Effect of autocorrelated data on composite panel production monitoring and control: A comparison of SPC techniques

Traditional statistical process control methodology is based on a fundamental assumption that the process data are independent. A comparison is presented of traditional and non-traditional SPC methodology for controlling the effect of autocorrelated processes in production monitoring and control. Results show that, for significantly autocorrelated data, the use of the autoregressive integrated moving average control chart will provide a more consistent technique for detecting assignable or special causes in the continuous production process.