Writing Parameters for 3D Printing of Dental Prostheses by Optimizing Them Using AI

Abstract We saw that the parameters for a dental printing process have a significant influence on the quality of the dental printed part, such as the layer height, speed of printing, orientation of printing, exposure time, and some parameters related to the used resin. There are many tra ditional ways of choosing the parameters, which are mostly empirical, and consequently lead to errors of dimensions, flaws on surfaces, and high consumption of material; there is also high production time. An Artificial Intelligence (AI) supported optimization scheme is proposed here for the optimal selection of 3D printing parameters to increase the quality and the production efficiency of individual dental prostheses. The proposed approach consists of data acquisition, data collection/preprocessing, feature analysis, training of the machine learning models, and optimization of the parameters to find out correlation between the printing conditions and quality factors such as dimensional accuracy, surface roughness, manufacturing time and con sumption of the materials. Various performance metrics are employed to analyze the different machine learning models and then the best one is utilized to determine the optimum parameter. There are plans to minimize the trial and error methods and to select the parameters on a data driven basis.