Intelligent Detection of Geometric Errors in Milling Processes

Dimensional tolerances and surface finish are two fundamental elements that must be carefully controlled during the manufacturing of industrial parts. The study of signals obtained from the machining of parts is useful for the control and monitoring of the process. For this reason, correlating these signals and information on the surface quality of the machined part is essential for the early detection of breaches in the quality levels of the parts. Therefore, the objective of this work is to develop an intelligent strategy capable of estimating the artificial geometric error induced in the part during machining. In order train these strategies, the experimental signals of the process and the three-dimensional scanned geometry of the machined part are used as starting data. This development aims to reduce both defects and production time, increasing the efficiency, productive capacity and environmental sustainability of the industrial process.