Optical Inspection Measurement Across Multiple Assembly Units
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Solution Overview
Problem
Existing optical inspection systems struggle to automatically generate a common measurement across multiple assembly units in real-time, leading to inefficiencies in quality control and defect detection.
Innovation Solution
The system retrieves images from multiple optical inspection stations, identifies serial numbers and positions of assembly units, and generates a virtual representation of the assembly line, allowing for real-time configuration and measurement across units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration and measurement methods are used for each assembly unit, then measurement precision can be maintained, but productivity is reduced due to time-consuming manual operations
Solution Approach 1:
The system performs preliminary actions by automatically capturing images of assembly units at multiple inspection stations, extracting serial numbers and configuration data, and pre-processing this information before measurement is actually needed. This preliminary data collection and organization eliminates the need for manual configuration during the measurement process, thereby increasing productivity without sacrificing precision.
Solution Approach 2:
The patent replaces manual mechanical configuration operations with an automated optical inspection system that uses cameras, image processing algorithms, and computer vision techniques to automatically capture, identify, and measure features of assembly units. This substitution of mechanical/manual processes with optical and computational methods dramatically reduces measurement time while maintaining or improving precision.
2Measurement precision
If multiple optical inspection stations are used to improve measurement coverage, then measurement precision increases, but device complexity increases due to coordination requirements
Solution Approach 1:
The patent implements a universal measurement system where a single control system manages multiple optical inspection stations, allowing each station to perform multiple functions including image capture, serial number identification, feature measurement, and data transmission. This multi-functionality reduces the need for separate specialized systems at each station, thereby improving measurement coverage and precision while managing system complexity through consolidation.
Solution Approach 2:
The system introduces an intermediary control system that acts as a mediator between multiple optical inspection stations and the central measurement system. This intermediary coordinates image data flow, synchronizes measurements across stations, and manages the integration of data from different sources, thereby enabling precise multi-point measurement while reducing the complexity burden on individual stations.
3Productivity
If real-time image processing is implemented across multiple stations, then productivity increases, but use of energy increases due to continuous computational operations
Solution Approach 1:
The system applies partial processing at each inspection station, where only the specific features and parameters relevant to that station's measurement scope are processed in real-time. Full image analysis and comprehensive measurement calculations are performed selectively based on detected features, rather than processing every pixel and parameter at every station continuously. This partial action approach maintains real-time productivity while reducing unnecessary computational energy consumption.
Data Source
AI summary
One variation of a method for automatically generating a common measurement across multiple assembly units includes: displaying a first image—recorded at an optical inspection station—within a user interface; receiving manual selection of a particular feature in a first assembly unit represented in the first image; receiving selection of a measurement type for the particular feature; extracting a first real dimension of the particular feature in the first assembly unit from the first image according to the measurement type; for each image in a set of images, identifying a feature—analogous to the particular feature—in an assembly unit represented in the image and extracting a real dimension of the feature in the assembly unit from the image according to the measurement type; and aggregating the first real dimension and a set of real dimensions extracted from the set of images into a digital container.