The additive manufacturing (AM) industry is well positioned to benefit from the increasing incorporation of AI and machine learning (ML) into core processes, and 2026 should provide many opportunities to test its potential. One factor to keep in mind when observing this trajectory is the quality of data that AI adopters in the AM industry have access to.
Not surprisingly, the U.S. Navy is leading the way in this trend. The U.S. military has just awarded information services company Senvol funding for a project aimed at demonstrating that its ML software suite, Senvol ML, can predict the mechanical performance of parts made with wire-based directed energy deposition (DED) AM. According to Senvol, the project:[AM] “Sensor Fusion Technology for Process Monitoring and Control” was already launched last July and will run until July 2027.
The research involves applying the data analysis capabilities of Senvol’s software to information collected by different types of sensors already in use in the AM industry. Sembor hopes to eventually help the Navy implement field surveillance standards across the branch’s ever-expanding AM activities.
In this context, wire DED is a logical place to start for the Navy. That’s because the process powers the type of hybrid system the Navy has been installing on U.S. military ships for several years. If the Navy can use ML software to accelerate the standardization of DED components, it can maximize the effectiveness of systems already in place while also supporting the case for further increasing onboard production capacity.
In a press release about the U.S. Navy’s funding for Senvol’s ML software, Senvol President Zach Simkin said: [AM] It’s important. For a part to be accepted into the supply chain, there must be sufficient trust in how it works. As advances in this field continue to evolve, we believe that by developing a consistent approach to analyzing field monitoring data and developing actionable guidance from there, AM users will be able to more easily meet part acceptance thresholds. ”
Quality control is perhaps the part of the overall AM process where automation can currently have the greatest impact, and few AM users stand to benefit more from such impact than the U.S. Navy. Of course, the Maritime Industrial Base (MIB) faces some of the toughest workforce development challenges of virtually any sector of Western manufacturing, so the Navy will welcome any solution that can reduce workforce needs without sacrificing standards.
And returning to onboard production capacity, this is an area where the need to minimize labor is always paramount. This is because the number of skilled workers available on board an active vessel at any given time is quite limited. Meanwhile, the Navy has also repeatedly demonstrated that onboard production capabilities are a central feature of AM augmentation, just one use case among many.
Additionally, the U.S. military’s international partners, particularly the United Kingdom and Australia, have also expressed interest in developing similar capabilities. This will contribute to making deployable offshore production capabilities a priority, while also opening opportunities for more comprehensive data collection to continuously improve the underlying technology involved.
If the U.S. Navy were able to standardize automated quality control for metal AM parts, not only the Navy but the entire U.S. military would benefit. As we noted earlier this week, as each branch continues to increase its technological maturity, they are all collectively simultaneously increasing the feasibility of cross-branch AM collaboration.
Image provided by: Senvol
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