Industrial Automation Dashboard Layout for Custom KPI Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial automation environments face challenges in effectively monitoring and visualizing operational data from machines, as existing systems lack user customization and dynamic updating capabilities, leading to inefficient data presentation and reduced productivity.
Innovation Solution
A system and method that allow users to select and customize the display of key performance indicators (KPIs) related to industrial operations, including position, style, and properties, enabling the creation of personalized dashboards with continuous updates of dynamic data, facilitating improved monitoring and visualization of machine operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If standardized data display formats are used in industrial automation systems, then system complexity is reduced and ease of operation is improved, but adaptability to different user needs and data presentation requirements deteriorates
Solution Approach 1:
The system dynamically adjusts data presentation formats, layouts, and visualizations based on user preferences, device type, and operational context. Display parameters such as data density, graphical representations, and update frequencies are made adjustable in real-time, allowing the interface to adapt from simplified views for operational efficiency to detailed views for analysis, resolving the contradiction between standardized operation and customized adaptability
Solution Approach 2:
Different regions or sections of the user interface are assigned different levels of customization based on local requirements. Critical operational data maintains standardized presentation for quick recognition, while secondary data allows greater customization options. This enables simultaneous standardization where needed and adaptability where beneficial, addressing both ease of operation and user-specific adaptability needs
2Loss of information
If comprehensive operational data is displayed to improve monitoring capability, then information completeness is improved, but device complexity and information overload increase
Solution Approach 1:
Comprehensive operational data is segmented into hierarchical groups and categories (e.g., critical alarms, performance metrics, operational status, maintenance data). Users can selectively expand or collapse data segments based on current needs, maintaining information completeness while reducing perceived complexity through organized, modifiable display structures that prevent information overload
Solution Approach 2:
The system initially presents a curated subset of most critical data for immediate operational awareness, with optional access to comprehensive data layers. This partial presentation approach prevents information overload while maintaining access to complete data, balancing information completeness with manageable complexity through progressive disclosure and selective data rendering based on operational context
3Productivity
If real-time data updates are implemented to improve monitoring accuracy, then productivity is improved, but energy consumption and system resource usage increase
Solution Approach 1:
Data update frequencies are implemented as periodic actions rather than continuous real-time streaming. The system dynamically adjusts refresh intervals based on data criticality, operational state, and device capabilities - critical safety data updates continuously, while non-critical metrics use periodic polling at optimized intervals. This maintains productivity through timely information while reducing energy consumption by eliminating unnecessary continuous data processing and rendering
Solution Approach 2:
The system dynamically changes data update parameters (frequency, granularity, detail level) based on operational context, device resources, and user preferences. During normal operations, lower update frequencies conserve energy, while during critical events or analysis modes, the system increases update rates. This adaptive parameter adjustment maintains productivity when needed while optimizing energy consumption during routine operations, directly addressing the contradiction between real-time monitoring and resource usage
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.