In the past years. neuro-fiuy systems received an increasing attention
and were used to solve a wide range of problelix in different domains. A
ne~u-o-fiwq S~S~CIII is a hybrid system consisting of an artificial neural
network and a fi~zzy inference system where the learning algorithm of the
artificial neural network is ilsed lo adjust the parameters of the membership
functions associated with the fuzzy inference system. This paper proposes a
neuro-fi~uy classification approach for identifying control chart patterns in
order to uncover the behavior of the production process. The proposed
approach was implemented by building a neuro-f~wy classification system
and b\z using simulated data. Nunierical results showed that the proposcd
approach has a good recognition periormancc of patterns on control charts.