LPBF Machine Condition Monitoring Patent Snapshot
The patent corpus for LPBF machine condition monitoring is nascent and highly fragmented, with 9 patent families spread across more than a dozen distinct filers. Nikon SLM Solutions AG holds the only multi-family position, and annual activity has plateaued near its modest peak, leaving substantial room for differentiated entry.
Nikon SLM Solutions leads a fragmented, early-stage field
Nikon SLM Solutions AG is the sole applicant with more than one patent record, placing it at the top of the ranking in a corpus where the vast majority of filers hold a single record each.
The top five filers account for 26% of the ranked applicants visible in this query’ combined total, signalling a low-concentration field with no visible incumbent capable of blocking broad entry. There is no meaningful tier gap between second and lower-ranked applicants.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Nikon SLM Solutions AG | 2 | |
| 2 | K Tamilselvan | 1 | |
| 3 | NANJING UNIV OF AERONAUTICS & ASTRONAUTICS | 1 | |
| 4 | Shanghai Leimou Technology Co., Ltd. | 1 | |
| 5 | K Sivaramakrishnan | 1 | |
| 6 | Shafae Mohammed Saeed Abuelmakarm | 1 | |
| 7 | U Sujan | 1 | |
| 8 | V Skandhakumar | 1 | |
| 9 | S Senthil Kumar | 1 | |
| 10 | K Rajasuresh | 1 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 11 | R Elakkiyadasan | 1 | |
| 12 | A Sam Immanuel | 1 | |
| 13 | M Shek Mubarak | 1 | |
| 14 | Andrew Ezekiel Wessman | 1 | |
| 15 | K Venkatesan | 1 | |
| 16 | Virginia Tech Intellectual Properties Inc | 1 | |
| 17 | R Saron | 1 | |
| 18 | P Vijaykannan | 1 | |
| 19 | Beihang University | 1 | |
| 20 | N Sathishkumar | 1 |
Nikon SLM Solutions AG’s position as a machine OEM filing across both powder-metallurgy process classes and digital-data-processing subclasses suggests vertical integration of hardware and monitoring software, but the absolute volume is too small to confirm a sustained strategic moat.
The most recent 18–24 months of filings are subject to publication lag and likely under-represent current activity; the apparent plateau should be interpreted cautiously. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Activity plateaued after 2021; powder-metallurgy and additive-manufacturing classes dominate
The annual filing trend and the IPC class breakdown together show a field that activated in 2021, has held a low steady state, and remains anchored in core process classes with sensor and AI sub-classes sparsely represented.
Annual filing trend
Filings first appeared in 2021, reached a small cluster, then registered further activity in 2024–2025. The zero values for 2022–2023 and 2026 should be read with caution given publication lag; the lifecycle evidence characterises the field as plateaued near its peak rather than declining.
↗ Hover for values · click a bar to ask EurekaTechnology composition
B22F (Powder metallurgy) and B33Y (Additive manufacturing) are visible in the IPC mix, reflecting the process-centric framing of most filings. G01N (Material analysis and testing), G06F (Electric digital data processing), G06N (AI models), and G01K (Temperature measurement) each appear in only one or two records, confirming that sensing, data-processing, and AI branches are currently under-served.
↗ 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.
Method for Predictive Control of Laser Powder Bed …
A method for adaptive control of laser power during selective laser melting may include the steps of generating a toolpath for a part, calculating a mechanistic feature of the part, inputting a laser scanning speed and the calculated mechanistic feature of the part into a machine learning model, predicting meltpool temperature variations along the toolpath… (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 | 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 2 patent records, the highest count in the corpus, with technology emphasis spanning B22F 10 and B22F 12 (Powder metallurgy process and apparatus) and G06F 30 (Electric digital data processing). This cross-class coverage suggests an integrated approach combining machine hardware with computational monitoring. No momentum trend data was recorded for this applicant, meaning its filing trajectory within the observation window does not show a new acceleration.
patent records: 2Nanjing University of Aeronautics & Astronautics
Nanjing University of Aeronautics and Astronautics holds 1 patent record and is flagged as a new entrant in the applicant momentum data. Its technology focus covers B22F 10, B22F 12, and B33Y 40 (Additive manufacturing post-processing), indicating an interest in the full process chain. As an institution with established aerospace manufacturing research, its entry into LPBF monitoring IP may precede broader academic-industry collaboration activity.
patent records: 1Frequently asked questions
The current corpus contains 9 patent families. This is a nascent and narrow niche; the small absolute count means individual filings carry significant weight and the field remains highly accessible to new entrants.
Nikon SLM Solutions AG is the top-ranked applicant with 2 patent records, the only filer to hold more than one record. All other identified applicants hold 1 patent record each.
B22F (Powder metallurgy) covers all 9 patent records and B33Y (Additive manufacturing) covers 7, making them the visible classes. G01N (Material analysis and testing) and G06F (Electric digital data processing) each appear in 2 records, while G01K, G06N, G06T, and B29C each appear in 1.
The United States leads with 4 patent records, followed by China with 3, India with 1, and WIPO PCT with 1. International coverage via PCT is thin, which may represent an opportunity for applicants seeking broad geographic protection.
The evidence characterises LPBF machine condition monitoring as at a Maturity stage, with annual filings plateaued near their peak. Despite this label, the absolute volume remains very small, and the foundational IP landscape is far from saturated.
One collaboration is documented: Andrew Ezekiel Wessman co-filed with the Arizona Board of Regents on behalf of the University of Arizona. Multiple academic institutions — including Nanjing University of Aeronautics and Astronautics, Beihang University, Northwestern University, and Virginia Tech Intellectual Properties Inc — are filing independently, suggesting that structured academic-industry partnerships in this niche are still rare.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
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