Browsing by Author "Rao, G. Srinivasa"

Now showing 1 - 7 of 7
  • Thumbnail Image
    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-Hyuck
    This 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.
  • Thumbnail Image
    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-Hyuck
    This 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.
  • Thumbnail Image
    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-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.
  • Thumbnail Image
    Item
    Double-acceptance sampling plan for exponentiated fréchet distribution with known shape parameters
    (Hindawi, 2021) Babu, M. Sridhar; Rao, G. Srinivasa; Rosaiah, K.
    We suppose that a product’s lifetime follow the exponentiated Fréchet distribution of defined shape parameters. Based on this assumption, a double-acceptance sampling plan is constructed. The zero and one failure framework is essentially thought of: if no errors are found from the first sample, then the lot is approved; also, if at least two failures occur, it is rejected. In the first sample, if one failure is observed, then the second sample is taken and decided for the same length as the first one. The cumulative sample sizes of the first and second samples are determined on the basis of the stated confidence level of the consumer to ensure that the actual median is longer than the given life. As indicated by the various ratios of the actual median life to specified median lifetime, the operating characteristics are calculated and placed in presented tables. To decrease the risk of the producer at the predefined level, the minimum ratios of this sort are additionally obtained. Lastly, examples are provided for representation reasons for the proposed model.
  • Thumbnail Image
    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, Muhammad
    This 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.
  • Thumbnail Image
    Item
    Monitoring mortality caused by COVID-19 using gamma-distributed variables based on generalized multiple dependent state sampling
    (Hindawi, 2021) Aslam, Muhammad; Rao, G. Srinivasa; Saleem, Muhammad; Ahmad, Rehan; Sherwani, Khan; Jun, Chi-Hyuck
    More recently in statistical quality control studies, researchers are paying more attention to quality characteristics having nonnormal distributions. In the present article, a generalized multiple dependent state (GMDS) sampling control chart is proposed based on the transformation of gamma quality characteristics into a normal distribution. The parameters for the proposed control charts are obtained using in-control average run length (ARL) at specified shape parametric values for different specified average run lengths. The out-of-control ARL of the proposed gamma control chart using GMDS sampling is explored using simulation for various shift size changes in scale parameters to study the performance of the control chart. The proposed gamma control chart performs better than the existing multiple dependent state sampling (MDS) based on gamma distribution and traditional Shewhart control charts in terms of average run lengths. A case study with real-life data from ICU intake to death caused by COVID-19 has been incorporated for the realistic handling of the proposed control chart design.
  • Thumbnail Image
    Item
    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.