Tag Pattern Parsing for Industrial Asset Mapping
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Solution Overview
Problem
In industrial process control and automation systems, managing millions of measurement tags across multiple sites is challenging due to diverse naming conventions, making it difficult for business users and corporate specialists to find required data for analysis and other tasks.
Innovation Solution
A method and system that parse databases of tags to identify patterns, group them, and allow users to map tags to assets based on these patterns, facilitating easier data access and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If millions of measurement tags are consolidated across multiple sites with diverse naming conventions, then the quantity of available data increases, but the difficulty of finding and organizing required data increases
Solution Approach 1:
The patent segments the large set of measurement tags into smaller, organized groups using asset models. Each asset model contains specific tags relevant to that asset, dividing the overwhelming million-tag system into manageable, contextually-grouped subsets that are easier to navigate and understand.
Solution Approach 2:
The patent introduces asset models as intermediary objects between the raw measurement tags and the users. These asset models act as mediators that provide contextual meaning and organization to the tags, bridging the gap between the diverse naming conventions and the user's need for organized data access.
2Measurement precision
If manual mapping of tags to assets is performed, then accuracy of data association improves, but the time and cost required increases
Solution Approach 1:
The patent performs preliminary actions by automatically generating asset models and pre-mapping tags to assets based on pattern recognition before users need to access the data. This preliminary organization reduces the subsequent time and effort required for manual mapping while maintaining accuracy through user verification capabilities.
Solution Approach 2:
The system performs self-service by automatically parsing tag databases, identifying patterns, and creating initial asset model mappings without requiring extensive manual intervention. This automated self-mapping capability reduces both time and cost while allowing users to review and correct mappings as needed to maintain accuracy.
3Adaptability or versatility
If diverse naming conventions are maintained across plants, then local operator familiarity is preserved, but ease of operation for business users decreases
Solution Approach 1:
The patent creates universal asset models that can accommodate multiple local naming conventions simultaneously. Each asset model serves multiple functions by accepting tags from different plants with different naming conventions while maintaining a consistent organizational structure, allowing business users to access data uniformly regardless of the original plant-specific conventions.
Data Source
AI summary
A method and apparatus for mapping measurement tags to assets. At least one memory is configured to store a plurality of tags. At least one processor is configured to parse a database of the plurality of tags to identify patterns of terms, wherein the plurality of tags include one or more terms and are related to measurements performed by an asset in an industrial process control and automation system. The processor is further configured to display the plurality of tags grouped by the identified patterns of terms. The processor is further configured to receive an input to map the tag related to the asset based on the identified patterns of terms. The processor is further configured to map the tag to the asset based on the input.