DED Melt-Pool Sensors Patent Snapshot 2026
The directed-energy deposition melt-pool sensor patent space is nascent and tightly held, with 7 patent families on record and Rolls-Royce Corp alone accounting for the largest single share. Aerospace OEMs and one university form the entire identifiable applicant base, signalling that the technology is still in early-stage proprietary development rather than broad industry diffusion.
Rolls-Royce leads a highly concentrated, aerospace-dominated field
Rolls-Royce Corp holds the top position in the applicant ranking, followed by GE Avio S.r.l. and Northwestern University each in second place, together accounting for the majority of activity among the largest filers.
The top five filers collectively represent 69% of the combined total of the ranked applicants visible in this query — an unusually high concentration for a technology in active development, indicating that a small cluster of aerospace-adjacent organisations has defined the field so far.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Rolls-Royce Corp | 3 | |
| 2 | GE Avio S.r.l. | 2 | |
| 3 | Northwestern University | 2 | |
| 4 | Rolls-Royce PLC | 1 | |
| 5 | MR AJAY M | 1 | |
| 6 | DR N KARTHI | 1 | |
| 7 | MR DEEPAK S R | 1 | |
| 8 | MR DHANUSHH M S | 1 | |
| 9 | NOVA University Lisbon | 1 |
The dominance of Rolls-Royce Corp and GE Avio S.r.l. reflects the direct relevance of melt-pool sensing to high-value turbine component manufacturing, where process control quality has immediate commercial consequences. Northwestern University’s co-presence suggests that foundational sensor-and-control research is still being conducted in academic settings and has not yet been fully absorbed by industry.
Records from the most recent 18–24 months are likely under-counted due to patent publication lag, so the apparent absence of 2025–2026 filings should not be read as a slowdown. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Sporadic early filings, with activity clustering in 2018 and 2023–2024
The annual filing trend and technology composition charts together reveal a field that has produced filings in two distinct pulses, anchored primarily in additive manufacturing and powder metallurgy classifications.
Annual filing trend
Filings first appeared in 2018 with two records, went silent through 2022, then recovered to two records in 2023 and three in 2024. The gap years likely reflect the narrow applicant base rather than declining interest; the 2023–2024 uptick coincides with all tracked applicants entering as new entrants. The 2025–2026 zeros are publication-lag artefacts and should not be interpreted as inactivity.
↗ Hover for values · click a bar to ask EurekaTechnology composition
B33Y (additive manufacturing) is the visible classification, followed by B22F (powder metallurgy) and B23K (welding, soldering and brazing). Lower-count branches — G05B (control and regulating systems), F01D (turbines), and G06N (AI-based computing) — represent adjacent or application-layer coverage that remains sparsely populated relative to the process-hardware core.
↗ 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.
Neuro-fuzzy logic for controlling material additio…
A method may include controlling, by a computing device, a directed energy deposition material addition (DED MA) technique based at least in part on a thermal model. The thermal model may define a plurality of default operating parameters for the DED MA technique. The method also may include detecting, by at least one sensor, at least one parameter related… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Systems and methods for global thermal control of … | 28 |
| 2 | Neuro-fuzzy logic for controlling material additio… | 5 |
| 3 | Neuro-fuzzy logic for controlling material additio… | 5 |
| 4 | Additive manufacturing systems and methods for com… | 3 |
| 5 | Wire and arc additive manufacturing (WAAM) system … | 2 |
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.
Rolls-Royce Corp
Rolls-Royce Corp holds 3 patent records — the largest single count in this corpus — concentrated in B33Y (additive manufacturing) and B22F (powder metallurgy) classifications. The applicant momentum trend is marked as a new entrant, indicating all of its filing activity falls within the recent tracking window. The intra-group co-filing with Rolls-Royce PLC (1 record) suggests coordinated IP strategy across the group’s entities.
patent records: 3GE Avio S.r.l.
GE Avio S.r.l. holds 2 patent records, focused on B29C (shaping of plastics), B33Y additive manufacturing processes, and B33Y apparatus classifications. Its momentum trend is also new entrant, placing its filings entirely within the recent period. GE Avio’s focus on process and apparatus classes, rather than powder metallurgy, suggests a distinct technical approach to melt-pool monitoring from Rolls-Royce Corp.
patent records: 2Frequently asked questions
The corpus contains 7 patent families in scope. This is a very small corpus, consistent with a nascent technology where foundational IP is only beginning to be staked out by a handful of aerospace-oriented organisations.
Rolls-Royce Corp holds the top position with 3 patent records, followed by GE Avio S.r.l. and Northwestern University each with 2 patent records. The top five filers account for 69% of the combined total among the ranked applicants visible in this query, indicating a highly concentrated competitive position.
The United States accounts for 6 of the patent records in this corpus. Single records appear in Canada and India, and one PCT application was filed through WIPO. European, Japanese, and Chinese jurisdiction coverage is absent from the current evidence.
B33Y (additive manufacturing / 3D printing) is the visible classification, followed by B22F (powder metallurgy) and B23K (welding, soldering and brazing). Lower-density classes include G05B (control and regulating systems), F01D (turbines), and G06N (AI-based computing).
The only documented collaboration is between Rolls-Royce Corp and Rolls-Royce PLC, which reflects intra-group coordination. No cross-sector or OEM-academic co-filings appear in the current corpus, suggesting the technology is being developed in competitive silos rather than through open consortia.
The G05B (control and regulating systems) branch holds only 2 patent records, and G06N (AI-based computing) holds only 1. Both represent technically relevant adjacent layers — closed-loop feedback control and machine-learning-based melt-pool analysis — that are sparsely covered relative to the process-hardware core.
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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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