Dynamic Data Grouping in Industrial Condition Monitoring GUIs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial condition monitoring systems face challenges in effectively grouping and presenting data on graphical user interfaces due to the decreasing availability of technically inclined personnel, necessitating improved systems and methods for operating these systems.
Innovation Solution
A system and method that includes a processor and graphical user interface (GUI) capable of receiving data from measurement points, allowing users to select components and specify grouping modes for displaying data visualizations, enabling dynamic grouping and reordering of data analysis workspaces based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is displayed in separate analysis workspaces for each measurement point, then data analysis capability is maintained, but the number of workspaces increases and system complexity increases
Solution Approach 1:
The patent combines multiple measurement point data into a single analysis workspace by implementing dynamic grouping functionality. The GUI allows users to select multiple measurement points and automatically groups their data visualizations together, replacing the need for separate workspaces for each measurement point while maintaining full data analysis capabilities.
Solution Approach 2:
The analysis workspace is enhanced to serve multiple functions simultaneously - it can display data from a single measurement point or multiple measurement points grouped together. The workspace becomes a universal container that adapts its content based on user selection and grouping mode, eliminating the need for dedicated workspaces for each measurement point.
2Device complexity
If traditional GUI interfaces are used, then system operation is simple, but ease of operation decreases for users with limited technical knowledge
Solution Approach 1:
The GUI implements self-service functionality by automatically grouping measurement point data based on user selections without requiring manual configuration. When users select multiple measurement points, the system automatically creates appropriate groupings and displays consolidated visualizations, eliminating the need for users to manually configure complex display parameters.
Solution Approach 2:
The GUI transitions from a static interface to a dynamic one that automatically adapts its display based on user input. The grouping mode and visualization layout change dynamically based on the selected measurement points and data types, providing an intuitive experience that guides users through the analysis process without requiring technical knowledge of the underlying system architecture.
3Quantity of substance
If multiple data analysis workspaces are created for different measurement points, then comprehensive data coverage is achieved, but productivity decreases due to increased navigation time
Solution Approach 1:
The patent merges data from multiple measurement points into consolidated visualizations within a single workspace. By grouping related measurement data together and displaying them in unified views, the system maintains comprehensive data coverage while eliminating the need for users to navigate between multiple separate workspaces, thereby significantly improving analysis efficiency.
Solution Approach 2:
The system organizes data in a new dimensional structure where multiple measurement points are grouped hierarchically within a single workspace rather than requiring separate flat workspaces. This dimensional reorganization allows comprehensive data coverage to be achieved through nested grouping structures, reducing navigation requirements while maintaining full data accessibility.
Data Source
AI summary
A method for grouping content displayed on a graphical user interface may include displaying selectable components that correspond to types of measurement data associated with a device or a component within the device. The method may then include receiving a selection of one of the selectable components, such that the one of the selectable components corresponds to a portion of the measurement data. The method may then receive a grouping mode input to specify characteristics for display of the portion of the data as data processing outputs. The method may then include displaying the data processing outputs associated with the selection, such that each respective data processing output may include visualizations associated with datasets of the portion of the measurement data. The respective visualizations of the respective data processing output may be displayed together based on an association between the respective datasets and the grouping mode input.