Robot Arm Optical Inspection for Hard-to-See Surface Defects
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Solution Overview
Problem
Current defect inspection methods in factories are inefficient and costly, particularly when defects are hard to visually identify, leading to potential release of non-standard products.
Innovation Solution
A defect inspection device comprising a robot arm, camera units, illumination units, and a control unit that uses image analysis and machine learning models to determine defects by photographing objects from different angles and under various illumination conditions, enabling accurate classification and transport of defective items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a person checks whether there is a defect in the completed object, then the inspection can be performed with simple equipment, but time and cost consumption is large
Solution Approach 1:
The patent replaces manual visual inspection with an automated inspection system comprising a robot arm, camera units, illumination units, and a control unit with machine learning models. This substitution of mechanical/manual inspection with an automated optical and computational system resolves the contradiction by eliminating time consumption while maintaining inspection capability.
Solution Approach 2:
The inspection system performs self-inspection through automated image capture, processing, and defect detection using pre-trained machine learning models. The system independently determines whether objects are defective without human intervention, achieving both simplicity and efficiency.
2Ease of operation
If a person checks whether there is a defect in the completed object, then the inspection process is simple, but in the case of a defect that is hard to visually check, there may be a problem in that an object which is not normally produced is released
Solution Approach 1:
The patent replaces human visual inspection with an automated optical inspection system using camera units and illumination units controlled by a computer. This substitution enables detection of defects that are hard to visually check while maintaining operational simplicity through automated image processing and machine learning-based defect determination.
Solution Approach 2:
The patent introduces image data as an intermediary between the object and the inspection result. The camera units capture images of the object, and the control unit processes these images using machine learning models to determine defects. This intermediary approach enables accurate detection of subtle defects while keeping the operation simple.
3Measurement precision
If multiple images are photographed under different illumination conditions and arrangement states, then defect detection accuracy is improved, but device complexity and processing time increase
Solution Approach 1:
The patent employs dynamic illumination conditions and object arrangement states to enhance defect detection precision. The illumination unit varies lighting conditions, and the robot arm adjusts object positions to capture images from multiple angles and under different lighting. This dynamic approach improves detection accuracy without requiring overly complex fixed infrastructure.
Solution Approach 2:
The robot arm serves multiple functions: it positions the camera unit, adjusts object arrangement states, and varies illumination conditions. This multi-functionality enables the system to capture diverse images for accurate defect detection while avoiding the need for separate dedicated devices for each function, thereby controlling overall system complexity.
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
The device efficiently identifies defects, reducing time and cost consumption by providing accurate classification and transport of defective products, enhancing the quality control process in factory automation.
Implementation Method 1
an illumination unit irradiating light to the exterior of the object
Implementation Method 2
a first camera unit photographing an exterior of the object
Data Source
AI summary
The defect inspection device includes a robot arm including a hold unit for holding an object and a driving unit for moving the object; a first camera unit photographing an exterior of the object; an illumination unit irradiating light to the exterior of the object; and a control unit determining whether there is a defect in the object based on an image of the object photographed by the first camera unit.