Knowledge Graph for Manufacturing SOP — 2026
Knowledge Graph for Manufacturing SOP Technology 2026
Patent records spanning 2000–2026 reveal four converging technical clusters — from ontology schema generation to LLM-augmented graph completion — reshaping how manufacturing SOPs are authored and executed. Chinese filings accelerated sharply from 2021, with two records dated 2026.
Semantic Graphs Redefining Manufacturing Procedural Knowledge
Knowledge graphs for manufacturing SOPs occupy the intersection of four technical sub-domains visible in this dataset: ontology-based semantic modelling of process entities, NLP and LLM integration for procedural knowledge extraction, industrial communication standard alignment (OPC UA, AutomationML), and graph completion via embeddings to infer missing procedural links at runtime.
The core mechanism shared across retrieved patents is the construction of a structured graph in which nodes represent process entities — operations, equipment, materials, parameters, and standards — while edges encode semantic relationships such as sequencing, dependency, conformance, and causality. This graph is queried or traversed to generate, validate, or recommend SOPs rather than relying on static paper or PDF documents.
Publication dates in this dataset span from 2000 to 2026, revealing three distinct maturity phases: a foundational phase (2000–2013) establishing networked knowledge for concurrent engineering, a development phase (2014–2021) focused on ontology-driven interoperability, and a convergence phase (2022–2026) in which LLM-augmented knowledge graph construction and graph completion are becoming dominant.
In this dataset, approximately 35 patent documents were retrieved across targeted searches. Istari Digital, Inc. holds the highest filing count in this dataset with at least 10 records, followed by Siemens Aktiengesellschaft with at least 7, reflecting concentrated IP activity around digital engineering ecosystems and ontology-driven program generation respectively.
Filing Trends and Technology Cluster Distribution
Analysis of the retrieved records reveals filing concentration across four technology clusters and a notable geographic shift toward CN-jurisdiction filings from 2021 onward, with US filings remaining the largest single jurisdiction in this dataset.
Jurisdiction Distribution — Knowledge Graph SOP Patents (Dataset Snapshot)
In this dataset, US-jurisdiction filings account for approximately 18 of ~35 retrieved records, making it the dominant jurisdiction, followed by CN with ~8 and EP with ~3.
↗ Click bars to exploreTechnology Cluster Patent Count — Knowledge Graph SOP (Dataset Snapshot)
In this dataset, Cluster 3 (Knowledge Graph Construction, Completion & LLM Integration) and Cluster 2 (Ontology Schema & Program Automation) hold the highest patent counts, reflecting concentrated recent filing activity in LLM-graph hybrid approaches.
↗ Click bars to exploreWhere Knowledge Graph SOP Technology Is Being Deployed
Retrieved patent and literature records identify five application domains where knowledge graph-based SOP technology is being actively developed and deployed, spanning shop floor maintenance, aerospace, process industries, digital engineering certification, and industrial communication standards.
Shop Floor Operations & Maintenance
Yokogawa Electric’s 2013 US patent digitises paper-based task procedures for field operators of industrial plant assets. Chongqing University’s 2023 CN patent constructs a ternary fusion knowledge graph integrating human expertise (operation manuals, maintenance handbooks), machine-sensed data, and physical IoT data to support SOP-driven operational maintenance decisions on production lines.
In-situ OperationsAerospace & Defense Manufacturing
Boeing’s 2012 US patent integrates engineering definition, process specification standards, and work instructions as a single authoritative reusable dataset. Istari Digital’s patent family (US, 2023–2025; WO, 2024) covers an interconnected digital engineering and certification ecosystem for regulated aerospace and defense industries, automating V&V requirement checking without human input.
Digital EngineeringProcess Industry & Energy
Siemens’ 2021 US patent applies automated configuration planning for process plants (chemical, energy) using flow-diagram-encoded requirements and archive-based standard planning solutions, with a CN equivalent filed in 2023. General Electric’s 2013 US patent applies semantic modelling for workscope recommendation for industrial gas turbines, representing early knowledge-graph-adjacent SOP automation in the energy sector.
Process AutomationIndustrial Communication Standards
The Korea Electronics Technology Institute’s 2020 KR patent covers advanced operation methods for industrial process equipment using AutomationML-to-OPC UA standard conversion. Chongqing University of Posts and Telecommunications’ 2026 CN patent builds a layered industrial knowledge graph with a RAG pipeline to automatically convert unstructured procedural text into standardized OPC UA XML models deployable on production systems.
Machine CommunicationLeading Patent Assignees in Knowledge Graph Manufacturing SOP — Dataset Snapshot
In this dataset, Istari Digital, Inc. holds the highest filing count with at least 10 records (US and WO, 2023–2025), and Siemens Aktiengesellschaft follows with at least 7 records in retrieved records spanning US, EP, CN, and MX jurisdictions from 2007 to 2025. Multiple industrial giants and Chinese university assignees also appear, indicating a contested technology space.
Top Assignees by Filing Count in Retrieved Records (Dataset Snapshot)
↗ Click bars to exploreIstari Digital, Inc.
Istari Digital holds the highest filing count in this dataset with at least 10 patent records covering the interconnected digital engineering and certification ecosystem (US and WO, 2023–2025). Their portfolio spans model-based systems engineering (MBSE) tools, simulation engines, CAD/PLM/supply chain integration, and automated verification and validation (V&V) of SOP and engineering requirements without human input — targeting regulated aerospace and defense manufacturing. Active and pending filings appear across US (2023, 2024, 2025) and WO (2024) jurisdictions.
United StatesSiemens Aktiengesellschaft
Siemens holds at least 7 patent records in retrieved records spanning US, EP, CN, MX, and DE jurisdictions from 2007 to 2025, making it the most geographically distributed portfolio in this dataset. Key technology areas include ontology schema generation for engineering program automation (US 2022, EP 2022, US 2025), automated process system planning for chemical and energy plants (US 2021, US 2023), computer-implemented design knowledge graphs for requirement completeness (EP 2025), and early industrial plant documentation interlinking (MX 2007). This portfolio spans the full SOP lifecycle from requirements through execution.
Germany — DEFrontier Technologies Shaping SOP Knowledge Graphs in 2026
Five clear emerging directions are visible in records dated 2023–2026 in this dataset, centered on LLM-graph hybrid architectures, embedding-based graph completion, OPC UA auto-construction, and automated V&V ecosystems.
LLM + Knowledge Graph Hybrid Architectures for SOP Generation
The 2026 filings from Chongqing University of Posts and Telecommunications (OPC UA auto-construction) and Beijing Institute of Mechanical Science National Innovation (MBSE-based concept design) explicitly integrate Retrieval-Augmented Generation (RAG), large language models, and knowledge graphs. This architecture — where the knowledge graph provides verified, structured procedural knowledge and the LLM provides natural language parsing and generation — represents the frontier for automated SOP authoring at scale. These are the most recent filed records in this dataset.
Graph Completion and Embedding-Based SOP Inference
Robert Bosch’s 2025 DE patent on completing a manufacturing knowledge graph via entity, attribute, and relationship embeddings signals a shift from static SOP encoding to dynamic graph inference. Missing process steps or relationships can be inferred from the graph’s learned embedding space, enabling adaptive procedural reasoning without manual graph maintenance. This approach specifically targets the graph maintenance problem that limits practical deployment of manufacturing knowledge graphs.
Ontology-Driven SOP Automation vs. LLM-Augmented Knowledge Graph Approaches
Click any row to explore further.
| Dimension | Ontology-Driven SOP Automation | LLM-Augmented Knowledge Graph |
|---|---|---|
| Primary Mechanism | Ontology schemas encoding relationships between programming blocks, variables, and KPIs; machine-executable engineering programs generated from schema | Large language models (LLMs) combined with knowledge graphs and Retrieval-Augmented Generation (RAG) to parse unstructured procedural text and generate structured SOP representations |
| Key Patent Example | Siemens — Method and system for generating engineering programs for an industrial domain (US, 2022; EP, 2022; US, 2025) | Chongqing Univ. of Posts and Telecom — OPC UA information model auto-construction using knowledge graph and LLMs (CN, 2026) |
| Input Requirements | Pre-defined ontology schema; structured KPI definitions; existing programming block library | Unstructured procedural text documents; device ontology layer; semantic knowledge layer; RAG pipeline configuration |
| Output | Machine-executable engineering programs for technical installations; automated configuration of industrial systems | Standardized OPC UA XML models deployable on production systems; SysML models auto-generated from complex design requirements |
| Filing Jurisdictions | US, EP (Siemens multi-jurisdiction portfolio spanning MX, CN, DE) | CN primary (2026 filings); DE for graph completion variant (Bosch, 2025) |
| Maturity Phase | Development Phase (2014–2021) through Convergence Phase (2022–2025); Siemens patents active from 2022 onward | Convergence Phase (2022–2026); most recent records in this dataset (2026) |
| Key Limitation Addressed | Human bottleneck in engineering program authoring; interoperability across manufacturing system layers | Inability to process unstructured procedural documents; missing procedural links inferred via graph embeddings |
| Representative Assignees | Siemens Aktiengesellschaft (Germany/US/EP) | Chongqing Univ. of Posts and Telecom (CN); Beijing Inst. of Mechanical Science (CN); Robert Bosch GmbH (DE) |
Frequently Asked Questions — Knowledge Graph for Manufacturing SOP
According to the retrieved dataset, the four sub-domains are: (1) ontology-based semantic modelling of process entities and their relationships; (2) NLP and LLM integration for automated extraction of procedural knowledge from unstructured documents; (3) industrial communication standard alignment (OPC UA, AutomationML) to make graph-encoded procedures machine-actionable; and (4) graph completion and embedding to infer missing procedural links at runtime.
Istari Digital, Inc. (US) holds the highest filing count in this dataset with at least 10 patent records covering the interconnected digital engineering and certification ecosystem across US and WO jurisdictions from 2023 to 2025.
The earliest patent in the dataset is Ford Global Technologies’ ‘Method for simultaneously realizing production and product technology by using network of knowledge’ (JP, 2000), which introduces logic-model-based knowledge encoding for manufacturing process sequencing.
This CN 2026 patent covers an OPC UA information model auto-construction method that builds a layered industrial knowledge graph — combining a device ontology, semantic knowledge layer, and RAG pipeline — to automatically convert unstructured procedural text into standardized OPC UA XML models that can be deployed directly on production systems.
The dataset indicates that while manufacturing knowledge graphs are actively patented, the specific application to Standard Operating Procedures as structured graph objects — covering steps, conditions, compliance rules, and role assignments — is less densely filed than general manufacturing knowledge graphs, representing a potential filing opportunity for organizations with SOP-domain expertise.
All CN-jurisdiction filings in this dataset are from 2021 or later, with two records appearing in 2026. The Chinese assignees include Xi’an Jiaotong University (2021, 2023), Chongqing University (2023), and Chongqing University of Posts and Telecommunications Industrial Internet Research Institute (2026), reflecting an accelerating Chinese academic-industrial presence in LLM-augmented knowledge graph approaches for manufacturing SOPs.
Data and insights on this page are based on a limited patent and literature dataset and are for reference only. Figures may not represent the complete technology landscape.