Nongnuch Saengsura, Saowanit Sukparungsee^*, Yupaporn Areepong

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 635-647, 2022, DOI:10.32604/iasc.2022.019997

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… More >

Ambreen Shafqat^1,2, Muhammad Aslam^3,*, Muhammad Saleem⁴, Zameer Abbas⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 373-391, 2021, DOI:10.32604/cmes.2021.016772

Abstract The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average (NEWMA) chart. In this study, two control charts are designed under the uncertain environment or neutrosophic statistical interval system, when all observations are undermined, imprecise or fuzzy. These are termed neutrosophic double and triple exponentially weighted moving average (NDEWMA and NTEWMA) control charts. For the proficiency of the proposed chart, Monte Carlo simulations are used to calculate the run-length characteristics (such as average run length (ARL), standard deviation of the run length (SDRL), percentiles (P₂₅, P₅₀, P₇₅))… More >