DED Thermal & Melt-Pool Modeling Patent Snapshot 2026
The DED thermal and melt-pool modeling patent space is small and highly concentrated, with BAE Systems PLC holding the dominant position among a field of 13 patent families. Activity peaked in 2021 and has since eased, leaving adjacent technical branches — particularly welding-process simulation and computational chemistry — with minimal coverage and potential entry room.
BAE Systems leads a concentrated, single-tier field
BAE Systems PLC is the clear leader, ranking first among all applicants and commanding a disproportionate share of filings. Northwestern University ranks second, followed by a cluster of single-record filers including the University of Science and Technology Beijing, Hamilton Sundstrand Corp, and Goodrich Corp.
The top five filers account for 69% of the combined total across the ranked applicants visible in this query — an unusually high concentration for an emerging manufacturing-process modeling topic. There is no meaningful second tier; beyond BAE Systems and Northwestern University, all remaining applicants hold a single patent record each.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | BAE Systems PLC | 6 | |
| 2 | Northwestern University | 2 | |
| 3 | UNIV OF SCI & TECH BEIJING | 1 | |
| 4 | Hamilton Sundstrand Corporation | 1 | |
| 5 | Shanghai Shenjian Precision Machinery Technology Co., Ltd. | 1 | |
| 6 | Shaoxing University | 1 | |
| 7 | Goodrich Corporation | 1 | |
| 8 | Hankaisi Intelligent Technology Co., Ltd. (Guizhou) | 1 | |
| 9 | ZHEJIANG PROVINCE INST OF ARCHITECTURAL DESIGN & RES | 1 | |
| 10 | Goodrich Aerospace Canada Ltd. | 1 |
BAE Systems’ lead reflects deliberate IP strategy in additive manufacturing simulation, likely tied to defense and aerospace qualification workflows. The absence of major process-equipment OEMs or tier-1 automotive suppliers from the ranking suggests the industrial mainstream has not yet committed significant IP resources here.
Patent publications typically lag filings by 18–24 months, so the most recent period may understate true activity levels. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
A 2021 activity spike followed by a pullback; simulation and process control dominate the technology mix
Filing volume was negligible before 2018, surged to six records in 2021, then retreated sharply. The technology composition reveals a dual focus: process-side additive manufacturing and powder metallurgy classes on one hand, and digital/computational classes on the other.
Annual filing trend
The 2021 peak — driven primarily by BAE Systems filings — stands out clearly. Post-2021 volumes are low in absolute terms; given the 18–24 month publication lag, 2024–2025 data should be treated as provisional and likely undercounted.
↗ Hover for values · click a bar to ask EurekaTechnology composition
B33Y (additive manufacturing) and B22F (powder metallurgy) lead the IPC mix, reflecting the process-physics core of this field. G06F (digital data processing) and G05B (control systems) together indicate a strong computational and closed-loop control thread, while G06N (AI/ML) appears at the same frequency as G05B — signaling early-stage machine-learning integration into thermal modeling workflows.
↗ 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.
Real-time simulation and model prediction method f…
The present application relates to a real-time simulation and model prediction method for wire arc additive manufacturing based on event sequences, including: in the real-time process of wire arc additive manufacturing of metal structures, activating elements in real time through event sequences and guiding the heat source in real time; setting heat source… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Systems and methods for global thermal control of … | 28 |
| 2 | Structural simulation of additively manufactured c… | 12 |
| 3 | 一种电弧熔丝增材制造底盘结构设计方法 | 4 |
| 4 | Method for simulating properties of an additively … | 4 |
| 5 | 一种线弧增材制造热历史的预测方法 | 2 |
| 6 | Structural simulation of additively manufactured c… | 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.
BAE Systems PLC
BAE Systems PLC holds six patent records — the largest position in this corpus — concentrated in B22F (powder metallurgy), B29C (plastics shaping), and B33Y (additive manufacturing) subclasses, reflecting a systems-level view of DED process simulation and control. No momentum trend data is available for BAE Systems in the applicant momentum evidence, suggesting its position reflects accumulated filings rather than a recent acceleration.
Patent records: 6Northwestern University
Northwestern University holds two patent records, both anchored in B23K (welding, soldering, and brazing) and B33Y (additive manufacturing) subclasses — positioning it as the primary academic voice on welding-process physics within DED thermal modeling. No momentum trend is recorded for Northwestern University in the applicant momentum evidence, consistent with a steady research-output pace rather than a recent filing surge.
Patent records: 2Frequently asked questions
The corpus covers 13 patent families in scope globally. This is a small, niche corpus, which means individual filings have disproportionate influence on the competitive picture and freedom-to-operate analysis is tractable.
BAE Systems PLC leads with six patent records — the largest single-applicant position in the corpus. Northwestern University is second with two records. All remaining applicants hold one record each.
B33Y (additive manufacturing) leads with eight records, followed by B22F (powder metallurgy) with six and B29C (plastics shaping) and G06F (digital data processing) with five each. G05B (control systems) and G06N (AI/ML computing) each appear four times, indicating a significant computational and control-systems thread alongside the core process-physics classes.
No. Annual filings peaked in 2021 with six records and have eased back since. The lifecycle assessment classifies the field as declining from that peak. The 2024 and 2025 data points should be read cautiously given the 18–24 month publication lag.
The United States leads with six patent records, followed by China and Europe (EPO) with two each and WIPO (PCT) with two. Australia has one record. The US-centric footprint reflects BAE Systems’ primary filing strategy, with limited coverage elsewhere.
Yes. Shanghai Hanghuo Intelligent Technology Co., Ltd. (listed in evidence as Shanghai Hanghe Intelligent Technology) and BF Goodrich (US) are both flagged as new entrants in the applicant momentum data, each with one recent filing. Their entry suggests early commercial interest beyond the established aerospace and academic participants, though each holds a single record.
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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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