Automation System Configuration Using Simulation Quality Metrics
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Solution Overview
Problem
The configuration of perception systems for autonomously acting systems in industrial automation is a complex, largely manual process that requires end-to-end data transfer and lacks automation, making it inefficient and costly.
Innovation Solution
A method and system that automatically configure automation systems by determining quality metrics through simulation and reference data, optimizing component configurations, including sensors and data processing algorithms, to meet accuracy and performance requirements, using a processing device to select and adjust sensor types, algorithms, and geometric arrangements for improved accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration process is used for perception systems, then flexibility and human judgment are maintained, but productivity and efficiency deteriorate due to time-consuming manual data transfer and configuration steps
Solution Approach 1:
The configuration system automatically performs data transfer, component selection, and parameter optimization without requiring manual intervention. The system self-configures perception systems by autonomously transferring data between tools, selecting appropriate sensors and algorithms, and optimizing parameters based on quality metrics.
Solution Approach 2:
The patent replaces manual mechanical configuration processes with automated computational systems. Instead of manual data transfer between tools and manual configuration steps, the system uses automated data transfer interfaces, algorithmic component selection, and computational optimization to configure perception systems.
2Loss of time
If comprehensive configuration of all perception system components is performed manually, then accuracy and detail are maintained, but loss of time increases significantly
Solution Approach 1:
The system automatically determines optimal configuration parameters for sensors, algorithms, and geometric arrangements by evaluating quality metrics. Instead of manual parameter tuning, the system computationally determines parameters that optimize detection accuracy, processing speed, and overall system performance.
Solution Approach 2:
The patent uses simulation models to create virtual copies of the perception system for testing and optimization. Configuration parameters are first determined through simulation, then transferred to the actual system, reducing the need for repeated manual testing and iteration.
3Device complexity
If multiple specialized tools are used for different configuration aspects, then comprehensiveness is improved, but device complexity increases due to manual data transfer requirements
Solution Approach 1:
The patent merges multiple specialized configuration tools into an integrated automated configuration system. The system combines sensor selection, algorithm configuration, geometric arrangement optimization, and parameter tuning into a unified automated process that eliminates manual data transfer between separate tools.
Solution Approach 2:
The system introduces an automated configuration platform that acts as an intermediary between various specialized tools and the final perception system. This intermediary automatically manages data transfer, ensures data completeness, and coordinates configuration across all components.
4Ease of manufacture
If manual configuration processes are used, then adaptability to specific applications is maintained, but engineering costs increase due to extended configuration time and manual labor
Solution Approach 1:
The system performs preliminary configuration work through automated data collection, simulation, and parameter optimization before actual system deployment. By pre-determining optimal configurations through computation rather than manual trial-and-error, engineering costs are reduced while maintaining application-specific adaptability.
Data Source
Figure 1~3
AI summary
The present invention relates to a method for configuring an automation system (20). The automation system (20) comprises at least one sensor (22) and a data processing device (21) as components. In the method, a quality metric of at least one of the components (21, 22) of the automation system (20) is automatically determined based on a simulation of the automation system (20) and on reference information. Depending on the quality metric, a configuration of the components (21, 22) is determined.