An Industrial Knowledge Graph is a structured representation of relationships among industrial assets, processes, systems, people, events, and data. It connects information from sources such as equipment records, sensor systems, maintenance logs, engineering documents, and production databases, allowing related entities and their relationships to be understood together. This creates a contextual layer that helps systems interpret not only individual data points but also how different components interact.
Industrial Knowledge Graphs are used in manufacturing, energy, utilities, mining, and process industries to improve data integration and operational understanding. They can support equipment troubleshooting, predictive maintenance, root-cause analysis, asset discovery, and intelligent search. By connecting technical knowledge with operational data, they help organizations uncover relationships that may be difficult to identify using conventional databases. When combined with artificial intelligence, knowledge graphs can provide richer context for reasoning, recommendations, and automated decision-making.
