Exponentially weighted moving average and industrial applications to feedback adjustment and control

In his book ‘Out of the Crisis’ the late Dr Edwards Deming asserted that ‘if anyone adjusts a stable process to try to compensate for a result that is undesirable, or for a result that is extra good, the output will be worse than if he had left the process alone’. His famous funnel experiments supported this assertion. The development of the control chart by Dr Walter Shewhart stemmed from an approch made to him by the management of a Western Electric Company plant because of their awareness that adjustments made to processes often made matters worse. However, many industrial processes are such that the mean values of product quality characteristics shift and drift over time so that, instead of sequences of independent observations to which Deming's assertion applies, process owners are faced with autocorrelated data. The truth of Dr Deming's assertion is demonstrated, both theoretically and via computer simulation. The use of the Exponentially Weighted Moving Average (EWMA) for process monitoring is demonstrated and, for situations where process data exhibit autocorrelation, its use for feedback adjustment is discussed and demonstrated. Finally, successful applications of process improvements using EWMA-based control algorithms is discussed.