Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring |
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Authors: | Jimoh Olawale Ajadi |
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Affiliation: | Department of Mathematics and Statistics, King Fahd University of Petroleum and Minerals, Dhahran, Kingdom of Saudi Arabia |
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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. |
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Keywords: | Average run length HotellingT2 MCUSUM chart MEC charts MEWMA chart Multivariate control charts. |
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