Industrial IDE Analytics for Unified Automation Configuration
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Solution Overview
Problem
Industrial automation systems face inefficiencies due to the need for separate configuration tools for disparate aspects of automation, leading to piecemeal design approaches and significant testing and debugging efforts to ensure proper integration.
Innovation Solution
An integrated development environment (IDE) that provides a common platform for designing, programming, and configuring multiple aspects of industrial automation systems using a unified design environment and data model, including a user interface component, project generation component, training component, and project deployment component, which supports features across the automation lifecycle and leverages analytics for improved design tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If separate configuration tools are used for different aspects of automation, then each tool can be specialized for its specific function, but the overall system complexity increases and integration testing becomes more difficult
Solution Approach 1:
The patent combines multiple separate configuration tools into a single integrated development environment that can handle control programming, visualization development, and device configuration simultaneously. This unified platform eliminates the need for separate tools while maintaining specialized capabilities through modular architecture, directly resolving the contradiction between tool specialization and system integration complexity.
Solution Approach 2:
The IDE is designed as a universal platform that performs multiple functions including control code generation, HMI/SCADA visualization creation, device configuration, and automated testing. This multi-functional approach allows a single tool to replace several specialized tools while maintaining the ability to perform each specific function effectively, thereby reducing integration complexity without sacrificing specialization.
2Ease of manufacture
If multiple separate tools are used for automation configuration, then each tool can focus on specific tasks, but the time required for testing and debugging increases significantly
Solution Approach 1:
The IDE performs preliminary actions by automatically generating device configurations, control logic, and visualization elements during the development phase. It also pre-configures testing frameworks and performs automated validation before deployment, thereby reducing the time required for subsequent testing and debugging activities while maintaining task-specific capabilities.
Solution Approach 2:
The system implements continuous feedback mechanisms where the IDE monitors configuration changes, automatically updates dependent components, and performs real-time validation. This feedback loop enables early detection of integration issues and allows for immediate correction, significantly reducing debugging time while preserving the ability to perform specialized tasks.
3Ease of manufacture
If separate tools are used for control and visualization development, then each tool can be optimized for its specific purpose, but the overall design efficiency decreases
Solution Approach 1:
The IDE merges control development and visualization development into a single integrated environment where both functionalities coexist and interact seamlessly. This combination maintains the optimization for specific purposes through dedicated modules while improving overall design efficiency by enabling concurrent development and automatic synchronization between control and visualization elements.
Data Source
AI summary
An industrial integrated development environment (IDE) includes a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time. The industrial IDE can apply analytics (e.g., artificial intelligence, machine learning, etc.) to project data submitted by developers across multiple industrial enterprises to identify commonly used control code, visualizations, device configurations, or control system architectures that are frequently used for a given industrial function, machine, or application. This learned information can be encoded in a training module, which can be leveraged by the IDE to generate programming, visualization, or configuration recommendations. The IDE can automatically add suitable control code, visualizations, or configuration data to new control projects being developed based on an inference of the developer's design goals and knowledge of how these goals have been implemented by other developers.