Monitoring the coefficient of variation using a double-sampling control chart

Abstract

Coefficient of variation (CV) control charts are widely used to monitor processes in which the mean of process characteristic varies and its standard deviation changes with the mean. However, such charts are generally insensitive to small shifts. In the present paper, a double-sampling (DS) CV chart is proposed to effectively detect the CV shifts. An optimization model is developed to obtain the values of parameters in the DS CV chart. The performance of the DS CV chart is then compared with those of the variable parameter (VP) and the exponentially weighted moving average (EWMA) CV charts. Based on our study, the DS CV chart outperforms the VP CV chart in detecting all shift sizes. In addition, the EWMA CV chart outperforms the DS CV chart only for very small shifts, but the DS CV chart generally has better detection ability than the EWMA CV chart for small, medium and large shifts. A real example of integrated circuit lead electroplating is provided for illustration of applications and this example confirms that the DS CV chart has superior performance when compared with the other two charts.

Keywords:

• Adaptive charts
• Average time to signal
• Coefficient of variation
• Double-sampling chart
• IC lead electroplating