Adaptive Plug-In Depth Learning for Pin Insertion Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional plug-in equipment struggles to determine the correct plug-in depth for electronic components with pins of varying lengths or non-parallel arrangements, leading to potential deformation or breakage of pins during insertion.
Innovation Solution
A learning method for plug-in depth is introduced, where a robot arm and visual devices are used to identify pin and hole distances, allowing for continuous calibration of the insertion depth to achieve an ideal depth, thereby preventing pin damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed predetermined depth is used for insertion, then the insertion process is simple and fast, but pin damage occurs when pins have varying lengths or non-parallel arrangements
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed predetermined insertion depth to a dynamic adaptive depth. The system uses visual measurement to detect actual pin distances and hole distances, then dynamically adjusts the insertion depth based on the calculated difference. This allows the insertion depth to adapt to varying pin lengths and arrangements while maintaining high automation and productivity.
Solution Approach 2:
The patent implements feedback through a closed-loop system. Visual devices measure the actual pin distances and hole distances, the system calculates the required insertion depth based on these measurements, performs insertion, and uses the results to continuously optimize the insertion depth. This feedback mechanism ensures pin integrity while maintaining efficient production throughput.
2Reliability
If visual measurement and continuous calibration are implemented to achieve ideal insertion depth, then pin damage is avoided, but the process complexity and time consumption increase
Solution Approach 1:
The patent replaces complex mechanical measurement and adjustment systems with visual measurement technology. Instead of using mechanical gauges, fixtures, or manual measurement tools, the system uses visual devices (cameras or sensors) to measure pin distances and hole distances optically. This substitution reduces mechanical complexity while achieving precise insertion depth control.
Solution Approach 2:
The system performs self-measurement and self-adjustment using integrated visual devices and automated calculation. The measurement and calibration functions are built into the plug-in device itself, eliminating the need for separate external measurement equipment or manual calibration procedures. This self-service approach reduces overall system complexity.
3Manufacturing precision
If visual devices and continuous calibration are used, then ideal insertion depth is achieved, but the measurement and detection difficulty increases
Solution Approach 1:
The patent measures pin distances and hole distances in the horizontal plane (x-axis direction) rather than attempting direct vertical depth measurement. By measuring the horizontal distances between pins and between holes, and calculating the difference, the system indirectly determines the required insertion depth. This dimensional transformation simplifies the measurement task while achieving precise depth control.
Data Source
AI summary
The present application provides a learning method for plug-in depth including steps of: (a) utilizing a robot arm to take an electronic component with a plurality of pins; (b) utilizing a first visual device to identify a pin distance; (c) utilizing a second visual device to identify a hole distance; (d) inserting the plurality of pins into the corresponding plurality of holes with a predetermined depth according to the pin distance and the hole distance; (e) determining whether the plurality of pins are inserted into the plurality of holes, performing step (f) when the determination result is satisfied, and performing step (g) when the determination result is not satisfied; (f) recording the predetermined depth and performing the step (a) again; (g) calibrating the predetermined depth and performing the step (a) again; and (h) completing the learning of the plug-in depth after the step (f) is performed multiple times successively.