Monitoring of Mean Processes with Mixed Moving Average – Modified Exponentially Weighted Moving Average Control Charts
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Abstract
In Statistical Process Control, a control chart is the most effective equipment for monitoring and improving processes. Classic control charts were created in the past and were effective at detecting both small and large changes. However, the mixed control chart has been presented to improve the performance of the traditional control chart. This research introduces a new mixed control chart, MA-MEWMA, which combines the moving average (MA) and the modified exponentially weighted moving average (MEWMA) charts to detect the tiny changes in the procedures both of symmetric and asymmetric distributions. The average run length (ARL) can also be used to measure progress in the MA-MEWMA chart with Shewhart, MA, and MEWMA charts that employ Monte Carlo simulation. The experiments demonstrated that the proposed chart had a greater impact compared to all other control charts with the parameter level ±0.05, ±0.10, ±0.25, ±0.50, ±0.75, ±1.00, ±1.50 through discovering a change in the average of the method in the control where ARL0 = 370. On the other hand, when the parameter level was set to 2.00, ±3.00, ±4.00, the MA control chart performed admirably. An excellent example is data set on viscosity from a batch chemical process. Environmental information data were provided to explain how the suggested chart and MA-MEWMA charts are implemented, demonstrating that the MA-MEWMA chart was more successful than other charts in detecting changes.
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References
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