Component Mounting Image Compression for Memory Load Control
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Solution Overview
Problem
The existing component mounting systems face challenges in efficiently managing memory capacity and transmission loads due to the need to save high-quality image data for accurate image processing and cause analysis, while also requiring reduced data for visual checks after component mounting, leading to increased memory and transmission loads.
Innovation Solution
A component mounting device that uses a condition determining section and saving control section to save image data in either a lossless or lossy compression format based on the importance of the captured image, allowing for efficient use of memory capacity by adapting the compression format according to the specific requirements of the image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If image data is saved in high quality and high resolution format, then the information quantity and quality of image data are improved, but the memory capacity load and transmission load increase
Solution Approach 1:
The patent applies local quality by differentiating the quality requirements of different image data based on their usage scenarios. Image data used for adjustment of mounting work or image processing is saved in a first format with high quality and high resolution to maintain detailed information. Image data used for visual check is saved in a second format with lower quality to reduce memory load. This localized quality adjustment resolves the contradiction by matching data quality to specific functional needs rather than uniformly applying high quality to all image data.
Solution Approach 2:
The patent changes the parameter of image data quality (resolution, file size) based on the intended usage. By adjusting the quality parameter according to whether the image data is for adjustment purposes or visual checking, the system optimizes the balance between information retention and memory consumption. This parameter change allows the same image data to be stored in different quality levels, directly addressing the technical contradiction.
2Measurement precision
If image data is saved in high quality format for accurate image processing and cause analysis, then the measurement precision and manufacturing precision are improved, but the device complexity and transmission load increase
Solution Approach 1:
The patent segments image data into different categories based on usage: image data for adjustment (requiring high precision) and image data for visual check (requiring lower precision). By segmenting the data storage approach, the system manages complexity through organized categorization rather than treating all image data uniformly. This segmentation allows precise management of high-quality data only where needed, reducing overall system complexity.
Solution Approach 2:
The patent applies local quality by providing high measurement precision only for image data used in adjustment and analysis tasks, while using lower precision for visual check data. This localized approach to quality maintains accuracy where critical (for mounting work adjustment and cause analysis) while reducing complexity and transmission loads for non-critical applications.
3Loss of information
If all image data is saved in high resolution format, then the information quantity is improved, but the productivity and efficiency of the system decrease due to increased processing time
Solution Approach 1:
The patent changes the quality parameter of saved image data based on usage requirements. For image data used in adjustment and analysis, high resolution is maintained to preserve information quantity. For visual check data, lower resolution is acceptable, reducing processing time and improving productivity. This dynamic parameter adjustment resolves the contradiction between information retention and system efficiency.
Solution Approach 2:
The patent applies local quality by differentiating between image data that requires high information quantity (for adjustment and analysis) and image data where lower information quantity is sufficient (for visual check). This localized quality approach maintains productivity by avoiding unnecessary processing and storage of high-resolution data where it is not needed, while preserving information quality where critical.
Data Source
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AI summary
Component mounting system 1 includes electronic component mounting device 10, control device 100, image processing device 110, memory device 115, and display 120. Electronic component mounting device 10 includes mounting head 26, supply device 28, and component camera 90, and is configured to use mounting head 26 to pick up an electronic component supplied by supply device 28 and to image the held electronic component using component camera 90. When saving the captured image data on memory device 115, it is determined whether a condition for using a first format is satisfied (S1, S2). When the conditions for using the first format are satisfied (S2: yes), the captured image data is saved on memory device 115 in the first format that is a lossless compression format (S5). When conditions for using the first format are not satisfied (S2: no), the captured image data is saved on memory device 115 in the second format, which is a lossy compression format.