Identifying defects in 3D printed items is one of the ongoing challenges to be overcome if the technology is to be more widely adopted. This development is very promising.
Small defects in 3D printed metal parts limit their performance and are roadblocks preventing the technology from being more widely used. Researchers at Argonne National Laboratory theorized that the defects stemmed from small voids in the cooled printed metal. The voids (porosity) can make printed components prone to cracking and other failures.
To check their theory, they used a 3D printer with an IR camera, a common option, to film the printing process from above. It monitored and recorded temperature data during the build process. At the same time, a high-powered X-ray from the Advanced Photon Source at Argonne took a side view of the build it was underway. The goal was to use the X-rays to see voids form and correlate that with what was going on thermally on the surface where new metal was being deposited.
Ending the struggle to produce end-use 3D-printed aircraft products.
In the aerospace industry, everything needs to be done in compliance with a standardized, documented specification, or procedure. Material specifications cover all aspects of raw materials production (and testing) from paints and sealers to billets and forgings. Certifications or “certs” travel with these materials throughout the manufacturing lifecycle testifying that they are what they should be. Process specifications exist for every manufacturing process used to produce something. From soldering to caulking and from rivet installation to lockwire application everything has a well-documented way of doing it correctly.
And for good reason: Failure at 30,000 feet has dire consequences so everything must be done in a predictable and (statistically significant) safe manner. Most people have heard of AS9100 standards which are based on ISO 9001 requirements. AS9100 takes ISO 9001 even further with additional quality system requirements in order to satisfy DOD, NASA, and FAA quality requirements.
As a result, Sigma Labs will enable in-process quality monitoring for additive manufacturing systems at the MTC’s National Centre for Additive Manufacturing through its software; the company will also participate in MTC’s member-sponsored programs with a focus on qualification and certification of the additive manufacturing process.
“With Europe at the forefront of many innovative and major developments in the metal AM industry, we believe this agreement, our second major research alliance with a European center of excellence, holds great promise for us and the future of AM,” said John Rice, CEO of Sigma Labs.
Neural networks and advanced algorithms use real-time video to analyze build quality and advise on how to improve it.
For years, engineers at Lawrence Livermore National Laboratory have used sensors and imaging techniques to analyze the physics and processes behind metal 3D printing in order to build high-quality metal parts the first time, every time. Now, they are leveraging machine learning to process data obtained during 3D builds in real time, detecting within milliseconds whether a build will be high quality. More precisely, they are developing convolutional neural networks (CNNs), a type of algorithm commonly used to process images and videos, to predict whether a part will be good by looking at as little as 10 milliseconds of video.
DNV GL is a quality assurance and risk management company that helps businesses obtain safety and sustainability through classification, certification, and other services to a wide range of industries, including the maritime, oil and gas, power, and renewables industries. The company has been frequently involved with 3D printing lately, particularly in the maritime arena, and now it has published the first classification guideline for the use of additive manufacturing in the maritime and oil and gas industries. The classification guideline is intended to ensure that parts produced via 3D printing, and the materials from which they are printed, have the same level of quality assurance as those produced by traditional means.