machine learning

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AI Driven Bioprinting Speeds up Tissue Engineering

Researchers at Rice University used artificial intelligence (AI) to speed up the development of 3D printed bioscaffolds that help injuries heal. A team led by computer scientist Lydia Kavraki of…

Self-Learning Robot Autonomously Moves Molecules, Setting Stage for Molecular 3D Printing

If you know even just a little bit about science, you probably already know that molecules are often referred to as “the building blocks of life.” Made of a group…

IP Security: Reverse Engineering to Test Vulnerability in 3D Printer Toolpaths

We hear a lot about engineering hardware and software and other accompanying technologies for 3D printing, so the idea of going in reverse may raise an eyebrow or two; however,…

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MX3D Uses Robot Arm to Make 3D Printed Robot Arm, Installs It on Robot

MX3D’s steel bridges are an inspiring sight to see, but, even if bridges are what the Dutch firm is known for, they are not the only thing the firm is…

US Air Force Uses Senvol ML Software to Qualify Multi-Laser 3D Printing Systems

Over the last few years, Senvol, which provides data to help companies implement additive manufacturing into their workflows, has put a good deal of focus into military applications. Back in…

Machine Learning & Geopolymers: 3D Printing for Construction

Ali Bagheri and Christian Cremona explore complexities in digital fabrication, sharing their findings in the recently published ‘Formulation of mix design for 3D printing of geopolymers: A machine learning approach.’…

Peter Naftaliev Lecture Series on Learning on How to Go from 2D to 3D with Machine Learning

Peter Naftaliev is an artificial intelligence (AI) researcher and consultant who is working in making 2D into 3D. Besides work for his company Abelians, he also publishes breakthrough research at…

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…

Machine Learning & Bioprinting: Researchers Improve Drop-on-Demand (DOD) Methods

As bioprinting continues to pick up steam in labs around the world, researchers still study the process intensively to build on current techniques and innovation. In ‘Multi-Objective Optimization Design through…

3D Printing News Briefs: February 8, 2019

We made it to the weekend! To celebrate, check out our 3D Printing News Briefs today, which covers business, research, and a few other topics as well. PostProcess has signed…

AMFG Receives Funding from Innovate UK to Improve AI and Machine Learning Software Solutions for 3D Printing

London-based company AMFG, formerly known as RP Platform until this summer, creates workflow automation software for industrial 3D printing so that companies, such as Bowman International and Makelab, can streamline and manage…

Paul Benning Chief Technologist 3D Printing at HP Predicts 3D Printing Developments in 2019

Paul Benning is the 3D Print and Microfluidics Chief Technologist at HP. Before that he was an HP Fellow and the Chief Technologist of their imaging and printing division. He’s…

Defense Logistics Agency Awards Senvol Grant to Predict Mechanical Performance of 3D Printed Parts

New York-based Senvol, which provides data to companies to help them adopt 3D printing into their workflows, has been pretty focused on military applications as of late. The company joined the National Armaments…

Senvol Receives Grant for Applying Data Analytics to 3D Printing Data

Senvol provides data to other companies in order to help them implement 3D printing into their workflows. Its massive searchable network, called the Senvol Database, is dedicated to searching 3D printers and materials…

Researchers Develop Machine Learning Method to Monitor 3D Printing Process for Defects

All sorts of issues can occur when a 3D printed part has a defect, and researchers around the world continue trying to find new ways to detect these defects before…

3D Systems Looks to Increase 3D Printer Efficiency with Aquant’s AI Platform

For the last two years, 3D printing industry giant 3D Systems has been looking into product launches in hardware, materials, and workflow, in order to create more opportunities for additional…