Industrial Knowledge Graph
A semantic model connecting industrial equipment, process flows, control loops, sensors and operating modes.
PROJECT OVERVIEW
Direction and context
The Industrial Knowledge Graph explores how equipment, instruments, process streams, control loops, measurements, operating modes and maintenance information can be connected into a machine-readable semantic model. The long-term goal is to support industrial analytics, digital twins, AI assistants and structured process reasoning.
Problem
Industrial context is distributed across tags, diagrams, documentation and specialist knowledge without a shared machine-readable model.
Product direction
A semantic graph that represents assets, measurements, relationships and operating context as connected entities.
Intended users
- Industrial data architects
- Automation engineers
- Analytics and digital-twin teams
Capabilities
- Equipment ontology
- Process-flow relationships
- Control-loop context
- Tag integration
- Structured process reasoning
Development timeline
- Domain model research
- Ontology and relationships in design
- Tag integration prototype planned
Current stage
ResearchCurrent focus: Designing the ontology, entity model, relationships and tag integration.
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