Open Access

ARTICLE

Mixed Moving Average-Cumulative Sum Control Chart for Monitoring Parameter Change

Nongnuch Saengsura, Saowanit Sukparungsee^*, Yupaporn Areepong

Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok, 10800, Thailand

* Corresponding Author: Saowanit Sukparungsee. Email:

Intelligent Automation & Soft Computing 2022, 31(1), 635-647. https://doi.org/10.32604/iasc.2022.019997

Received 05 May 2021; Accepted 18 June 2021; Issue published 03 September 2021

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) via 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.

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