Iceland-based startup Euler offers AI-powered defect detection software for laser powder bed fusion (LPBF) and selective laser sintering (SLS) 3D printing. The company, which recently launched from stealth mode, has integrated its process monitoring tool within Fusion, Autodesk’s cloud-native CAD/CAM 3D 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 achieve automated, live 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 make system-to-system comparisons for industrial-scale applications.
Using Fusion’s versioned, granular data management, the Euler App connects real-time sensor data from 3D printers with 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’s AI software
Euler’s Autodesk App identifies and analyses common powder-based 3D printing defects like spatter, recoated issues, burn marks, smoke, warpage, and poor powder distribution. It can anticipate process failures during 3D printing, automatically triggering in-situ mitigation actions to prevent issues 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 supervise 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 removing the need for expensive equipment.
Additionally, Euler’s system-to-system comparisons enable manufacturers to analyze and standardize the performance of multiple 3D printers, ensuring consistent quality at an industrial scale.
Over the past few months, Autodesk has been beta-testing Euler’s offering on a Renishaw RenAM 500Q four-laser LPBF 3D printer at its Boston Technology Center. According to Autodesk, the direct onboarding process of the tool is straightforward. The team claimed it “seamlessly” connected the 3D printer to the Euler Cloud platform.
Autodesk’s Machine operators reportedly found that Euler’s automatic AI insights offer “incredible value” for its 3D print jobs. For instance, the tool identified a periodic fluctuation of 3D printing spatters during testing. This revealed a 3D printer hardware defect which could have gone undetected and resulted in insufficient part quality.
According to Autodesk, Euler’s integration of process monitoring and data “bridges the communication gap between design and manufacturing teams.” It reportedly fosters a shared understanding of process capabilities and limitations, ensuring designs are practical and manufacturable.
live process monitoring for 3D printing
Live monitoring and quality assurance tools are vital for ensuring 3D printed parts meet the required quality for demanding applications like aviation, aerospace and defense. Therefore, Euler adds to a growing number of companies offering live defect-detection capabilities.
Chicago-based 3D printing quality assurance software developer Phase3D is a key player in this space. The firm 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 as they are being 3D printed on LPBF systems. It provides simultaneous and automated layer-by-layer inspection across multiple 3D printers to ensure high quality during high-volume production.
Phase3D Fringe platform uses structural light to measure a height map of each material layer before and after melting. This creates live visualizations of 3D printing anomalies, allowing engineers to make informed decisions about build cancellation. Earlier this year, the company commercialized its True Layer Thickness toolkit. This measures, in microns, the quantity of metal powder distributed across a 3D printer’s build platform. As such, the 3D printing inspection tool allows users to guarantee an even material distribution of each layer, preventing issues during metal additive manufacturing.
Similarly, Californian metal 3D printer manufacturer Velo3D offers its Assure Quality Assurance and Control System. This is compatible with the company’s Sapphire 3D printers and provides 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. Multi-sensor, physics-based detection algorithms are also used to trace quality during production, streamlining the part validation process.
Elsewhere, Ceramics 3D printer manufacturer 3DCeram recently introduced CERIA, its AI tool to enhance ceramic 3D printing. Designed to support the entire additive manufacturing workflow, the platform features CERIA Live, which provides continuous monitoring and adjustments during 3D printing, ensuring an uninterrupted production flow is maintained.
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Featured image shows Euler’s AI tool in Autodesk Fusion. Image via Autodesk.
