multidisciplinary Digital Publishing Institute, 2019) Rao, Gadde Srinivasa; Albassam, Mohammed; Aslam, MuhammadThis paper assesses the bootstrap confidence intervals of a newly proposed process capability index (PCI) forWeibull distribution, using the logarithm of the analyzed data. These methods can be applied when the quality of interest has non-symmetrical distribution. Bootstrap confidence intervals, which consist of standard bootstrap (SB), percentile bootstrap (PB), and bias-corrected percentile bootstrap (BCPB) confidence interval are constructed for the proposed method. A Monte Carlo simulation study is used to determine the efficiency of newly proposed index Cpkw over the existing method by addressing the coverage probabilities and average widths. The outcome shows that the BCPB confidence interval is recommended. The methodology of the proposed index has been explained by using the real data of breaking stress of carbon fibers.Item EWMA control chart using repetitive sampling for monitoring blood glucose levels in type-II diabetes patients(MDPI, 2019) Aslam, Muhammad; Rao, Gadde Srinivasa; Khan, Nasrullah; Al-Abbasi, Fahad A.Abstract: In this paper, we discuss the application of the exponentially weighted moving average (EWMA) control chart for the monitoring blood glucose in type-II diabetes patients. We present tables for the practical use in healthcare. From the simulation results and a real example, the efficiency of the proposed chart in detecting a shift in diabetic level is compared with the existing chart. It is found that the proposed chart provides a strict method to monitor the diabetic levels in diabetes patients. From the simulation results and a real example, it is concluded that the use of the proposed chart in health care issues may reduce the risk of heart disease by monitoring diabetic levels in an effective way.Item Life truncated multiple dependent state plan for imprecise Weibull distributed data(Springer Science and Business Media LLC, 2024) Rao, Gadde Srinivasa; Aslam, Muhammad; Josephat, Peter Kirigiti; Al-Husseini, Zainalabideen; Albassam, MohammedThis paper aims to provide a multiple dependent state (MDS) sampling technique for light-emitting diode luminous intensities under indeterminacy by employing time truncated sampling schemes and the Weibull distribution. This indicates that ASN is significantly impacted by the indeterminacy parameter. Furthermore, a comparison is shown between the existing, indeterminate sampling plans and the recommended sample designs. The projected sampling technique is illustrated by calculating the luminous intensities of LEDs using the Weibull distribution. Based on the findings and practical example, we conclude that the suggested strategy needs a smaller sample size than SSP and the current MDS sampling plan.Item Mixed EWMA–CUSUM chart for COM-Poisson distribution(Taylor & Francis, 2020) Rao, Gadde Srinivasa; Aslam, Muhammad; Rasheed, Umer; Jun, Chi-HyuckIn this article, we develop a mixed (SPC) control chart for monitoring moderate and/or small shift in the process following the Conway Maxwell Poisson (COM-Poisson) distribution. To determine the ability and performance of the proposed mixed EWMA-CUSUM control chart, we evaluate the average run lengths and compare with different control charts. We will compare the efficiency of the proposed control chart over the existing control charts in terms of average run length. The results show an improvement in ARL when compared with the existing charts. A real example and a simulation study is also added to use the chart in the industry.Item Monitoring air quality using the neural network based control chart(Springer Science and Business Media LLC, 2023) Azmat, Sumaira; Sabir, Qurat Ul An; Tariq, Saadia; Shafqat, Ambreen; Rao, G. Srinivasa; Aslam, MuhammadThis paper intends to develop ANN (artificial neural network) based control charts. The (ANN) is a machine learning (ML) methodology that evolved and developed from the scheme of imitating the human brain. ANN has been explained by discussing the network topology and development parameters (number of nodes, number of hidden layers, learning rules, and activated function). Among many models that deal with combining factors and data-based supervised learning classifiers, ANN has the most significant impact on air quality as air quality has nonlinear and noisy data. The best activation of a new hybrid EWMA (HEWMA) control chart is proposed by mixing two EWMA control charts to efficiently monitor the process mean. The ANN-based HEWMA scheme was a promising procedure for the detection of air quality measurements. We compare the performance of the ANN-based HEWMA control chart and the EWMA control chart based on average run lengths when the data are contaminated with the measurement error. The results revealed that the higher the temperature, the better fitting shape we obtain from air quality parameters. The ANN-based HEWMA control chart deals with measurement errors more efficiently than the EWMA control chart.Item Monitoring circuit boards products in the presence of indeterminacy(Elsevier Ltd, 2021) Aslam, Muhammad; Rao, Srinivasa G.; Shafqat, Ambreen; Liaquat, Ahmad; Rehan, ShweraniIn 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.Item 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.