Industrial Equipment Data Organized into Smart Knowledge Graphs

Honeywell's patent describes a system that collects data from industrial equipment, makes sense of it using rules, and organizes it into a smart graph for better control and actions.

What it covers

This patent details a system for industrial settings that creates a 'knowledge graph' about equipment. It starts by receiving a request that includes a description of the equipment (an 'asset descriptor'). Then, it gathers operational data from various sources related to that equipment. The core innovation is 'contextualizing' this raw data using specific configuration details and rules. This means making the data understandable and relevant, like translating different machine languages into one common tongue. The processed data is then organized into a knowledge graph structure. Finally, the system can perform actions based on this organized knowledge, like adjusting equipment settings or flagging potential issues. For example, it could gather vibration data from a pump, combine it with its maintenance history and operating parameters, and then identify that a specific type of unusual vibration pattern indicates an imminent bearing failure, triggering an alert.

What it doesn't cover

• —Does not cover systems that collect data without contextualizing it using specific rules and configuration data.
• —Does not cover knowledge graphs that are not specifically configured for the described industrial assets.
• —Does not cover systems that do not perform actions based on the generated knowledge graph data.
• —Does not cover the collection of data from non-operational technology sources.
• —Does not cover knowledge graphs that are not organized within a defined data structure.

The clever bit

The real ingenuity lies in the 'contextualization' step. Instead of just collecting raw data, the system intelligently interprets it using specific rules and configuration data unique to the assets and their data sources, transforming disparate operational technology data into meaningful insights within a structured knowledge graph.

Why it matters

In complex industrial environments, equipment generates vast amounts of data. This patent provides a structured way to make that data actionable. By creating a 'knowledge graph,' it allows for a deeper understanding of how different pieces of equipment and their data relate, which is crucial for optimizing operations, predicting failures, and improving safety in sectors like manufacturing and energy.

Real-world examples

• 1.Industrial automation systems
• 2.Manufacturing plant monitoring
• 3.Energy grid management
• 4.Predictive maintenance platforms
• 5.Smart factory software