Auxiliary information-based maximum generally weighted moving average chart for simultaneously monitoring process mean and variability |
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| Authors: | Shin-Li Lu Jen-Hsiang Chen Su-Fen Yang |
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| Affiliation: | 1. Department of Industrial Management and Enterprise Information, Aletheia University, New Taipei City, Taiwan;2. Department of Information Management, Shih Chien University Kaohsiung Campus, Kaohsiung City, Taiwan;3. Department of Statistics, National Chengchi University, Muzha, Taipei, Taiwan |
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| Abstract: | An auxiliary information-based (AIB) maximum exponentially weighted moving average (MaxEWMA) chart has been proposed to simultaneously monitor both increases and decreases in the process mean and/or variability, called the AIB-MaxEWMA chart, which is superior to the existing MaxEWMA chart. In this paper, we propose the AIB maximum generally weighted moving average chart, called the AIB-MaxGWMA chart, to further enhance the sensitivity of the AIB-MaxEWMA chart. Numerical simulation studies indicate that the AIB-MaxGWMA chart is sensitive to small shifts in the process mean and/or variability. The performance of the AIB-MaxGWMA chart based on average run lengths (ARLs) also outperforms than its counterparts including AIB-MaxEWMA, MaxGWMA and MaxEWMA charts. An example is used to illustrate the efficiency of the proposed AIB-MaxGWMA chart in detecting small process shifts. |
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| Keywords: | auxiliary information average run length MaxEWMA chart MaxGWMA chart statistical process control |
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