In some manufacturing processes, the variance can change, depending on the process mean. For example, if the output value reflects process yield, an increased mean might naturally lead to an increase in variance. When the variance is a function of the mean, the coefficient of variation (CV) is an appropriate measure for process variability. Since the CV control chart was first introduced by Kang et al (2007), there were some trials to improve the performance of CV control charts depending on the shift size. In this research, we present some CV related control charts and compare the performance of those control charts for better use in the field. The CV control chart shows good sensitivity to large shift in CV. The CV-EWMA control chart(2008), the CV-DEWMA control chart(2011) and the CV-GWMA control chart(2011) were developed to control processes sensitively responding to small shifts of CV. The FIR CV-GWMA control chart is more effective control chart to detecting off-target processes in the stage of set-up or start-up of process.

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. Th

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. The CV control chart is an effective tool to control the mean and variability of process simultaneously. The CV control chart, however, is not sensitive at small shifts in the magnitude of CV. The CV-EWMA(exponentially weighted moving average) control chart which was developed recently is effective in detecting a small shifts of CV. Since the CV-EWMA control chart scheme can be viewed as a weighted average of all past and current CV values, it is very sensitive to small change of mean and variability of the process. In this paper, we propose an FIR(Fast initial response) CV-EWMA control chart to improve the sensitivity of a CV-EWMA scheme at process start-up or out-of-control process. Moreover, we suggest the values of design parameters and show the results of the performance study of FIR CV-EWMA control chart by the use of average run length( ). Also, we compared the performance of FIR CV-EWMA control chart with that of the CV-EWMA control chart and we found that the CV-EWMA control chart gives longer in-control ARL and much shorter out-of-control ARL.

The control chart is widely used statistical process control(SPC) tool that searches for assignable cause of variation and detects any change of process. Generally, ？맴詠？ control chart and ？맴詠？ are most frequently used. When the production run is short and