Artificial intelligence applied to automatic supervision, diagnosis and control in sheet metal stamping processes

Abstract In sheet metal forming processes, any disturbance as a slight change in the mechanical properties of the material can be the reason for the occurrence of defects without changing any other of the process parameters. In order to avoid production breakdowns and to improve the reliability of the stamping process, an integrated automatic control has been designed and tested. This includes a system based on the use of sensors, artificial vision, and neural networks for the diagnosis and the prediction of the process results as well as a second system including the strategy and the devices for the automatic control system, based on fuzzy logic.