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.
PaperID: p 108-119
Author's Name: Maria Emilia Camargo, Ivonne Maria Gassen, Marcia Adriana de Oliveira Cerezer and Suzana Leitão Russo
Volume: Volume 2
Issues: Volume 2
Keywords: Control charts, neural networks, fuzzy logic.