Energy Facility Alert Analysis Using a Knowledge Graph
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Solution Overview
Problem
SMEs tasked with managing energy production or processing facilities face inefficiencies in analyzing alerts due to the need to manually consult a wide range of data sources, demanding significant time and limiting their ability to oversee multiple facilities.
Innovation Solution
A system and method that utilizes a data structure, such as a knowledge graph, to integrate and analyze diverse data sources, automating the process of identifying alert causes and recommending corrective actions, thereby reducing the time SMEs spend on manual data retrieval and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SMEs manually consult multiple data sources to analyze alerts, then they can identify root causes accurately, but it demands significant time and limits their ability to oversee multiple facilities
Solution Approach 1:
The system performs preliminary actions by pre-integrating and organizing data from multiple sources into a unified data structure before alerts occur. When an alert is generated, the relevant data is already structured and linked, eliminating the need for SMEs to manually search and correlate data from disparate sources during the analysis process.
Solution Approach 2:
The patent introduces an intermediary system that sits between the multiple data sources and the SMEs. This intermediary automatically retrieves, integrates, and organizes data from various sources (process control systems, maintenance management systems, etc.) into a unified view, allowing SMEs to focus on analysis rather than data collection.
2Reliability
If SMEs manually retrieve and analyze data from multiple sources, then they can provide thorough technical support, but it limits their capacity to manage multiple facilities
Solution Approach 1:
The system creates a universal data structure and interface that can handle data from multiple facilities through the same framework. The unified data model allows a single SME to efficiently manage multiple facilities by providing consistent access to integrated data regardless of the facility or equipment type, thereby increasing productivity without compromising support quality.
Solution Approach 2:
The system segments the complex task of multi-facility management into manageable components by organizing data hierarchically (facilities → equipment → data sources). This segmentation allows SMEs to focus on specific equipment or facilities when needed while maintaining an overview of all managed assets, enabling them to oversee more facilities effectively.
3Loss of time
If the system integrates and analyzes diverse data sources automatically, then it reduces the time SMEs spend on manual data retrieval, but it increases the complexity of the data integration system
Solution Approach 1:
The system manages complexity by changing parameters of the data structure rather than creating complex integration logic. It uses standardized data models,统一的标识符 systems, and configurable parameters that can be adjusted without redesigning the entire integration architecture, making the system more manageable despite handling diverse data sources.
Data Source
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AI summary
A method for facilitating the management of one or more energy production or processing facilities includes receiving an alert corresponding to an operational anomaly associated with the process equipment, interrogating a data structure linking together and organizing a plurality of distinct data sources, selecting a subset of data sources from the plurality of data sources identified as associated with a potential cause of the alert based on the interrogation of the data structure, statistically analyzing data sourced from the selected subset of data sources, identifying the potential cause of the alert based on the statistical analysis, and recommending a corrective action to resolve the identified potential cause of the alert using the plurality of distinct data sources.