Component Mounter Luminance Optimization for Recognition Accuracy
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Solution Overview
Problem
Existing component mounting systems face reduced accuracy in component recognition due to improper luminance conditions, leading to incorrect judgments about component posture and suitability for mounting, despite the component being properly sucked and having a proper shape.
Innovation Solution
A recognition parameter optimization device and method that adjusts and optimizes the luminance-related condition by analyzing image data from a camera, combining brightness of the illuminator and threshold values, to ensure accurate component recognition and mounting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a luminance related condition is set in advance before component recognition, then the component recognition can be performed efficiently, but the accuracy of component recognition is reduced when the pre-set condition does not correspond to the actual component
Solution Approach 1:
The system performs preliminary component recognition using a default luminance related condition before actual mounting. Based on the results of this preliminary recognition, the system automatically optimizes and updates the luminance related condition for subsequent operations. This preliminary action allows the system to prepare appropriate recognition parameters in advance while maintaining the ability to adapt to actual component variations.
Solution Approach 2:
The system uses the results of component recognition as feedback to continuously optimize the luminance related condition. By analyzing whether components are correctly identified and recognized, the system adjusts the luminance parameters (brightness and threshold value) to improve recognition accuracy for future operations, creating a closed-loop optimization process.
2Measurement precision
If the luminance related condition is optimized to improve recognition accuracy, then fewer erroneous judgments occur, but additional processing time and computational resources are required
Solution Approach 1:
The system performs luminance condition optimization during idle periods or in parallel with other operations. By conducting optimization in advance and storing the optimized conditions for future use, the system minimizes the time impact on actual mounting operations while still achieving improved recognition accuracy.
Solution Approach 2:
The system automatically optimizes its own luminance related conditions without requiring external intervention or manual adjustment. The optimization process uses the recognition results themselves to self-adjust the parameters, eliminating the need for additional human time investment while improving accuracy.
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 optimization of luminance-related conditions based on image data improves the accuracy of component recognition, preventing erroneous judgments and ensuring proper mounting of components.
Implementation Method 1
obtained by imaging the component by a camera while irradiating light to the component from an illuminator
Data Source
AI summary
The image data obtained by imaging the component in the component recognition when the component mounter mounts the component on the board is stored in the storage, and the luminance related condition is optimized based on this image data. Therefore, a proper luminance related condition corresponding to the component to be actually mounted can be obtained.