LPBF In-Situ Characterization Patent Snapshot 2026
LPBF in-situ characterization remains a nascent, highly concentrated field with only 7 patent families on record, dominated by Nikon SLM Solutions AG holding 4 of those families. Activity peaked in 2021 and has eased, leaving substantial room for new entrants to establish defensible positions in adjacent sensing and AI-driven analysis branches.
Nikon SLM Solutions AG leads a highly concentrated, early-stage field
Nikon SLM Solutions AG holds the visible position with 4 patent families, followed by Nanjing University of Aeronautics and Astronautics, Virginia Tech Intellectual Properties Inc., and Beihang University, each with 1 patent family.
The top five filers account for 100% of the ranked applicants visible in this query’ combined total, signaling extreme concentration. The gap between the leader (4 families) and the three challengers (1 family each) is substantial relative to the total corpus size.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | Nikon SLM Solutions AG | 4 | |
| 2 | NANJING UNIV OF AERONAUTICS & ASTRONAUTICS | 1 | |
| 3 | Virginia Tech Intellectual Properties Inc. | 1 | |
| 4 | Beihang University | 1 |
Nikon SLM Solutions AG’s commanding share suggests it has laid the broadest process-monitoring IP foundation in this space; the three academic institutions occupy narrow but distinct technical niches, leaving the commercial tier largely uncontested beyond the leader.
The most recent filings (2024–2025) may not yet be fully published; figures for those years should be treated as provisional minimums. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Activity spiked in 2021 then eased; powder metallurgy and additive manufacturing classes dominate
The annual filing trend reveals a single pronounced burst of activity in 2021 followed by a sharp retreat, while the technology composition chart shows that B22F and B33Y classes account for the overwhelming majority of coverage.
Annual filing trend
Filing volume was negligible through 2020, surged to 5 families in 2021, then fell to isolated single-family filings in 2024 and 2025. The 2024–2025 bars are subject to publication lag and likely undercount actual activity; the 2021 spike remains the defining event in this corpus.
↗ Hover for values · click a bar to ask EurekaTechnology composition
B22F (Powder metallurgy) and B33Y (Additive manufacturing) together cover virtually the entire corpus, reflecting process-centric patent drafting. G06F (Electric digital data processing), G01K (Temperature measurement), G01N (Material analysis and testing), and G06N (AI models) each appear in only one or two families, indicating that sensing and data-analytics dimensions of in-situ characterization remain sparsely covered.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Machine learning thermal management system for add…
A thermal measurement system enables high-resolution sub-surface temperature monitoring during additive manufacturing processes through machine learning demodulation of chirped fiber Bragg grating (C-FBG) sensors. An optical sensing subsystem includes a C-FBG sensor that encodes spatial temperature information in wavelength for high-temperature operation. A… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | 一种具有原位监测功能的LPBF增材制造装置及方法 | 9 |
| 2 | Systems and methods | 9 |
| 3 | Systems and Methods | 6 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Nikon SLM Solutions AG
Nikon SLM Solutions AG holds 4 patent families, the largest position in this corpus by a wide margin. Its technology emphasis spans B22F 10 (Powder metallurgy process), B33Y 50 (Additive manufacturing data and controls), and G06F 30 (Digital data processing), indicating a systems-level approach that integrates process parameters with digital monitoring. No momentum trend data is available for this applicant in the recent period, but its accumulated position gives it first-mover breadth in process-integrated monitoring claims.
families: 4Nanjing University of Aeronautics and Astronautics
Nanjing University of Aeronautics and Astronautics holds 1 patent family, with a technology focus across B22F 10, B22F 12, and B33Y 40, suggesting coverage of process parameters and materials handling in an additive manufacturing context. Its momentum is flagged as a new entrant in the recent period, indicating this institution has only recently entered the space. As an aerospace-affiliated research university, its work likely targets process qualification for structural components.
families: 1Frequently asked questions
The current corpus contains 7 patent families. This is a small dataset reflecting the field’s early and specialized nature; engineers should treat it as a near-exhaustive snapshot of formally published IP rather than a sample.
Nikon SLM Solutions AG holds 4 of the 7 patent families, making it the clear leader. The remaining 3 families are distributed among Nanjing University of Aeronautics and Astronautics, Virginia Tech Intellectual Properties Inc., and Beihang University, each holding 1 family.
Five of the 7 families were filed in 2021, representing a concentrated burst of activity likely driven by simultaneous industrial and academic interest in formalizing process-monitoring approaches for LPBF. No comparable surge has occurred since, and annual volume has eased from that peak.
The United States leads with 3 patent records, followed by China with 2, and Europe (EPO) and WIPO (PCT) with 1 each. Coverage is primarily concentrated in the home jurisdictions of the filing entities.
No co-applicant or jointly assigned families appear in the corpus. All filings are single-entity, which is consistent with both proprietary industrial strategies and independent academic research programs at this early stage.
The branches with the lowest coverage are G01K (Temperature measurement), G01N (Material analysis and testing), and G06N (Computing based on AI models), each represented by only 1 family. These are also areas of high technical relevance to in-situ characterization, suggesting that targeted filings in thermal sensing or ML-based anomaly detection could establish a position with limited blocking risk from existing patents.
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