Metal 3D Print Support Patents: Who Leads, Where Gaps Are 2026
Filing growth compares 2021 (7 records) with 2024 (17) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 197 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
This landscape tracks published patent records at the intersection of metal additive manufacturing and support-structure optimization — the algorithms, topology methods and platform architectures used to decide where and how support material is generated during a metal print. The scope spans 197 records filed or published between 2015 and mid-2026, drawn from filings that combine additive-manufacturing terms with support-structure and topology-optimization language.
Because publication typically lags filing by around 18 months, the most recent year in the trend is necessarily incomplete — 2024 is the last year that can be read as a full picture, and everything after it will keep filling in as more records publish.
Filing trends and technology composition
Two views of the same 197-record dataset: how filing volume has moved year over year, and how the technology splits across IPC subclasses.
A sharp run-up through 2023, now filling in
Filings rose from 2 in 2017 to a peak of 84 in 2023, with the 2021-to-2024 span alone showing 143% growth (7 to 17 records). The 2025 and 2026 figures are not yet complete and should not be read as a slowdown.
Data platforms and AI outweigh mechanical design classes
G06Q (business/commerce data processing) appears on 73.1% of the 197 records and G06N (AI-based computing) on 37.1%, ahead of G05B control systems (29.9%) and the additive-manufacturing-specific class B33Y (19.8%). That ordering signals that a large share of this claim space is written as fleet-management and predictive-platform IP wrapped around the printing process, not narrow mechanical topology claims.
Shares are the percentage of the 197 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Metal Additive Manufacturing — Metal-Print Support-Structure Optimization Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about metal additive manufacturing — metal-print support-structure optimization patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative filing
Metal Additive Manufacturing for Value Chain Networks
An information technology system for supporting additive manufacturing and value chain workflows includes a cloud-based metal additive manufacturing management platform including an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from one or more additive manufacturing nodes to optimize additive manufacturing and value chain processes and workflows. The information technology system includes a distributed ledger system configured to store data related to the manufacturing nodes.Filed by Strong Force VCN Portfolio 2019, LLC, published 2023-03-23. Claims a cloud platform and distributed-ledger architecture around AI-optimized additive manufacturing nodes, rather than a specific support-topology algorithm.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20220187847A1 | Robot Fleet Management for Value Chain Networks | 341 |
| 2 | US20230123322A1 | Predictive Model Data Stream Prioritization | 338 |
| 3 | US20220197306A1 | Job Parsing in Robot Fleet Resource Configuration | 327 |
| 4 | US20230206329A1 | Transaction platforms where systems include sets of other systems | 236 |
| 5 | US20230214925A1 | Transaction platforms where systems include sets of other systems | 205 |
| 6 | US20220245574A1 | Systems, Methods, Kits, and Apparatuses for Digital Product Network Systems and Biology-Based Value Chain Net… | 194 |
| 7 | US20230222454A1 | Artificial-Intelligence-Based Preventative Maintenance for Robotic Fleet | 140 |
| 8 | WO2022133330A1 | Robot fleet management and additive manufacturing for value chain networks | 138 |
| 9 | US20230173395A1 | Systems and methods with integrated gaming engines and smart contracts | 132 |
| 10 | WO2022240906A1 | Systems, methods, kits, and apparatuses for edge-distributed storage and querying in value chain networks | 127 |
Ranked by citation count within the searched corpus; older records accumulate citations simply by being available longer, so treat this as a signal of influence rather than current relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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The numbers point to a field where platform-level claims dominate and mechanical support-topology claims are comparatively open.
One filer, then a steep drop
The leading assignee alone accounts for 145 of the 197 records in scope, with the remaining ranked assignees holding single-digit to low-double-digit counts. This is not a fragmented field with many mid-size players; it is one dominant filer surrounded by a handful of academic and industrial entrants.
Growth peaked, publication still catching up
Filings climbed from 7 in 2021 to 17 in 2024, with a peak year of 84 in 2023. Because publication lags filing by roughly 18 months, 2025 and 2026 figures will continue to rise as more records publish — they should not be read as a decline.
Platform IP outweighs mechanical topology IP
G06Q and G06N classes cover the majority of records, ahead of B33Y, the additive-manufacturing-specific class, at 19.8%. Filers are more often claiming the data and decision layer around printing than the geometry of the support structures themselves.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to metal additive manufacturing — metal-print support-structure optimization patent landscape, with the prior art for and against each one.
Where to take this analysis
The dataset points to a field where the mechanical optimization problem is comparatively under-claimed relative to the platform and data layer around it.
Map the mechanical claim space directly
Run a narrower search limited to B33Y and G05B classes to isolate support-geometry and control-system claims from the platform-level filings that dominate this dataset.
Explore in EurekaTrack the leading filer's continuations
Given how concentrated the ranking is, monitor the leading assignee's later-filed continuations and divisionals for narrower claims that could still emerge from its portfolio.
Set up monitoring in EurekaWatch academic filings for licensing signals
University-held records in this space are typically earlier-stage and more open to licensing than platform-holder portfolios; a closer read of their claims can surface freedom-to-operate options.
Review academic filings in EurekaCommon questions on this landscape
Within the 197 records in this dataset, one filer — the Strong Force TX/VCN Portfolio entities — holds 145 records, an outsized share of the field. General Electric and two university systems (University of Texas System and Shanghai Jiao Tong University) round out the ranked assignees at much lower volumes. This is a heavily concentrated field rather than one with many mid-size competitors, so freedom-to-operate analysis should start with the leading filer's claim scope.
Filings grew 143% from 2021 to 2024, rising from 7 to 17 records, with the highest single year so far being 2023 at 84 published records. Because patent publication lags filing by roughly 18 months, the 2025 and 2026 figures in the trend are still incomplete and will continue to rise as more records publish. Treat any apparent dip in the most recent one or two years as a data-lag artifact, not a real slowdown.
The IPC composition points strongly toward software and data-platform claims: G06Q (business/commerce data processing) appears on 73.1% of the 197 records and G06N (AI-based computing) on 37.1%, both well ahead of B33Y, the additive-manufacturing-specific class, at 19.8%. That means a large portion of this claim space is written around cloud platforms, predictive models and fleet management applied to additive manufacturing, rather than narrow mechanical topology-optimization algorithms for supports themselves.
Given how much of the ranked filing volume sits in platform and AI-management claims, narrower mechanical and process-specific branches look comparatively under-claimed — areas such as lattice-based support geometry generation, in-process support removal sensing, and multi-material support/build interfaces. A first claim in these areas would want to specify the physical or sensing mechanism precisely, since the dominant filer's claims are architected at the system level and are unlikely to block a tightly drawn mechanical claim. Confirming this requires a follow-up search scoped to the specific mechanical sub-area before filing.
US20230090334A1, assigned to Strong Force VCN Portfolio 2019, LLC and published 2023-03-23, claims a cloud-based metal additive manufacturing management platform with an AI system trained on outcomes and parameters from manufacturing nodes, plus a distributed-ledger system for storing node data. It is architected around the IT and data-management layer of additive manufacturing operations, not around a specific support-structure topology or geometry algorithm. A filing directed at a concrete mechanical or algorithmic support-optimization method is unlikely to be blocked by this claim set, though a full freedom-to-operate review should check the full claim language rather than the abstract alone.
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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.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.