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Combined Cumulative Sum-Exponentially Weighted Moving Average Scheme for Monitoring the Process Mean

D. Tyagi, H. Shonik

Abstract



In most of the industrial applications, if a quality characteristic is showing to less than 1.5 standard deviation shifts in the process parameters, the cumulative-sum (CUSUM) and exponential weighted moving average (EWMA) charts are capable to spot these shifts to bring the process back to a statistical state of in-control. This paper proposes the combination of the abovementioned charts (denoted as Combined CUSUM-EWMA). This chart combines the features of these charts which enhance the capability of detecting small and moderate shifts. The performance of the proposed chart is investigated in terms of the average run length (ARL) values using simulations. The optimal design parameters are also provided to guide researchers in the implementation of the proposed chart. The new chart is also compared to some existing charts from the literature.

Keywords


Combined CUSUM-EWMA scheme, Average runs length, Monte Carlo simulation, Statistical process control.

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