Robotic Sanding Workflow for Vision-Guided Surface Defect Removal
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Solution Overview
Problem
Existing methods for detecting and sanding surface defects on vehicle bodies, such as fine bending and irregularities, are limited by image processing techniques and automation challenges due to complex shapes, leading to quality deviations and potential equipment interference.
Innovation Solution
A sanding automation system using robots to generate inspection marks with uniform pressure, analyze defects through vision systems, and perform sanding operations with controlled pressure and suction to ensure accurate and efficient removal of surface defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If camera-based image processing techniques are used to detect surface defects, then detection automation is improved, but detection precision deteriorates because fine bending on non-flat surfaces cannot be detected
Solution Approach 1:
The system performs preliminary action by generating inspection marks on the vehicle body surface before defect detection. These marks are created in advance to enhance the visibility of surface defects, allowing the vision system to accurately detect fine bending and other subtle defects that would otherwise be invisible to automated detection systems.
Solution Approach 2:
The inspection marks change the visual appearance of the surface by creating contrasting patterns that highlight surface irregularities. The marks make subtle surface defects visible through visual contrast, enabling the vision system to detect fine bending and other surface imperfections with high precision.
2Measurement precision
If manual inspection and sanding operations are performed by skilled operators, then measurement precision is improved, but productivity deteriorates due to quality deviations depending on skill level
Solution Approach 1:
The system replaces manual mechanical inspection and sanding operations with an automated system combining vision technology and robotic sanding. The vision system automatically detects surface defects, and a robot performs sanding operations, eliminating quality deviations caused by operator skill variations while significantly improving productivity.
Solution Approach 2:
The system enables self-service by allowing the vehicle body to indicate its own defects through the inspection marks. The vision system reads these marks to automatically identify defect locations and characteristics, eliminating the need for manual inspection while maintaining high detection precision.
3Productivity
If robot-based sanding automation is implemented, then productivity is improved, but reliability deteriorates due to contact and interference with equipment from complex vehicle body shapes
Solution Approach 1:
The system applies local quality by generating inspection marks with specific local characteristics that encode surface defect information. These marks are created with particular patterns and densities tailored to different surface conditions, allowing the robot to reliably identify and sand only the necessary areas without interference from complex vehicle body geometries.
4Measurement precision
If inspection marks are generated to secure visibility for surface defect detection, then measurement precision is improved, but device complexity increases due to additional marking equipment and processes
Solution Approach 1:
The system achieves universality by using a single robotic system that can perform both inspection mark generation and sanding operations. The robot is equipped with interchangeable tools, allowing it to function as both a marking device and a sanding device, thereby reducing overall system complexity while maintaining high detection precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces quality deviations and human errors, minimizes exposure to harmful environments, and lowers production costs by automating surface defect inspection and sanding processes, while enabling data management for future process improvements.
Implementation Method 1
a dust absorption module for removing dust generated on the vehicle body by generating suction force
Data Source
AI summary
A sanding automation system for removing a surface defect of an exterior component includes a first robot for generating an inspection mark of a certain pattern on an exterior component with uniform pressure through an inspection mark tool to secure visibility of a surface defect, a vision system for analyzing an image of the exterior component photographed through at least one vision sensor and recognizing a surface defect marking position and a surface defect depth level displayed on the exterior component on which the inspection mark is generated, and a second robot for removing the surface defect by sequentially moving a sanding tool to at least one of the surface defect marking positions and performing a sanding operation with the set amount of sanding according to a corresponding surface defect depth level.