Production-Line Image Inspection Learning Data Collection
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Solution Overview
Problem
Existing machine learning systems for image-based inspection on production lines require separate sensors for acquiring physical property information, leading to system complexity and increased costs, and lack general versatility.
Innovation Solution
A machine learning system that integrates image acquisition, preprocessing, and quality determination using a single camera, where inspection target site images are clipped based on setting files, and learning data is collected for a learning model using the same production line as inspection targets, without the need for additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate sensors are used to acquire physical property information, then measurement precision is improved, but device complexity increases and costs increase
Solution Approach 1:
The patent merges the image acquisition function and physical property information acquisition function into a single camera device. The camera captures both visual information and physical property data (such as temperature, humidity, or other environmental parameters) simultaneously, eliminating the need for separate sensors and reducing system complexity while maintaining measurement precision.
Solution Approach 2:
The camera is designed to perform multiple functions: it acts as both an image acquisition device and a physical property information acquisition device. This multi-functional approach allows the same device to collect both visual data and physical parameter data, reducing the overall number of components needed in the system.
2Measurement precision
If separate sensors are used to acquire physical property information, then measurement precision is improved, but manufacturing cost increases
Solution Approach 1:
By combining image acquisition and physical property information acquisition into a single camera, the patent reduces the total number of components that need to be manufactured and assembled. This integration lowers manufacturing costs while maintaining the capability to acquire both types of data with appropriate precision.
Solution Approach 2:
The multi-functional camera reduces bill of materials costs by eliminating redundant components. Instead of purchasing and installing separate sensors for physical property measurement, the system uses the camera's integrated capabilities, thereby reducing overall system cost while maintaining measurement precision.
3Measurement precision
If separate sensors are used to acquire physical property information, then measurement precision is improved, but system versatility decreases
Solution Approach 1:
The integrated camera system enhances versatility by providing a universal device that can perform both image acquisition and physical property measurement across different inspection scenarios. This multi-functional approach allows the same system to be adapted to various inspection tasks without requiring additional specialized sensors, thereby improving general versatility.
Data Source
AI summary
A machine learning system in the present disclosure includes: an image pickup unit that photographs a product and acquires a product image; a preprocessing unit that generates an inspection target site image by clipping an image of an inspection target site of the product based on a setting file, and saves the generated inspection target site image in an image saving unit; and an inspection processing unit that performs a quality determination process on the inspection target site image of a quality determination object indicated as a quality determination target by production instruction information, in which when the inspection target site image saved in the image saving unit is relevant to a product that is designated by the production instruction information as a learning object that is not the quality determination target, the inspection target site image is accumulated in the image saving unit, as learning data.