Startup based in Iceland Euler offers AI-powered defect detection software for laser powder bed fusion (LPBF) and selective laser sintering (SLS) 3D printing. The company, recently launched in stealth mode, has integrated its process monitoring tool within Merger, AutodeskThe cloud-native 3D CAD/CAM design software.
Available as an Autodesk Fusion app, Euler’s Software as a Service (SaaS) tool leverages existing 3D printer camera data and AI algorithms to perform live, automated 3D printing analysis without expensive monitoring equipment. It can detect common process defects, predict and mitigate 3D printing failures, filter data into actionable insights, and perform system-to-system comparisons for industrial-scale applications.
Using Fusion’s granular and versioned data management, the Euler application connects real-time sensor data from 3D printers to detailed design files, feeding the information back into the design software. This creates an integrated process chain spanning CAD design, preparation and post-processing, supporting rapid iteration for industrial manufacturing applications.
Autodesk integrates Euler AI software
Euler’s Autodesk application identifies and analyzes common powder-based 3D printing defects, such as spatter, overlapping issues, burn marks, smoke, warping, and poor powder distribution. It can anticipate process failures during 3D printing, automatically triggering in-situ mitigation actions to avoid problems with the final part.
The tool also uses artificial intelligence (AI) to translate complex raw data into actionable insights that can be monitored and reported to ensure consistent and reliable production. This allows those without specialized expertise to more effectively oversee the 3D printing process, lowering the barrier of entry to high-quality additive manufacturing. Users can also upload images of powder bed layers for Euler to analyze, increasing accessibility and eliminating the need for expensive equipment.
Additionally, Euler’s system-to-system comparisons allow manufacturers to analyze and standardize the performance of multiple 3D printers, ensuring consistent quality on an industrial scale.
Over the past few months, Autodesk has been beta testing Euler’s offering on a Renishaw RenAM 500Q quad-laser LPBF 3D printer at its Boston technology center. According to Autodesk, the process of directly integrating the tool is simple. The team claimed it “seamlessly” connected the 3D printer to the Euler Cloud platform.
Autodesk machine operators have reportedly discovered that Euler’s automatic AI insights provide “incredible value” for their 3D printing jobs. For example, the tool identified a periodic fluctuation in 3D printing spatter during testing. This revealed a hardware defect in the 3D printer that could have gone unnoticed and resulted in insufficient part quality.
According to Autodesk, Euler’s integration of process and data monitoring “bridges the communication gap between design and manufacturing teams.” This would appear to promote a common understanding of process capabilities and limitations, ensuring that designs are practical and feasible.
live process monitoring for 3D printing
Live monitoring and quality assurance tools are essential to ensure 3D printed parts meet the quality required for demanding applications such as aviation, aerospace and defense. Therefore, Euler joins the growing number of companies offering live defect detection capabilities.
Chicago-based 3D printing quality assurance software developer Phase3D is a key player in this field. The company recently launched Fringe Qualification, a new tool for Fringe, its metal 3D printing in-situ inspection platform. This new offering allows users to certify and control the quality of metal parts during their 3D printing on LPBF systems. It enables simultaneous and automated layer-by-layer inspection across multiple 3D printers to ensure high quality during high-volume production.
Phase3D The Fringe platform uses structural light to measure a height map of each material layer before and after fusion. This creates live visualizations of 3D printing anomalies, allowing engineers to make informed decisions about canceling construction. Earlier this year, the company released its True Layer Thickness Toolkit. This measures, in microns, the quantity of metal powder distributed on the construction platform of a 3D printer. As such, the 3D printing inspection tool allows users to ensure uniform material distribution of each layer, thereby avoiding issues during metal additive manufacturing.
Likewise, the Californian manufacturer of metal 3D printers Bike3D offers its Assure quality assurance and control system. This is compatible with the company’s Sapphire 3D printers and allows live monitoring of the LPBF 3D printing process. Defects are automatically detected as they occur, with quality control and build report summaries generated for each print job. Physics-based multi-sensor detection algorithms are also used to track quality during production, streamlining the part validation process.
Elsewhere, manufacturer of ceramic 3D printers 3DCeram recently introduced CERIAits AI tool to improve ceramic 3D printing. Designed to support the entire additive manufacturing workflow, the platform incorporates CERIA Live, which provides continuous monitoring and adjustments during 3D printing, ensuring an uninterrupted production flow is maintained.
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The featured image shows the Euler AI tool in Autodesk Fusion. Image via Autodesk.