Global – October 27, 2026 -- An Industrial Knowledge Graph links assets, measurements, events, documents and procedures as connected entities. This gives Industrial AI more relevant context than raw document search, according to a TDengine explainer for OT architects.
Graph links symptoms to causes, checks and approved actions
Nodes cover equipment concepts, fault conditions, maintenance procedures, rules, documents and events. Links express relations such as causes, applies to, requires or precedes. A compressor alarm, for example, can be tied to its troubleshooting procedure, operating conditions and earlier investigation records.
Roller press case shows reuse of a hydraulic pressure investigation
A roller press shut down after hydraulic pressure fluctuated. The maintenance record captured the observed condition, a possible cause, the handling sequence, the pressure limit and required spare parts.
When a similar roller press shows the same fluctuation, the graph helps a maintenance engineer find the earlier investigation and its documented reasoning. It does not prove the new fault has the same cause. The engineer still checks the equipment, operating state and approved procedure.
Three use cases require governance decisions
The explainer names investigation, knowledge reuse and traceability as the practical activities. Teams must still decide which documents are authoritative, how updates are handled, who can access information, and when an engineer must validate a recommendation.
TDengine IDMP runs ontology and document-derived graph in parallel
TDengine IDMP documents Industrial Ontology as a semantic layer that models the physical industrial world: assets, data, relationships and operational context that users configure and maintain. Its Knowledge Graph extracts entities and relationships from uploaded documents and makes the resulting network available for queries and AI context. The source describes this as one documented implementation, not a general definition.
Evaluation should start with one asset class
The explainer recommends scoping a first project to fault investigations for one asset class rather than every document across every plant. It also states that a Knowledge Graph is neither a graph database nor an ontology, and does not necessarily replace RAG or document search.