Field Device Data Segmentation for Monitoring Efficiency
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Solution Overview
Problem
Existing systems for industrial data acquisition require high configuration efforts and are limited in administering measured value curves, making it difficult to efficiently monitor and control field devices.
Innovation Solution
A method that involves reading and categorizing field device data into subgroups based on data types and time of generation, displaying them graphically in a coordinate system to facilitate easy correlation and visualization, allowing for simultaneous control of multiple field devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If field device data are administered using known systems limited to measured value curves, then data can be collected and stored, but high configuration effort is required and monitoring efficiency is reduced
Solution Approach 1:
The patent segments field device data into multiple subgroup types (measured value curves, event logs, diagnostic data, configuration data) and displays them in separate selectable areas. This segmentation allows maintenance specialists to focus on specific data types without being overwhelmed by all data simultaneously, reducing configuration effort and improving monitoring efficiency.
Solution Approach 2:
The patent introduces a temporal dimension by automatically determining and displaying time points when data subgroups were generated. This chronological organization across multiple data types creates a comprehensive view without requiring complex manual configuration, resolving the contradiction between monitoring efficiency and configuration effort.
2Loss of time
If multiple field device data are displayed simultaneously, then monitoring time is reduced, but data organization and correlation become more complex
Solution Approach 1:
The display is divided into multiple selectable areas, each dedicated to a specific data subgroup type. Maintenance specialists can select which data types to view simultaneously, organizing complex data into manageable segments that reduce monitoring time while maintaining clear structure.
Solution Approach 2:
The system automatically determines and displays time points when data subgroups were generated, providing temporal feedback that helps specialists correlate events across different data types. This automated temporal organization reduces the complexity of managing multiple simultaneous data displays.
3Loss of information
If field device data are read and displayed with detailed time information, then data correlation is improved, but data processing complexity increases
Solution Approach 1:
The system automatically determines the time points when data subgroups were generated without requiring manual intervention. This self-service approach to temporal metadata extraction improves data correlation capability while minimizing the increase in processing complexity, as the automation handles the complex temporal analysis.
Solution Approach 2:
The system performs preliminary organization of data by time points before display, pre-processing the temporal relationships. This preliminary action ensures that when multiple data types are displayed simultaneously, their temporal correlations are already established, improving data correlation while keeping the display layer simple.
Data Source
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AI summary
A method for controlling and managing field devices, a control unit, a program element, and a computer-readable medium are proposed. The first step of the method is to read field device data, which comprises several subgroups of field device data. In a second step, the times at which each subgroup of the read field device data was generated are determined. A third step of the method is to assign each subgroup of the read field device data to a corresponding field device. Furthermore, in a fourth step, the first group of subgroups of the read field device data is assigned to a first data type, and in a fifth step, a second group of subgroups of the read field device data is assigned to a second data type.Finally, in a sixth step, the subgroups of the read-in field device data are graphically represented in a diagram depending on the times of their generation and depending on their data type.