AM-Optimizer: developing an application to detect critical areas and drive printing orientation in additive manufacturing

This work introduces AM-Optimizer, a MATLAB-based application designed to enhance build orientation optimisation in Additive Manufacturing (AM). Unlike existing commercial and open-source solutions, the tool integrates advanced geometric analysis, detection of critical features, and user-defined customisation according to specific printers, materials, and support strategies. The method employs a convex hull algorithm to reduce the orientation search space, while simultaneously evaluating essential indicators such as support volume, warping risk, surface quality, base contact area, and thin-wall stability. A comparative study of support estimation techniques, including projection, voxelisation, and ray tracing, highlights the trade-offs between computational efficiency and accuracy, with ray tracing selected as the preferred compromise. The application has been validated through benchmark models and industrial components, demonstrating competitive performance and improved robustness compared to leading commercial software. In addition, it provides innovative features such as a customisable surface roughness model and detailed management of geometry-sensitive regions. Results confirm the potential of AM-Optimizer as a flexible and transparent tool to improve pre-processing in AM, with future developments aimed at incorporating anisotropic effects and structural optimisation.