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Homogeneously Weighted Moving Average Control Chart for Rayleigh Distribution

Author

Listed:
  • Mehwish Butt

    (Department of Economics and Statistics, Dr. Hasan Murad School of Management (HSM), University of Management and Technology Lahore, Pakistan)

  • Hafiza Farwa Amin

    (Department of Statistics, Virtual University of Pakistan)

  • Javed Iqbal

    (Department of Statistics, Virtual University of Pakistan)

  • Maqbool Hussain Sial

    (Department of Economics and Statistics, Dr. Hasan Murad School of Management (HSM), University of Management and Technology Lahore, Pakistan)

  • Najam-ul Hassan

    (Lecturer, Department of Economics, Bhakkar Campus, University of Sargodha, Pakistan)

  • Mueen-ud-Din Azad

    (Department of Economics and Statistics, Dr. Hasan Murad School of Management (HSM), University of Management and Technology Lahore, Pakistan)

Abstract

In this paper we have proposed Homogeneously Weighted Moving Average (HWMA) control chart for Rayleigh distribution. The Average Run Length (ARL1) is used to evaluate the performance of the proposed HWMA control charts. The ARL1 performance of HWMA control chart is compared to the Exponentially weighted moving average (EWMA) control charts with respect to the different shift size (i.e. 10%, 15%, 20%, 30%, 40% increase and decrease in shift). The results are calculated using sample size n=5. It is observed that with the increase in shift proposed HWMA chart shows more efficient results i.e. ARL1 values decrease with the increase in shifts. It is found that the proposed HWMA chart for Rayleigh distribution outperforms the existing EWMA control chart.

Suggested Citation

  • Mehwish Butt & Hafiza Farwa Amin & Javed Iqbal & Maqbool Hussain Sial & Najam-ul Hassan & Mueen-ud-Din Azad, 2023. "Homogeneously Weighted Moving Average Control Chart for Rayleigh Distribution," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 12(3), pages 366-384.
    • Handle: RePEc:rfh:bbejor:v:12:y:2023:i:3:p:366-384
    DOI: https://doi.org/10.61506/01.00043
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    References listed on IDEAS

    as
    1. Muhammad Riaz & Ronald Does, 2009. "A process variability control chart," Computational Statistics, Springer, vol. 24(2), pages 345-368, May.
    2. Petros Maravelakis & John Panaretos & Stelios Psarakis, 2004. "EWMA Chart and Measurement Error," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(4), pages 445-455.
    3. Muhammad Riaz, 2008. "Monitoring process mean level using auxiliary information," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(4), pages 458-481, November.
    Full references (including those not matched with items on IDEAS)

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