Extended maximum generally weighted moving average control chart for monitoring process mean and variability

Authors:
Shey-Huei Sheu;Chi-Jui Huang;Tsung-Shin Hsu
Affiliations:
Department of Industrial Management, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., Taipei 106, Taiwan and Department of Statistics and Informatics Science, Provide ...;Department of Industrial Management, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., Taipei 106, Taiwan and Department of International Trade, Jinwen University of S ...;Department of Industrial Management, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., Taipei 106, Taiwan
Venue:
Computers and Industrial Engineering
Year:
2012

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Abstract

In this paper, we propose an extended control chart, called the maximum generally weighted moving average (MaxGWMA) control chart, to simultaneously detect both increases and decreases in the mean and/or variability of a process. Simulations are performed to evaluate the average run length, standard deviation of the run length, and diagnostic abilities of the MaxGWMA and maximum exponentially weighted moving average (MaxEWMA) charts. An extensive comparison reveals that the MaxGWMA control chart is more sensitive than the MaxEWMA control chart.