https://eureka.patsnap.com/resources/blog/rd-blog/machine-learning-based-predictive-quality-control-using-statistical-process-control-patent-patent-landscape/ · Patsnap · data cut-off 2026-10-15 · downloaded from the live page
Patent Landscape · Advanced Manufacturing

Machine Learning Based Predictive Quality Control Patents Using Statistical Process Control

28 simple patent families and 59 published records cover ML/SPC predictive quality control, with filings split across 21 listed organisations.

59
Published Records
28
Simple Patent Families
41%
In Force at Cut-off
EP
Leading Jurisdiction

59 published records collapse into 28 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 24 of 59 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.

  • 28 simple patent families and 59 published records make up this dataset, with no date limit applied to the search string.
  • Five filers tie at the top each holding 2 of the 28 simple patent families; the largest single row.
  • G05B and G06N lead the IPC mix appearing on 42.9% and 39.3% of the 28 families respectively, ahead of G06Q at 25.0% and G01N at 17.9%.
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Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview

What this dataset covers

This set gathers records matching statistical process control or SPC alongside machine learning or predictive model terms, combined with manufacturing or quality-control language. The search string sets no date limit, so the dataset spans whatever filing years the matching records happen to carry, and the chart on this page shows only a recent filing window rather than the full set. Across the result, 28 simple patent families correspond to 59 published records, reflecting that single inventions are frequently filed into more than one office.

This is a small pool: 28 families is not enough to support claims about market concentration, technology maturity or white space, and the search string itself may have pulled in records that only loosely match the intended topic. Treat this page as a starting point for a more targeted search, not as a map of the field.

Records vs. families in scope
  1. SHENZHEN MINDRAY BIO MEDICAL ELECTRONICS CO LTD2
  2. ELISA OYJ2
  3. WEARNE DIGITAL PTE LTD2
  4. NIMS UNIV RAJASTHAN JAIPUR2
  5. SRI ESHWAR COLLEGE OF ENG2
  6. RIVIAN HOLDINGS LLC1
  7. AUSET PACIFIC PTY LTD1
  8. Yunnan Guoti Metal Co., Ltd.1
  9. NANOTRONICS IMAGING INC1
  10. PROF DR VANDANA SINGH1

Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. Filings held by named individuals rather than organisations are removed where they can be identified (5 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 21 of the 21 filers returned for this search; the data endpoint returns at most 100 entities, so even that 21 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.

Source: Patsnap Eureka. Assignee ranking and totals. Derived from one Patsnap search for Machine Learning Based Predictive Quality Control Using Statistical Process Control Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
The numbers

Filing trend and technology composition

Two views of the same 28-family dataset: how publication activity by filing year moves through the available window, and which IPC subclasses recur most across the families.

Filing trend (published records, by earliest filing year)

Records run from 2018 through 2026, with a peak so far at 2019 (14 records). From 2022 onward the counts are still filling in as later filings publish, so no decline should be read into the most recent years.

Filing trend (published records, by earliest filing year)048111532018142019202020212022202320242025420262022 onwards are shaded as still filling in: a filing is only visible once it publishes, up to 30 months after filing.

Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two.

IPC subclass composition (share of 28 simple patent families)

G05B (control and regulating systems) appears on 42.9% of families and G06N (AI-based computing) on 39.3%, with G06Q (business/admin data processing) at 25.0% and G01N (material analysis and testing) at 17.9%. Because a family can carry more than one IPC class, these shares add up to more than 100%.

IPC subclass composition (share of 28 simple patent families)G05B · Control & regulating systems1242.9%G06N · Computing based on AI models1139.3%G06Q · Business, commerce & admin dat…725.0%G01N · Material analysis & testing517.9%G16H · Healthcare informatics414.3%G06F · Electric digital data processi…310.7%H01L · Semiconductor devices310.7%A61B · Diagnosis & surgery27.1%Other2071.4%

Shares are the percentage of the 28 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.

Source: Patsnap Eureka. Filing trend and technology composition. Derived from one Patsnap search for Machine Learning Based Predictive Quality Control Using Statistical Process Control Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.

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Record in focus

One record from the result set

As returned by the search
EP4723126A12026-04-08

EP4723126A1, real-time quality control from patient sample data

Shenzhen Mindray Bio-Medical Electronics Co. Ltd.

The abstract describes a method and system for patient-based real-time quality control during instrument testing, and a method for building the underlying quality control model. The system acquires actual test results for a target item together with patient information such as disease, age, gender or ordering department, and uses that patient information to inform the quality control process alongside the live test results.This is the first record returned under the database's default ordering, not the most cited, newest or broadest filing in the set. What its granted claims actually require has to be read from the claim set itself; an abstract and a family count cannot establish claim scope.

EP4723126A1, patent drawing 1EP4723126A1, patent drawing 2
View full record

Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.

Source: Patsnap Eureka. The first record the search returned, shown in full. Derived from one Patsnap search for Machine Learning Based Predictive Quality Control Using Statistical Process Control Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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Patterns in the data

What the filer and classification counts show

These figures describe counts only: how many families each listed filer is named on, and how many families carry each IPC subclass. Neither establishes scope, importance or market position.

Filer concentration
7.1%
largest single-row share

Top row holds 2 of 28 families

Shenzhen Mindray Bio-Medical Electronics Co Ltd is named on 2 of the 28 simple patent families in scope (7.1%). Four other listed filers also hold 2 families each, so five rows share the top count rather than one filer standing above the rest.

Counted in simple patent families
Long tail
21 of 21
listed filers at 2 or fewer families

No listed filer exceeds 2 families

All 21 listed filers hold 2 or fewer simple patent families each. Filer rows are not rolled up to corporate group and can overlap when a family names more than one filer, so rows cannot be summed into a coverage or concentration figure.

Counted in simple patent families; 21 organisations listed
IPC composition
42.9%
families tagged G05B

G05B and G06N recur most across families

G05B (control and regulating systems) appears on 12 of the 28 families (42.9%) and G06N (AI-based computing) on 11 of 28 (39.3%). G06Q (business/admin data processing) and G01N (material analysis and testing) follow at 25.0% and 17.9%. Shares add to more than 100% because a family can carry multiple IPC classes.

Counted in simple patent families
Legal status
41%
of 59 records granted and in force

24 of 59 records are in force at retrieval

24 of the 59 published records were granted and still in force as of the 2026-10-15 retrieval date. The remainder are pending, withdrawn, refused, lapsed or not determinable, and this breakdown is not available on this page.

Counted in published records; status as of retrieval
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Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Machine Learning Based Predictive Quality Control Using Statistical Process Control Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Next steps

Where to take this from here

This page is a first pass over a small, broadly worded search. Narrowing the terms or reading individual claim sets is the next step for any of the following.

Narrow the search string

The topic terms are broad enough to pull in records that only loosely match predictive quality control. Tightening the Boolean string and re-running the search would separate genuine matches from noise, particularly among the smaller IPC subclasses this page does not break out.

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Read granted claims directly

Family and IPC counts cannot establish what any single filing covers. For any record of interest, including EP4723126A1, the next step is pulling the granted claim set rather than relying on the abstract.

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Track new publications

Because 2022 onward is still filling in as later filings publish, a monitoring search catches new records in this space as they appear rather than relying on a one-off snapshot.

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Source: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Machine Learning Based Predictive Quality Control Using Statistical Process Control Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
FAQ

Common questions about this dataset

Answers are grounded in the same dataset. Derived from one Patsnap search for Machine Learning Based Predictive Quality Control Using Statistical Process Control Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP

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How this page was built, and what the numbers do and do not mean

Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:

TAC:(("statistical process control" OR "SPC") AND ("machine learning" OR "predictive model") AND (manufactur* OR "quality control"))

Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. No subclass carries much of this set: the most common one is on 42.9% of the patent families and the set spans 25 subclasses in all. That can mean the technology genuinely sits across several areas, or that the search string is also matching adjacent work that happens to use the same words. This page cannot separate the two, and the result set is not screened by hand.

What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 59 records and 28 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.

Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (5 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 21 of the 21 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 21 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included

Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-15.

Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (24 of 59). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka

Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level

Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.

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 limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. 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, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records 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.

The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.

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.

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