Mobile Worker Knowledge Graph for Faster Industrial Maintenance
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Solution Overview
Problem
In industrial facilities, the increasing complexity of processes and reduction in human personnel lead to challenges in accessing and understanding asset information quickly during maintenance, resulting in prolonged downtime due to the difficulty in locating necessary information during critical events.
Innovation Solution
A knowledge graph integrated with manufacturing control systems and data analytics, providing a cloud-based platform that automates data integration across disparate environments, enabling operators to access collective knowledge and AI-driven insights for efficient decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If human personnel are reduced to lower costs, then operational costs decrease, but access to asset information during maintenance becomes slower and more difficult
Solution Approach 1:
The system pre-processes and structures asset information into a knowledge graph before maintenance events occur. Historical data, asset relationships, and maintenance procedures are organized in advance, enabling rapid retrieval during critical maintenance situations without requiring additional human personnel time.
Solution Approach 2:
An AI-driven knowledge graph system acts as an intermediary between reduced human personnel and complex asset information. The system bridges the gap by automatically querying, analyzing, and presenting relevant asset data to operators, compensating for reduced human expertise and availability.
2Quantity of substance
If industrial process complexity increases to handle more assets, then asset coverage improves, but information retrieval difficulty increases
Solution Approach 1:
The system segments complex industrial information into structured knowledge graphs with discrete entities, relationships, and attributes. Each asset, process, and maintenance procedure is broken down into manageable knowledge units that can be independently queried and recombined, simplifying navigation through complex industrial systems.
Solution Approach 2:
The knowledge graph system provides universal access to asset information across diverse industrial processes and asset types. A single unified platform handles multiple asset categories (pumps, valves, control systems) and process complexities, eliminating the need for separate information systems for different asset types.
3Reliability
If operators rely on historical records for solutions, then institutional knowledge is preserved, but solution retrieval time increases during emergencies
Solution Approach 1:
The system implements feedback loops where historical maintenance data and operator actions continuously refine the knowledge graph. AI algorithms learn from past maintenance outcomes and operator behaviors, automatically updating the system with new insights and solutions, thereby improving future problem resolution speed while preserving institutional knowledge.
Solution Approach 2:
The system pre-analyzes historical maintenance records and identifies optimal solutions before emergencies occur. AI algorithms process historical data in advance to build a repository of proven solutions and diagnostic pathways, enabling operators to access pre-validated solutions immediately during critical events rather than searching through raw historical records.
Data Source
AI summary
A prescriptive intelligent system is provided for mobile industrial workers At least one data lake stores data associated with industrial assets and processes. At least one orchestration engine applies at least one information standard to at least one ingestion pipeline, which is enabled to process data from the at least one data lake and use artificial intelligence algorithms that identify actionable insights in the data, wherein actionable insights comprise solutions implemented in historical environments and feasible for other environments. A system stores the data as a knowledge graph across different types of technology components for user interfaces. A user interface responds to an excursion associated with an industrial asset and/or process by providing an overview of at least one of an industrial asset and/or process, an alarm, a root cause analysis, and/or a prescribed solution, and coordinates outputs from some of the different types of technology components.