PROCESS QUALITY CONTROL: A HYBRID COMBINATION OF NEURAL NETWORKS AND FUZZY LOGIC FOR THE CONSTRUCTION OF CONTROL CHARTS

The new world order has been featuring increasingly by large technological and social changes and the consequent increased competitiveness in most sectors of the economy. In the race for new markets and in an attempt to maintain current positions, it is necessary a efficient and effective management to ensure the continuity of the enterprise in the long term, beyond the fulfilment of its mission. In order to fulfill its mission, companies increasingly need robust tools to monitor and evaluate their productive processes, thus, the statistical process control (CEP) in an enterprise is an important factor especially if we consider the high degree of competitiveness in the most varied fields of activity and current market requirements. In this context, this article was aimed at developing a methodology for constructing control charts based on neuro-fuzzy network waste, i.e. a hybrid model. After adjusting a model AR with intervention, was constructed the control chart. the the weight of spinning.