A process monitoring module based on fuzzy logic and pattern recognition

This article presents a plastic injection moulding monitoring module based on knowledge built on-line using feedback from production data. A fuzzy classifier was especially developed for this application. It is based on unsupervised and supervised classification methods. The role of the first one is to identify the functioning modes of the process whereas the role of the second one is to associate the state of the process to one of the identified functioning modes at the moment where a workpiece is injected. Furthermore this diagnosis module integrates an on-line learning method which allows to enrich and upgrade the initial knowledge during production. The results obtained show that the monitoring system is a solution for quality and productivity control having serious economical advantages. For example maintenance tasks can be anticipated and the size of the training set can be considerably reduced. The computing times show that the monitoring system can be used for the purpose of industrial applications without any decrease of production rate.