University of Pittsburgh engineers have developed an algorithm designed to optimize support structures in laser powder bed fusion additive manufacturing. This innovative approach aims to significantly reduce residual stress and deformation in manufactured parts by enhancing the design of support structures through intelligent computational algorithms.
Description
The new support structure optimization algorithm provides a major advancement in additive manufacturing technology by focusing on minimizing residual deformation and facilitating ease of support removal. This is achieved by designing support structures that balance strength and ease of removal through chemical/electrochemical etching. The optimized support structures can reduce residual stress and enhance powder removal, offering substantial improvements over traditional support design strategies.
Applications
- Aerospace and Automotive Industries
- Medical Devices
- Industrial Manufacturing
Advantages
The primary benefit is the reduction of manufacturing costs by minimizing the volume of support structures while ensuring they are easy to remove using chemical or electrochemical etching. This approach also allows for the fabrication of parts that were previously difficult or impossible to manufacture using conventional methods, as it accommodates the needs of both mechanical stability during printing and efficient post-processing. The hybrid lattice structure used in the support design is unique in its ability to withstand the high stresses of metal AM processes while also being optimized for dissolvable support removal. This results in improved part quality, reduced production time, and cost savings, making it an attractive solution for industries requiring high-precision metal components.
Invention Readiness
Finite element simulations validated the algorithm's effectiveness, showing up to a 40% reduction in residual deformation compared to conventional strategies. Proof of concept testing on metal parts using laser powder bed fusion showed significant reductions in residual stress and deformation. Various geometries tested with different support designs confirmed the optimized pattern's superior performance. Residual stress measurements using X-ray diffraction and high-precision 3D scanning supported these findings. The algorithm is at the prototype stage, with completed in vitro proof of concept, and future steps include further testing and validation.
IP Status
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