Univ. of Southern California: Researchers Make 3D Printing Smarter for All Users

Researchers from the Daniel J. Epstein Department of Industrial and Systems Engineering, led by Qiang Huang, Ph.D., have recently been granted $1.4M funding support, including a recent $350,000 NSF grant. Assisted…

HEXWAVE: Waving Goodbye to “Threat” of 3D Printed Guns?

3D printed guns remain a controversy, despite the comparatively little threat they pose compared to mass-produced weaponry (that isn’t to say that there are no dangers to the technology). As…

Stratasys & DSM Venturing Lead $12 Million Round in Support of Inkbit  

Stratasys and DSM Venturing (venture capital arm of Royal DSM) lead the way in yet more financing for startups, acting as the major sources of funding support of $12 million total,…

Enhancing FDM 3D Printed Parts with New Algorithms

In ‘Build Orientation Optimization for Strength Enhancement of FDM Parts Using Machine Learning based Algorithm,’ authors Manoj Malviya and K.A. Desai explore a new method for controlling anisotropy and thus,…

3D Printing Service Bureaus: Refining Pricing Systems with More Progressive Cost Analytics

Deepak Pahwa and Binil Starly provide cost analytics for 3D printing services bureaus in their recently published paper, ‘Network Based Pricing for 3D Printing Services in Two-Sided Manufacturing-as-a-Service Marketplace.’ Taking…

Markforged Demonstrating its Blacksmith AI

Accuracy in Additive Manufacturing (AM), from the CAD design to the printing process, is not always easy to deliver. Companies are working hard at trying to ensure consistency and repeatability…

China: Applying Neural-Network Machine Learning to Additive Manufacturing Processes

In ‘Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives,’ authors Xinbo Qi, Guofeng Chen, Yong Li, Xuan Cheng, and Changpeng Li investigate how machine learning…

Alchemite Machine Learning Engine Used to Design New Alloy for Direct Laser Deposition 3D Printing

Artificial intelligence (AI) company Intellegens, which is a spin-off from the University of Cambridge, created a unique toolset that can train deep neural networks from noisy or sparse data. The machine…

Using Semi-Supervised Machine Learning in Laser Powder-bed Fusion Fault Detection

Researchers from the University of Liverpool outline their findings regarding the automatic detection of faults in additive manufacturing products in a recently published paper, ‘Automatic fault detection for laser powder-bed…

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