What is it about?
Neural Slicer is a novel neural network-based computational pipeline as a presentation-agnostic slicer for multi-axis 3D printing. Benefiting from Neural Network technology, this advanced slicer can work on models with diverse representations and intricate topology.
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Why is it important?
We introduce a novel neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing. This advanced slicer can work on models with diverse representations and intricate topology. The approach involves employing neural networks to establish a deformation mapping, defining a scalar field in the space surrounding an input model. Isosurfaces are subsequently extracted from this field to generate curved layers for 3D printing. Creating a differentiable pipeline enables us to optimize the mapping through loss functions directly defined on the field gradients as the local printing directions. New loss functions have been introduced to meet the manufacturing objectives of support-free and strength reinforcement. Our new computation pipeline relies less on the initial values of the field and can generate slicing results with significantly improved performance.
Perspectives
I hope this paper highlights the exciting potential of advancements in multi-axis 3D printing. The additional degrees of freedom in this technology offer numerous benefits, such as reduced need for support structures and enhanced mechanical strength. Traditional methods for defining and optimizing curved layers in 3D printing often face challenges like requiring high-quality meshes, indirect optimization objectives, and dependency on initial model orientation. However, our new computational pipeline based on neural networks addresses these issues, optimizing curved layers to meet manufacturing goals of support-free printing and strength reinforcement. Through this approach, we can achieve remarkable results, as demonstrated by the successful fabrication of a complex Bunny Head model using an 8-DOF robotic system. I hope this makes the fascinating world of multi-axis 3D printing more accessible and thought-provoking.
Tao Liu
University of Manchester
Read the Original
This page is a summary of: Neural Slicer for Multi-Axis 3D Printing, ACM Transactions on Graphics, July 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3658212.
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