Statistical Process Control (SPC) based on the well known Shewhart control charts, is widely used in contemporary manufacturing
industry, including many foundries. However, the classic SPC methods require that the measured quantities, e.g. process or product
parameters, are not auto-correlated, i.e. their current values do not depend on the preceding ones. For the processes which do not obey this
assumption the Special Cause Control (SCC) charts were proposed, utilizing the residual data obtained from the time-series analysis. In the
present paper the results of application of SCC charts to a green sand processing system are presented. The tests, made on real industrial
data collected in a big iron foundry, were aimed at the comparison of occurrences of out-of-control signals detected in the original data
with those appeared in the residual data. It was found that application of the SCC charts reduces numbers of the signals in almost all cases
It is concluded that it can be helpful in avoiding false signals, i.e. resulting from predictable factors.