Signal Rule Annotation for Assembly Data Across Unreliable Networks
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Solution Overview
Problem
Current methods for data analysis in digital plants face challenges such as limited algorithm capabilities, dependency on manual operations, and network issues affecting data transmission, leading to incomplete or delayed analysis.
Innovation Solution
A method for determining data obtaining logic based on assembly model information, identifying physical signals, and applying signal rules to annotate data using a semantic ontology module, ensuring data context and consistency across networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is transmitted through networks with varying transmission capabilities, then data can be collected from remote sensors, but network issues cause transmission delays and incomplete data
Solution Approach 1:
The system performs preliminary actions by downloading analysis algorithms locally to edge devices before data transmission is needed. This allows data to be processed at the source even when network transmission is unreliable or delayed, ensuring continuous analysis capability independent of network conditions.
Solution Approach 2:
The patent introduces an intermediary layer (edge computing devices/gateways) between sensors and cloud centers. This intermediary performs local data processing and analysis, mediating between data collection and cloud-based analysis, thereby reducing dependency on stable network transmission.
2Reliability
If analysis algorithms are downloaded locally to enable offline analysis, then data can be analyzed without network dependency, but algorithms are limited to specific data types and cannot perform complex system-wide analysis
Solution Approach 1:
The system dynamically adapts algorithm deployment based on data types and analysis requirements. Simple, frequent analysis tasks use locally deployed algorithms for immediate processing, while complex, system-wide analysis tasks utilize cloud-based algorithms when network conditions permit, creating a flexible, multi-level processing architecture.
Solution Approach 2:
The analysis system is segmented into multiple levels: edge devices handle local, real-time analysis with specialized algorithms, while cloud centers perform comprehensive, system-wide analysis with advanced algorithms. This segmentation allows each layer to use algorithms optimized for its specific requirements.
3Reliability
If historical data is used for analysis, then analysis can continue without online services, but online services cannot be provided during emergencies
Solution Approach 1:
The system implements feedback mechanisms where local analysis results are continuously compared with historical patterns and cloud-based insights. This feedback loop enables the system to maintain productive online services by learning from historical data while still providing real-time analysis capabilities.
4Measurement precision
If expert operators manually analyze on-site automated systems, then complex analysis can be performed, but the process is too dependent on manual operation
Solution Approach 1:
The system implements self-service capabilities through automated analysis algorithms that independently process data, identify patterns, and generate insights without requiring manual expert intervention. The system serves itself by continuously learning from data and improving its analysis capabilities autonomously.
Data Source
AI summary
A method, apparatus, and system are for determining signal rules and annotating data. The method, according to an embodiment, includes: determining data obtaining logic based on assembly model information corresponding to the assembly; wherein the data obtaining logic includes a to-be-obtained data object and an obtaining rule; determining at least one physical signal corresponding to the data obtaining logic; and determining, based on the data obtaining logic and the at least one physical signal corresponding to the data obtaining logic, a signal rule corresponding to the obtaining rule. By annotating the running data of an assembly, the context of the data may be indicated, so that the running data of the assembly can be made more consistent, easier to maintain, and/or applied to a new environment. Moreover, since the annotation information of data can adopt a common format, it may be more suitable for information migration and system configuration.