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Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring

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  • Jimoh Olawale Ajadi
  • Muhammad Riaz

Abstract

Multivariate exponential weighted moving average and cumulative sum charts are the most common memory type multivariate control charts. They make use of the present and past information to detect small shifts in the process parameter(s). In this article, we propose two new multivariate control charts using a mixed version of their design setups. The plotting statistics of the proposed charts are based on the cumulative sum of the multivariate exponentially weighted moving averages. The performances of these schemes are evaluated in terms of average run length. The proposals are compared with their existing counterparts, including HotellingT2, MCUSUM, MEWMA, and MC1 charts. An application example is also presented for practical considerations using a real dataset.

Suggested Citation

  • Jimoh Olawale Ajadi & Muhammad Riaz, 2017. "Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(14), pages 6980-6993, July.
  • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:14:p:6980-6993
    DOI: 10.1080/03610926.2016.1139132
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    Cited by:

    1. Muhammad Riaz & Babar Zaman & Ishaq Adeyanju Raji & M. Hafidz Omar & Rashid Mehmood & Nasir Abbas, 2022. "An Adaptive EWMA Control Chart Based on Principal Component Method to Monitor Process Mean Vector," Mathematics, MDPI, vol. 10(12), pages 1-27, June.
    2. Muhammad Aslam & Syed Masroor Anwar, 2020. "An improved Bayesian Modified-EWMA location chart and its applications in mechanical and sport industry," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-19, February.
    3. Jean-Claude Malela-Majika & Schalk William Human & Kashinath Chatterjee, 2024. "Homogeneously Weighted Moving Average Control Charts: Overview, Controversies, and New Directions," Mathematics, MDPI, vol. 12(5), pages 1-30, February.
    4. Nasir Abbas & Muhammad Riaz & Shabbir Ahmad & Muhammad Abid & Babar Zaman, 2020. "On the Efficient Monitoring of Multivariate Processes with Unknown Parameters," Mathematics, MDPI, vol. 8(5), pages 1-32, May.

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