Objectives: Designing and printing out a 3D model of a mandible, including the teeth with replicated carious lesions, to be fitted into the Dental Patient Simulator. Students assessed the 3D teeth models against the extracted teeth and the standard models, identifying specific restorative dentistry procedures where they might be applied as the teaching aids.
Methods: A 3D tooth model was printed out against a patient’s Cone Beam Computed Tomography scan. The study was attended by 22, 5th-year students, who, having prior removed the caries, filled in the cavities of different classes and trepanned the pulp chamber in the 3D models, subsequently rating them against a questionnaire.
Results: Over 95% of students recommended introducing the 3D models into teaching conservative dentistry with endodontics at the pre-clinical stage to enhance manual skills in cavity preparation and filling. The replication of tissue hardness and anatomical characteristics in the 3D models was rated significantly higher, as compared to the standard ones (p <0.05). Over 90% of students also asserted that working on the 3D models would enhance their pulp chamber trepanation skills, and rated overall replication of the anatomical characteristics significantly higher, in comparison with the standard teeth models (p <0.05).
Conclusions: In pre-clinical education, the 3D teeth models offer a viable alternative, as there is an appreciable potential for different types of teeth to be printed out, in full consideration of their anatomical diversity. Further design refinements in the 3D teeth models are required, though, particularly the ones regarding true-to-life replication of the soft tissues.

Computational intelligence (CI) can adopt/optimize important principles in the workflow of 3D printing. This article aims to examine to what extent the current possibilities for using CI in the development of 3D printing and reverse engineering are being used, and where there are still reserves in this area. Methodology: A literature review is followed by own research on CI-based solutions. Results: Two ANNs solving the most common problems are presented. Conclusions: CI can effectively support 3D printing and reverse engineering especially during the transition to Industry 4.0. Wider implementation of CI solutions can accelerate and integrate the development of innovative technologies based on 3D scanning, 3D printing, and reverse engineering. Analyzing data, gathering experience, and transforming it into knowledge can be done faster and more efficiently, but requires a conscious application and proper targeting.