Study of the influence of the thermal aging on the original shape of the parts obtained by FDM 3D Printing with Z-ULTRAT material

Abstract

Additive manufacturing technology is continuously improving and developing at an accelerated speed, penetrating more and more fields and industries: biomedical, aerospace, clothing, dentistry, automotive, electronics, etc. Discoveries in materials and methods allow printers to manufacture parts of different shapes, sizes and with different accuracies. Ensuring the functionality of the product depends on the accuracy of the component. The precision of the parts obtained by additive manufacturing is influenced by the environmental conditions (increasing or decreasing of temperature). The paper analyzes the influence of printing parameters and the number of cycles of thermal aging on the accuracy of a ring parts obtained by additive manufacturing. In order to establish a relationship between the input parameters and the dimensional accuracy, an artificial neural network was developed and trained. The results showed that the artificial neural network is a suitable tool for optimizing the parameters of additive manufacturing.