Estrategia para la compensación de errores dimensionales en piezas fabricadas a través de impresión 3D.

Abstract

The technological tools available on the market to facilitate parts production in industries are becoming more and more reliable. The digital race demands that these tools that aid manufacturing structure the information and make it available to the systems involved in the product life cycle. Measurement systems must return reliable values in characteristics such as accuracy, precision, durability, among other factors, to determine errors and problems that arose before and during manufacturing. Methods are required that allow solving and correcting every possible problem in production and promoting sustainable manufacturing. This work proposes implementing a methodology to inspect manufactured parts and digitize the data to compliant with production standards. The measurement allows the deviation to be verified by modifying the dimensional tolerances that affect the part’s functionality. The procedure is carried out through a point cloud that allows determining the geometric and dimensional values of the manufactured part and comparing it with the projected parameters to calculate the deviation. The procedure generates a database that can be translated into useful information to train an artificial neural network, or a genetic algorithm can obtain geometric and dimensional tolerance calculations