Since it raised its latest funding round, SaaS provider Interspectral didn’t rest on its laurels. The company has been collaborating with different OEMs in the industry and is now involved in two other R&D projects.
As a reminder, the company develops AM Explorer, a visualization software package that allows users to fuse, explore, and analyze simulation, monitoring, and post-build part analysis data in metal AM.
So far, the company has been making its software compatible with LPBF through collaborations with OEMs such as AddUp and EOS. The company expanded its collaboration with the latter OEM by making its software compatible with all EOS M 290 1kW, EOS M 300-4 1kW, and EOS M 400 3D printers.
This partnership seamlessly integrates AM Explorer with EOSCONNECT, providing customers with a fully streamlined data management process. EOS users can access real-time process monitoring and part analysis from a single platform, driving operational efficiency and sustainability. By leveraging the capabilities of AM Explorer to Detect, Visualize, and Analyze, customers benefit from a comprehensive solution that supports every stage of the additive manufacturing process, a press release reads.
In addition to this collaboration with EOS, Interspectral goes further in addressing the challenges with Electron Beam Powder Bed Fusion. To achieve reliable and consistent results, Interspectral will be working with Freemelt, one of the OEMs to watch if you have any interest in E-PBF technology. As part of this MoU, Freemelt’s electron beam AM capabilities will be combined with the real-time visualization and advanced monitoring of Interspectral’s AM Explorer.
More specifically, Interspectral explains that they will focus on deploying AI-enhanced automatic anomaly detection and closed-loop monitoring in Freemelt’s AM systems. Using the backscatter image data, AM Explorer can apply AI models that detect process irregularities in real time, allowing operators to adjust or halt production as needed.
This new method is set to enable an efficient, data-driven approach to quality assurance, helping manufacturers reach new levels of consistency in complex additive manufacturing tasks, the company explains.
R&D projects in the pipeline
Interspectral received funding for the RES2AM and ESCROW projects. RES2AM stands for
“Resilient and Resource-efficient Additive Manufacturing of large/complex added value parts and ESCROW stands for “Enhanced Software Control for Rapid Optimised World Class Metal Additive Manufacturing”.
The RES2AM project seeks to create resilient and resource-efficient additive manufacturing for large, complex metallic components using powder bed fusion with a laser beam (PBF-LB).
Alongside RISE Research Institutes of Sweden, Interspectral will collaborate with Chalmers University of Technology, GKN Aerospace Sweden AB, Nikon SLM Solutions, and Quintus Technologies AB. The RES2AM project adopts a two-stage approach.
In Stage 1, pilot solutions will be developed and validated, focusing on design frameworks, real-time monitoring systems, and advanced thermal management for large-scale AM parts. This stage lays the groundwork by testing solutions in industrial settings.
In Stage 2, a system demonstrator will be implemented to reach industrial readiness, targeting high-quality, resilient AM processes tailored for aerospace and energy sectors. Interspectral’s contribution is focused on developing new AI-powered analytics functionality that empowers industry stakeholders with insights for process stability and efficiency.
In ESCROW, Interspectral joins forces with SIMTEC Soft Sweden AB and Chalmers University of Technology to advance metal additive manufacturing by integrating AI-based real-time monitoring systems.
The project focuses on optimizing the production of high-performance alloys like Alloy 718 and Ti-6-4 through advanced CFD (Computational Fluid Dynamics) simulations, enabling precise process control and minimizing material waste. Interspectral’s role centers on developing sophisticated AI models that predict and adjust critical parameters, ultimately driving production quality and speed.
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