Abstract: A methodology is presented for using neural network (NN) techniques to evaluate input data presented to a computer-controlled processing system. An initial evaluation is used to determine if the input data represents a valid product that is intended to be processed by one or more algorithms within the computer system. If the input data is determined to be invalid, the operation of the algorithm on the product is not initiated (or halted if previously started). Presuming a valid input is ascertained by the NN-based evaluation system, further classification and identifications may be performed to properly match the presented data with a particular system process, as well as select an optimum algorithm for preforming a given task from a set of possible algorithms that may be used for that task.

Abstract: A method for monitoring the process in laser material processing and provides a corresponding method, comprising the steps of taking a real-time image comprising the position and surrounding of the process where material processing occurs by a camera that is arranged in or on a laser material processing head; determining at least one image section in the real-time image and its position on a camera sensor; determining an actual position of the process in the material processing, and a nominal position of the relevant image detail using a projection of programmed path data for controlling the laser material processing head in the section of the real-time image, and the transfer of the at least one image section from the camera to a computer.