Multi-objective optimization for enhanced digitalization in direct 3D printing: an application in dentistry.

objectiveThis study aims to mitigate variances between scanned STL files and original models to limit divergence from reference files and ensure dental appliance manufacture accuracy. The study also attempts to optimize STL mesh triangles to improve digital model quality and detail while balancing memory usage and accuracy. It also examines how external factors like scan distance (SD), scan angle (SA), and light intensity (LI) affect STL file quality and accuracy. The research also optimizes scanning parameters utilizing a multi-objective optimization approach to find the optimal combination of SD, SA, and LI to minimize deviation, triangles and time consumed altogether, improving 3D printing efficiency and accuracy. MATERIALS AND

methodsAn optimal combination for experiments is developed using response surface methodology with varying ranges of SD, SA, and LI to generate 20 runs. The study used a denture to develop scanned STL files at these different parametric combinations, evaluating the resulting output deviation, number of triangles and time. Predictive model for deviation is then created and processed using the multi-objective Non- dominated sorting Genetic algorithm II to minimize deviation, triangles and time consumed.

resultsThe results of the study demonstrate the significance of the developed model for deviation only using regression and for all three using ANN. As indicated by ANOVA analysis revealing a p-value less than 0.05, affirming regression model statistical significance. Optimization results states SD of 5.3621 inch, SA 82.1746 degree and LI 15.2456 W/m

conclusionsThe accuracy of file is heavily contingent upon the quality of the STL mesh derived from the process. This mesh typically requires preprocessing due to its unorganized structure, which not only compromises accuracy but also incurs additional time due to inefficiencies in mesh structure. Furthermore, while increasing the number of triangles in the mesh provides higher resolution and accuracy, it also demands greater memory allocation. Thus, achieving a balance between memory usage and the number of triangles is imperative. CLINICAL RELEVANCE: Direct 3D printing streamlines dental fabrication by using patient-specific scanned STL files to create dental appliances. This method saves time, improves efficiency, and eliminates multi-stage cast generation. The scanned STL files, originally produced from point cloud data processed by surface reconstruction, must be accurate. Unorganized STL meshes require preprocessing, which reduces accuracy and increases time. Adding mesh triangles improves resolution and accuracy, but it requires more memory. Thus, memory utilization and triangle count must be balanced with time consumed. Fixing these issues provides high-quality, accurate dental restorations, increasing patient outcomes and digital dentistry. Additionally, it provides practioners to develop freedom constraints devices with more effectiveness.