The digitalization of production as part of Industry 4.0 permits traditional manufacturing processes such as milling, to be supplemented by IT and software products. As a result, product quality can be improved, production processes designed more quickly and easily and manufacturing costs can be reduced. However, traditional CAM (Computer-aided Manufacturing) systems for programming 3D paths for milling operations still lack a number of functions important for the technological optimization of the milling process in particular.
In the "OptiWear" research project, we collaborated with our partners to develop a software tool which analyzes tool positioning in milling operations conducted using ball-end milling tools and optimizes it so as to ensure that tool wear is distributed over a large area of the cutting edge. This prolongs the service life of the milling tool, enhances product quality and reduces manufacturing costs.
With the help of an artificial neural network, we developed a module which identifies the areas of the tool cutting edge which are likely to sustain particularly high levels of tool wear. We subsequently developed an additional software module which adapts any given 3D tool path to optimize the distribution of wear along the cutting edge.
In the final step, we integrated both software modules into a Product-Lifecycle-Management-System (PLM).