Signal Selection Interface for Industrial Data Extraction
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Solution Overview
Problem
Non-automation experts face challenges in extracting relevant data from distributed control systems due to the large size of the address space and the need for specialized knowledge, making manual identification time-consuming and often infeasible, especially without the involvement of automation experts.
Innovation Solution
A signal selection agent that uses a domain knowledge mapping model and intuitive user interface to facilitate signal identification and selection, enabling data extraction by mapping domain concepts and knowledge to signals, thereby reducing the time required for configuration and making the process feasible for non-experts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of relevant signals by browsing the address space is performed, then data extraction can be achieved, but it is time-consuming and requires specialized automation knowledge that non-experts do not possess
Solution Approach 1:
The patent introduces an intermediary component (signal selection agent with domain knowledge mapping model) that mediates between the data scientist and the complex DCS address space. This intermediary automatically maps domain concepts to relevant signals, eliminating the need for data scientists to manually browse and understand the complex address space structure, thus resolving the contradiction between extraction accuracy and configuration time.
Solution Approach 2:
The system enables self-service by allowing data scientists to perform data extraction configuration without requiring automation experts. The domain knowledge mapping model automatically interprets domain concepts and identifies relevant signals, making the system self-configuring from the perspective of non-expert users, thereby reducing both time and knowledge requirements.
2Quantity of substance
If all accessible data is exported from the DCS, then complete data availability is achieved, but high load is placed on the DCS and most data is irrelevant for analysis
Solution Approach 1:
The patent applies the extraction principle by selectively extracting only the relevant signals needed for data analysis from the large address space, rather than exporting all accessible data. The domain knowledge mapping model identifies and extracts only the necessary signals, reducing data volume and system load while maintaining data quality for analysis purposes.
Solution Approach 2:
Instead of performing excessive action (exporting all data), the system performs partial action by exporting only the subset of signals that are relevant for analysis. The domain knowledge mapping enables selective extraction of necessary signals, avoiding the overhead of handling unnecessary data while ensuring complete coverage of relevant information.
3Ease of operation
If the address space is made browsable via standardized interface, then data accessibility is improved, but the large size of the address space makes manual identification challenging and infeasible
Solution Approach 1:
The patent applies segmentation by dividing the large address space into manageable domains based on domain concepts. Instead of presenting the entire address space to users, the system segments it into meaningful categories (e.g., process control, safety systems, instrumentation) that align with industrial automation domains, making navigation and signal identification feasible for non-experts.
Solution Approach 2:
The domain knowledge mapping model serves multiple functions: it acts as a translator between domain concepts and address space elements, as a filter for relevant signals, and as a guide for navigation. This multi-functional approach enhances ease of operation by providing a universal interface that handles various aspects of data extraction without requiring users to understand the underlying complexity.
Data Source
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AI summary
There is provided a system and corresponding method for providing a configuration for data extraction from an automation system (100). The system comprises a signal selection agent (200) configured to: receive a user selection of at least one module of the automation system (100); generate, for display to the user, a user interface (212) identifying one or more selectable signals associated with the selected module and displaying one or more guidance elements (214-218) comprising data mined from data sources (202-206) pertaining to the automation system (100) for guiding the user in the selection of relevant signals; receive a user selection of one or more of the selectable signals; and automatically generate the configuration for data extraction on the basis of the selected signals.