Automated Visual Inspection System for 100% Surface Coverage
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Solution Overview
Problem
Current inspection methods for manufactured components are limited, typically inspecting only about 1% of the component's surface area, leading to a low confidence level and high rates of undetected defects, especially in complex machines like semiconductor equipment, where many components are sourced from separate suppliers with varying inspection capabilities.
Innovation Solution
An automated visual-inspection system utilizing a plurality of robots with cameras to inspect components at various stages of fabrication, capable of inspecting all surfaces, including those not facing the mounting table, and employing a machine-learning inference algorithm for defect classification and comparison against idealized samples to enhance precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If automated visual inspection system with multiple robots and cameras is implemented, then inspection coverage increases to 100% of component surfaces, but device complexity increases
Solution Approach 1:
The inspection system is divided into multiple independent robotic inspection units, each equipped with cameras and inspection algorithms. Each unit independently inspects specific surfaces or aspects of the component, allowing the system to achieve comprehensive 100% coverage while maintaining manageable complexity through modular architecture. The segmentation of inspection tasks across multiple units resolves the contradiction between extensive coverage and system simplicity.
2Reliability
If detailed inspection of all surfaces is performed, then defect detection confidence increases to 95% or higher, but inspection time increases
Solution Approach 1:
The system performs preliminary automated visual inspection of all component surfaces before detailed analysis. The robotic units first capture comprehensive imagery of entire surfaces, then apply machine learning algorithms to identify and prioritize areas with potential defects. This preliminary scanning approach allows the system to achieve high 95% confidence in defect detection while minimizing total inspection time by focusing detailed analysis only on suspicious areas rather than uniformly examining every surface point.
3Adaptability or versatility
If multiple suppliers are used for component fabrication, then manufacturing flexibility increases, but inspection quality consistency deteriorates
Solution Approach 1:
The automated visual inspection system is designed with universal applicability across multiple suppliers and component types. The robotic inspection units use standardized cameras, lighting systems, and machine learning algorithms that can be deployed at any supplier facility. The system inspects various surfaces including top surfaces, sidewalls, and recesses using the same technical approach, ensuring consistent inspection quality regardless of which supplier manufactured the component. This multi-functional design resolves the contradiction between manufacturing flexibility and inspection consistency.
4Ease of operation
If traditional visual inspection methods are used, then ease of operation is maintained, but measurement precision deteriorates with only 1% inspection area
Solution Approach 1:
The inspection system employs machine learning algorithms that automatically analyze captured images and identify defects without requiring constant human intervention or interpretation. The robotic units autonomously navigate, capture imagery, and process data using embedded algorithms. This self-service capability maintains operational simplicity while dramatically improving measurement precision by inspecting 100% of surfaces compared to traditional 1% manual inspection coverage. The system serves itself by automatically performing tasks that would otherwise require skilled human inspectors.
Data Source
AI summary
Various examples include systems, apparatuses, and methods to perform an automated visual-inspection of components undergoing various stages of fabrication. In one example, an inspection system includes a number of robots, each having a camera, to inspect a component for defects at various stages of fabrication. Generally, each of the cameras is located at a different geographical location corresponding to the various stages in the fabrication of the component. At least some of the cameras are arranged to inspect all surfaces of the component that are not facing a table upon which the component is mounted. The system also includes a respective data-collection station electronically coupled to each the number of robots and an associated one of the cameras. A master data-collection station is electronically coupled to each of the data-collection stations. Other systems, apparatuses, and methods are disclosed.