Robot Touchup Visualization for Tool Center Point Wear Detection
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Solution Overview
Problem
Industrial robots experience mechanical wear that leads to inaccuracies in tool center point positions, which are not effectively monitored or analyzed, leading to frequent and unrecorded touchups by operators, making it difficult to detect deterioration trends.
Innovation Solution
A method and system for analyzing touchup data to the robot's tool center point position, providing a graphical display and automated analysis of touchup history, including distance, direction, and frequency, to trigger alerts when specific criteria are met, indicating potential mechanical wear issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If operators manually monitor and adjust tool center point positions without automated analysis, then operational flexibility is maintained, but wear detection capability deteriorates
Solution Approach 1:
The system implements automated feedback by continuously collecting touchup data from robot controllers, analyzing wear trends through comparison against thresholds, and generating alerts when wear patterns indicate potential issues. This closed-loop feedback mechanism enables precise wear detection without requiring operators to manually monitor each robot, resolving the contradiction between detection precision and monitoring complexity.
Solution Approach 2:
The system enables self-service wear monitoring by automatically collecting data from robot controllers, performing trend analysis, and generating maintenance alerts without operator intervention. The automated analysis engine processes touchup data and compares it against wear thresholds, allowing the system to self-monitor wear conditions and notify operators only when actionable insights are generated, thus improving detection capability while maintaining operational simplicity.
2Manufacturing precision
If operators perform frequent touchups to compensate for mechanical wear, then operational accuracy can be maintained, but productivity deteriorates due to increased intervention
Solution Approach 1:
The system performs preliminary wear detection by continuously analyzing touchup data trends and generating alerts before mechanical wear significantly degrades operational accuracy. By detecting wear patterns early through automated threshold comparisons and trend analysis, the system enables preventive maintenance scheduling that prevents accuracy degradation, thereby maintaining manufacturing precision while avoiding the productivity loss associated with frequent reactive touchups.
3Loss of information
If detailed touchup data is collected and analyzed for each robot, then wear trend detection capability is improved, but information processing complexity worsens
Solution Approach 1:
The system extracts only the essential wear-relevant information from touchup data by comparing cumulative touchup distances and frequencies against predefined thresholds. Rather than processing and storing all raw touchup data, the system extracts key metrics such as total touchup distance, frequency of touchups, and directional patterns, then compares these extracted features against wear thresholds. This extraction approach enables effective wear trend detection while minimizing data processing and storage complexity.
Data Source
AI summary
A method and system for analyzing data describing touchups to a robot's tool center point position. A robot operator performs the touchups to a robot's tool center point position when the operator notices inaccuracies in the location of operations performed by the robot—such as a spot weld in a wrong location on a workpiece—where the inaccuracies may be caused by mechanical wear in robot joints. Each operator-defined touchup changes the position and optionally orientation of a particular point in the robot's motion program. The disclosed method provides a graphical display of the history of position touchups for the robot, and analyzes the touchup data against certain criteria for the distance, direction and frequency of the touchups. When the analysis determines that any individual or combination of criteria are met, an alert is provided which indicates a possible mechanical wear issue exists with the robot and needs attention.