Search Results - qiang+huang

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2019-054 - A Convolution Modeling and Learning Framework for Predicting Geometric Shape Accuracy of 3D Printed Products

Market Opportunity Achieving high 3D shape accuracy remains a major challenge in additive manufacturing due to complex, layer-by-layer error accumulation and interlayer interactions. Existing physics-based simulations are computationally intensive and difficult to integrate with data-driven learning, while most machine-learning approaches have focused...

2015-225 - Geometric Shape Optimization & Accuracy in 3D Printing

Additive manufacturing Rapid prototyping of: Medical Devices Micro and Nano features Abstract USC researchers have developed a new compensating system and methods that improve dimensional accuracy of the 3D printed objects by at least 75%. Furthermore, the technology eliminates the need for post processing by optimizing the compensation factor(s)...

Published: 12/3/2025 Inventor(s): Qiang Huang
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2024-173 - Automated Accuracy Qualification for 3D Printed Products

3D printing Automatic qualification Geometric Accuracy Abstract USC researchers have developed a new system for automated qualification of 3D-printed products. It consists of two main components: (1) automated non-rigid shape registration and characterization of surface deviation patterns for quality assessment, and (2) automated surface patch...