Abstract
ABSTRACTThis study focuses on the development of new one-sided and two one-sided MEWMA charts for monitoring the mean of a multivariate normal process. The one-sided MEWMA chart detects either increases or decreases while the two one-sided MEWMA chart detects both increases and decreases, in the process mean vector. The idea is to first truncate either positive or negative normalized observations to zero, and then apply the one-sided MEWMA charts to transformed data. This helps increase the sensitivities of one-sided and two one-sided MEWMA charts. The Monte Carlo simulation method is used to compute the run length characteristics of the proposed multivariate charts. A detailed run length comparison reveals that the proposed one-sided and two one-sided MEWMA charts are uniformly more sensitive than the existing counterparts when detecting moderate-to-large shifts in the process mean. In addition, with reasonable assumptions, the proposed two one-sided MEWMA chart outperforms the conventional MEWMA chart. Real datasets are considered to explain the implementation of the proposed multivariate charts.
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