Autonomous Sanding Head Repair for Surface Defect Finishing
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Solution Overview
Problem
Existing automated finishing systems lack the capability to autonomously detect and repair defects in workpieces efficiently, leading to inconsistent surface finishes and potential damage during material removal processes.
Innovation Solution
A method and system that utilizes an end effector equipped with optical sensors and a sanding head, capable of generating virtual models of workpieces, detecting defects through image analysis, and autonomously navigating to repair them using closed-loop force control and adaptive toolpaths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If automated finishing systems perform material removal to repair defects, then surface defects are repaired, but the risk of damaging the workpiece increases
Solution Approach 1:
The system employs real-time feedback through optical sensors that continuously monitor the workpiece surface during the finishing process. When defects are detected, the system adjusts the material removal process parameters dynamically, comparing actual results with target specifications and making corrections to prevent over-removal or damage while ensuring defect repair.
Solution Approach 2:
The system performs preliminary detection and assessment of surface defects using optical sensors before initiating material removal. Virtual models are created and analyzed in advance to plan the repair strategy, allowing the system to prepare appropriate parameters and paths to minimize damage risk while effectively repairing identified defects.
2Measurement precision
If manual inspection and repair processes are used, then defect detection is possible, but productivity decreases due to labor-intensive operations
Solution Approach 1:
The system enables self-service automation where the automated finishing system independently performs defect detection, virtual model creation, repair path generation, and material removal execution without human intervention. The system autonomously monitors its own performance and adjusts parameters, eliminating the need for manual inspection and repair operations while maintaining high detection accuracy and productivity.
Solution Approach 2:
The system replaces manual mechanical inspection and repair operations with automated optical sensing, computer vision analysis, and robotic material removal. Optical sensors and image processing algorithms substitute human eyes and judgment, while automated control systems replace manual operation, dramatically increasing productivity while preserving defect detection accuracy.
3Productivity
If high material removal rates are used to improve productivity, then processing speed increases, but surface finish consistency deteriorates
Solution Approach 1:
The system dynamically adjusts material removal parameters in real-time based on workpiece geometry, detected defect characteristics, and process conditions. The material removal rate is not fixed but varies continuously to optimize both productivity and surface finish consistency, with the system adapting speeds, forces, and paths according to local requirements.
Solution Approach 2:
The system applies different material removal rates and parameters to different locations on the workpiece based on local requirements. High removal rates are used in areas with significant defects or where material needs to be removed, while lower rates are applied in areas requiring precise finish control, ensuring optimal balance between productivity and surface quality across the entire workpiece.
Data Source
AI summary
A method includes: compiling lower-resolution images, captured during a global scan cycle executed over a workpiece, into a virtual model; defining a nominal toolpath and a nominal target force for the workpiece based on a the virtual model; detecting a defect indicator on the workpiece based on the lower-resolution images; accessing a higher-resolution image captured during a local scan cycle over the defect indicator; characterizing the defect indicator as a defect reparable via material removal based on the higher-resolution image; defining a repair toolpath for the defect based on the virtual model; navigating a sanding head over the workpiece according to the repair toolpath to repair the defect; and, during a processing cycle: navigating the sanding head across the workpiece according to the nominal toolpath and deviating the sanding head from the nominal toolpath to maintain forces of the sanding head on the workpiece proximal the nominal target force.