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Maximum Chi-Square Generally Weighted Moving Average Control Chart for Monitoring Process Mean and Variability
Authors:Shey-Huei Sheu  Chi-Jui Huang  Tsung-Shin Hsu
Affiliation:1. Department of Statistics and Informatics Science , Providence University , Taichung , Taiwan;2. Department of Industrial Management , National Taiwan University of Science and Technology , Taipei , Taiwan shsheu@pu.edu.tw;4. Department of International Trade , Jinwen University of Science and Technology , New Taipei City , Taiwan;5. Department of Industrial Management , National Taiwan University of Science and Technology , Taipei , Taiwan
Abstract:In this article, we propose a new control chart called the maximum chi-square generally weighted moving average (MCSGWMA) control chart. This control chart can effectively combine two generally weighted moving average (GWMA) control charts into a single one and can detect both increases as well as decreases in the process mean and/or variability simultaneously. The average run length (ARL) characteristics of the MCSGWMA and maximum exponentially weighted moving average (MaxEWMA) charts are evaluated by performing computer simulations. The comparison of the ARLs shows that the MCSGWMA control chart performs better than the MaxEWMA control chart.
Keywords:ARL  GWMA control chart  MaxEWMA control chart  MCSGWMA control chart  Simulation
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