Page 27 - 3DMP Summer 2022

the new Legor 3DMetalHub in Bressan- vido, Italy, a center of excellence focused on accelerating additive manufacturing (AM) for the luxury industry.
“Our work with Legor aligns perfectly with HP’s vision to disrupt manufacturing norms and accelerate digital manufac- turing and sustainable impact for cus- tomers around the world,” says Didier Deltort, president, HP Personalization & 3D Printing. “The combination of our Metal Jet 3D printing platform with Legor’s materials expertise and customer-centric approach will disrupt the luxury jewelry and fashion industries. This is an exciting milestone as we prepare to make Metal Jet more broadly available to the market later this year.”
HP Inc.: www.hp.com/us-en/printers/ 3d-printers.html
Legor Group SpA: www.legor.com
Blisk via Eight Lasers
and High-Volume Build Box
Velo3D provided an up-close look at a 21-in. blisk printed on its Sapphire XC— the latest member of the Sapphire fami- ly—which features a build chamber meas- uring 600 mm dia. by 550 mm tall, and eight 1-kW lasers. The booth also dis- played a wide array of printed parts, including parts printed with its latest qual- ified metal powders, including Haynes 282, a, wrought, gamma-prime-strength- ened superalloy developed for high-tem- perature structural applications. Velo3D: www.velo3d.com
MES and Workflow Software for AM, Plus AMFG-Sigma Tech. Agreement
Autonomous Man- ufacturing (AMFG) showcased its manu- facturing execution system (MES) and workflow software for AM. The complete end- to-end workflow solu- tion forwarded by AMFG features:
• Ordering portal. Users can streamline
and standardize their order-management processes with a centralized order-man- agement system and integrated commu- nication tools.
• Production scheduling. A full pro- duction suite includes auto-scheduling capability for end-part manufacturing at scale. Visibility is enabled across produc- tion sites to optimize business assets.
• Machine analysis. Use actionable, data-driven insights to maximize ROI and KPI performance via integrated machine analytics and reporting tools.
• Integrations. AMFG offers seamless integration to a user’s existing systems such as ERP and PLM to provide for full process automation.
In related news, Sigma Additive Solu- tions (formerly Sigma Labs, Inc.), provider of quality-assurance software, signed an agreement with AMFG to incorporate in- situ monitoring into MES systems.
The combination reportedly allows users of the technology to automate full production workflow, including key vis- ibility into production monitoring, with full traceability from powder to part; move toward automated part and process qualification; view data in real- time, with the ability to dive deep into analytics feed; capture data to support simulation, material properties predic- tion and final pedigree, and key quality assurance checks to decrease post inspection needs; and provide data con- nectivity and integrity throughout the manufacturing process no matter the equipment environment.
At AMUG, Jacob Brunsberg, president and COO of Sigma Additive Solutions, and
AMUG and RAPID + TCT 3D Sven Hinrichs, head of technology con-
sulting at AMFG, presented details of the joint solution, discussing the criticality of actionable data insights and how to employ data in meaningful ways such as pedigree of part and material properties, final quality assurance, and refining the build process. The ultimate goal, they said, is improving manufacturing OEE and ulti- mately shortening time to qualification for related components.
AMFG: www.amfg.ai
Sigma Additive Solutions: www.sigmaad- ditive.com
Machine-Learning Engine Quickly Dials In on Ideal Aerospace Heat-Exchanger Material
Intellegens, a developer of machine- learning (ML) technology for use in AM simulation and process software, and available to software providers, machine builders and end users, featured its Alchemite ML engine.
Highlighting Alchemite’s capabilities, a case study where Intellegens and its Alchemite ML tool, in collaboration with GKN Aerospace, sought a titanium-alloy composition with the highest thermal conductivity possible without diminishing mechanical properties. The composition would be proved out at the ATI Boeing Accelerator, a 3-mo. accelerator for start- ups seeking to build solutions applicable to the UK aerospace industry. The team attained such a combination, typically a 2-yr. material-design process, within the 3-mo. timeframe.
The team sought a viable titanium alloy of AM of heat exchangers—critical com- ponents in aerospace applications. Not only must the heat exchangers be intri- cately shaped to perform efficiently, but also must be robust enough to serve as structural components. Current materials, the team determined, did not meet the needed combination of high thermal con- ductivity, strength and suitability for AM.
Intellegens used Alchemite deep-learn- ing methods to work closely with GKN Aerospace to analyze all available titanium alloy data. The team considered 20 phys- ical properties across 256 historical alloys
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