Hybrid artificial intelligence system in constraint based scheduling of integrated manufacturing ERP systems

The paper presents hybrid artificial intelligence system in constraint based scheduling of integrated manufacturing ERP systems. The system includes neural networks. The models were created by use simple neural networks (linear network - L, multi-layer network with error backpropagation - MLP and Radial Basis Function network - RBF) and hybrid neural networks in the form of: L - MLP network, L - RBF network, MLP-RBF network and L - MLP - RBF network. Neural networks as classification models were used to selection of tool for manufacturing operation. Next models as forecasting models were used to forecasting of tool use in different time intervals for manufacturing operation. These models were used at the stage of constraint bases scheduling and preventing standstill due to lack of tools, and special tools in particular. The created models were tested on real data from an enterprise.