@Article{iasc.2022.019997,
AUTHOR = {Nongnuch Saengsura, Saowanit Sukparungsee, Yupaporn Areepong},
TITLE = {Mixed Moving Average-Cumulative Sum Control Chart for Monitoring Parameter Change},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {31},
YEAR = {2022},
NUMBER = {1},
PAGES = {635--647},
URL = {http://www.techscience.com/iasc/v31n1/44321},
ISSN = {2326-005X},
ABSTRACT = {In this research, we propose the new mixed control chart called the mixed Moving Average-Cumulative Sum (MA-CUSUM) control chart used for monitoring parameter changes in asymmetrical and symmetrical processes. Its efficiency was compared with that of the Shewhart, Cumulative Sum (CUSUM), Moving Average (MA), mixed Cumulative Sum-Moving Average (CUSUM-MA) and mixed Moving Average-Cumulative Sum (MA-CUSUM) control charts by using their average run lengths (ARLs), the standard deviation of the run length (SDRL), and median run length (MRL) <i>via</i> the Monte Carlo simulation (MC). The simulation results show that the MA-CUSUM control chart was more efficient than the other control charts for small-to-moderate parameter changes for all distributions tested. To compare their applicability to real-world situations, the control charts were applied to data for the River Nile flow from 1871–1930 and mine explosions in the UK from 1875–1951. It was found that the MA-CUSUM control chart could more quickly detect parameter changes than the other control charts.},
DOI = {10.32604/iasc.2022.019997}
}