Industrial Automation Dashboards for Real-Time KPI Customization
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Solution Overview
Problem
Existing industrial automation systems lack the ability to provide customizable and dynamic visualizations of operational data, limiting user interaction and efficiency in monitoring and analyzing machine performance.
Innovation Solution
A system that allows users to select and customize the display of key performance indicators (KPIs) with defined properties and positions, enabling the creation of personalized dashboards that are dynamically updated with real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If operational data is displayed on fixed systems with predefined interfaces, then data presentation is standardized and reliable, but user customization and adaptability are limited
Solution Approach 1:
The display interface is segmented into multiple independent visualization elements (charts, graphs, indicators) that can be independently selected, configured, and arranged by users. Each element represents a discrete data item that can be customized without affecting others, enabling flexible dashboard creation while maintaining system reliability through modular architecture.
Solution Approach 2:
The system transitions from static predefined interfaces to dynamic customizable dashboards where users can real-time configure display properties, select different data items, and reposition elements. This dynamic configuration capability allows the interface to adapt to different user needs and operational contexts while the underlying data processing remains standardized.
2Loss of information
If comprehensive operational data is presented to all users, then information completeness is ensured, but information overload and difficulty in finding key metrics occur
Solution Approach 1:
Different users can configure their dashboards to display different subsets of operational data based on their specific roles and needs. The system maintains access to all comprehensive operational data but allows individual users to select and prioritize the most relevant metrics for their position, ensuring both data completeness and ease of operation.
Solution Approach 2:
The system provides pre-configured dashboard templates with commonly needed operational metrics already organized and displayed. Users can start with these pre-prepared configurations and then customize them as needed, reducing the time and effort required to set up effective monitoring displays while ensuring key information is immediately available.
3Measurement precision
If real-time operational data is continuously updated and displayed, then monitoring accuracy is improved, but system resource consumption increases
Solution Approach 1:
The system updates and displays only the specific operational data items that users have selected for their dashboards, rather than continuously processing and rendering all available data. This partial action approach maintains real-time accuracy for relevant metrics while reducing computational overhead by excluding unnecessary data processing and rendering operations.
Data Source
AI summary
Techniques to facilitate visualization of an application associated with an industrial automation environment are disclosed herein. In at least one implementation, a plurality of data items associated with machine operations in the industrial automation environment is presented. A user selection of at least one data item of the plurality of data items is received. Additionally, display instructions comprising display properties of the at least one data item and position information that identifies where to display the at least one data item are also received. The display instructions are processed to render a graphical user interface to the application, wherein the at least one data item is displayed according to the display properties and positioned in the graphical user interface based on the position information.