AI Document Extraction for Autonomous Control System Configuration
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Solution Overview
Problem
The configuration of automation systems in process plants is time-consuming, error-prone, and requires human intervention, making it difficult to achieve autonomous reconfiguration.
Innovation Solution
An automated method using a pretrained AI model to extract configuration data from various document types, such as P&ID diagrams and HMI diagrams, to generate structured configuration information for control agents, enabling autonomous control system configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual information collection and extraction from multiple documents is performed, then configuration accuracy can be maintained through human review, but the configuration process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces the mechanical manual process of information collection and extraction with an automated information processing system that uses natural language processing and machine learning models to extract configuration data from process documentation, thereby eliminating manual labor while maintaining extraction accuracy through validated information processing algorithms
Solution Approach 2:
The system enables self-service configuration by automatically gathering information from multiple document sources, extracting relevant parameters, and generating control system configurations without requiring human intervention, allowing the system to configure itself autonomously while maintaining accuracy through built-in validation mechanisms
2Productivity
If automated information extraction is implemented, then configuration speed and productivity are improved, but error-proneness increases due to lack of human review
Solution Approach 1:
The patent implements feedback mechanisms where the automated extraction system continuously validates extracted information against multiple document sources and cross-references data consistency, allowing the system to detect and correct extraction errors automatically while maintaining high configuration speed through efficient feedback loops
Solution Approach 2:
The system performs preliminary validation and cross-checking of extracted information before final configuration generation, pre-identifying potential errors or inconsistencies in the extracted data to prevent configuration mistakes before they occur, thereby maintaining reliability without sacrificing automation speed
3Reliability
If human intervention is required for configuration, then system safety can be ensured through expert review, but the system cannot achieve autonomous reconfiguration during operation
Solution Approach 1:
The patent enables the control system to perform self-service reconfiguration by automatically detecting changes in process requirements, extracting updated configuration parameters from documentation, and autonomously generating new control configurations without human intervention, thereby achieving both safety through validated algorithms and adaptability for runtime reconfiguration
Solution Approach 2:
The system implements dynamic reconfiguration capabilities that allow the control system to adapt to changing process conditions in real-time by automatically updating configurations based on current operational data and documentation, enabling the system to be both safe through controlled changes and highly adaptable to runtime requirements
4Quantity of substance
If comprehensive information is collected from multiple documents, then configuration completeness is improved, but the complexity of information management increases
Solution Approach 1:
The patent applies segmentation by dividing the information extraction process into distinct modules that handle different document types and extract specific parameter categories separately, allowing the system to manage comprehensive information from multiple documents through organized, modular processing that reduces overall system complexity
Solution Approach 2:
The system implements a universal information extraction framework that can process multiple document formats and types through a single integrated platform, enabling the system to collect comprehensive information from diverse sources while maintaining manageable complexity through standardized processing protocols and unified data structures
Data Source
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AI summary
The present invention relates to a computer-implemented method (100) for for an automated configuration of a control system (200), comprising: - Collecting (102), by a document-type identifier module (50), first information (10) from at least a document database (60), wherein the collecting involves the step of detecting (103) a document type information (61) of at least one document (62) found in the at least one document database (60) and if, the identified document type information (61) of the at least one document (62) fulfils a certain quality parameter (63), suggesting the first information (10) to be extracted from the at least one document (62) with that identified document type information (61); - Extracting (104), by an extraction module (52), the suggested first information (10) from the at least one document (62) with the identified document type information (61) to obtain second information (12); - Generating (106), by a plant section module (54), at least one plant section (310) of a plant system (300) on basis of the second information (12); - Generating (108) a configuration information (14), by a configuration module (55), for at least one control agent (220) of the control system (200) for the automated control of the at least one plant section (310) of the plant system (300).