Optimizing additive manufacturing: Minimizing support structures through constraint-based design

Abstract

Support structures are critical in Additive Manufacturing (AM) but pose challenges due to increased time and material costs for post-processing. This study introduces a novel constraint-based strategy to refine structural parameters while reducing reliance on support structures. By integrating this technique with topology optimization, component angulations are calibrated to align with AM constraints, enabling optimal designs without the need for support. Implementation of this constraint was done using MATLAB, transferring models to Cura software for support identification during printing. To validate the results, stress distribution was scrutinized in the ABAQUS environment, revealing a significant reduction in stress levels due to the proposed methodology, consistent with existing studies on stress reduction phenomena. Moreover, the study demonstrates a substantial decrease in material volume usage, leading to cost savings and promoting sustainable manufacturing practices. This reduction in material usage also enhances structural integrity, minimizing the risk of failure and improving overall performance.