Robotic Control Panel Manipulation for Precise Industrial Adjustments
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Solution Overview
Problem
Existing methods for testing and adjusting industrial equipment control systems face inefficiencies due to uncertainty in control system software versions and human operators' inaccuracies in performing timely and accurate control adjustments.
Innovation Solution
A system utilizing robotic arms controlled by a data analytics server to automatically manipulate control panel elements based on operational data analysis, enabling precise and timely adjustments without direct integration or human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human operators manually adjust control panel elements, then flexibility and adaptability are maintained, but accuracy and timeliness of adjustments deteriorate due to human error and response time limitations
Solution Approach 1:
The control system performs self-adjustment through robotic arms that automatically manipulate control panel elements based on analytics data, eliminating the need for manual human intervention while maintaining system adaptability through automated decision-making algorithms
Solution Approach 2:
The patent replaces human manual operations with robotic arms equipped with computer vision and precision control systems, substituting mechanical human interaction with automated robotic manipulation to achieve higher accuracy and consistency
2Measurement precision
If direct integration with control system software is implemented, then control precision is improved, but system complexity and integration difficulty increase
Solution Approach 1:
The patent introduces an intermediary layer consisting of computer vision systems and image processing algorithms that translate visual information from control panels into control signals, avoiding direct software integration while maintaining precise control through visual recognition and pattern matching
3Productivity
If automated robotic manipulation is implemented, then productivity and timeliness are improved, but adaptability to different control panel configurations deteriorates
Solution Approach 1:
The robotic system employs dynamic adaptability through real-time image processing and machine learning algorithms that enable the robotic arms to automatically adjust their manipulation strategies based on detected control panel configurations, maintaining high productivity across diverse panel types
Solution Approach 2:
The system changes operational parameters such as robotic arm positioning, gripper force, and movement speed based on detected control panel characteristics, enabling automated adaptation to different configurations while maintaining efficient operation
Data Source
AI summary
Systems and methods presented herein utilize one or more robotic arms and a data analytics server in conjunction with existing control systems. The data analytics server is configured to receive operational data relating to operation of industrial equipment being controlled by a control system. The data analytics server is also configured to perform data analytics on the operational data. The data analytics server is further configured to determine one or more control signals configured to cause the one or more robotic arms to automatically manipulate one or more control elements of a control panel of the control system. In addition, the data analytics server is configured to automatically transmit the one or more control signals to the one or more robotic arms to cause the one or more robotic arms to automatically manipulate the one or more control elements of the control panel of the control system.