High-precision material taking method and system for die punching of mini LED circuit board

Abstract

The invention discloses a high-precision material taking method and system for die punching of a mini LED circuit board, and aims to solve the problems of inaccurate circuit board positioning, inaccurate suction force and clamping force adjustment and poor material taking stability. By integrating the visual recognition and positioning module, the intelligent control and adjustment module, the sensor feedback module and the automatic path planning module, high-precision automatic recognition, positioning and grabbing of the circuit board are achieved. The visual identification module scans the position, the shape and the size of the circuit board in real time and dynamically adjusts positioning errors, the intelligent control module automatically adjusts suction force and clamping force according to feedback data of a sensor, the circuit board is prevented from being damaged or improperly grabbed, the self-adaptive learning function is achieved, production data are analyzed in real time through the machine learning and optimization module, and the production efficiency is improved. And the operation strategy is optimized, and the material taking precision and efficiency are continuously improved. And through intelligent feedback control and an optimization algorithm, the automation level, the precision and the production efficiency of the production line are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of miniLED circuit board manufacturing technology, and in particular to a high-precision material extraction method and system for miniLED circuit board die punching. Background Art

[0002] During miniLED PCB production, positioning errors often occur, leading to inaccurate material handling. Especially during mass production, irregular shapes, uneven surfaces, or misaligned surfaces can lead to inaccurate material handling, impacting production efficiency and product quality. Traditional reclaiming systems often lack precise control over suction and clamping force when handling PCBs of varying sizes, shapes, and materials. Excessive suction can damage the PCB, while too weak suction prevents effective gripping. Excessive or insufficient clamping force can also affect the stability and accuracy of the PCB. Due to the highly diverse sizes, shapes, and material properties of miniLED PCBs, traditional reclaiming devices struggle to efficiently and accurately adapt to these diverse requirements. This is especially true when PCBs have irregular shapes or rough surfaces, making reclaiming systems often inadequately adaptable. Factors such as temperature, humidity, and material fluctuations in the production environment often cause PCBs to deform, warp, or shift during handling, impacting material handling accuracy. Manual adjustments make it difficult to adapt to these changes in real time. Summary of the Invention

[0003] A high-precision material extraction method for miniLED circuit board die punching includes the following steps: S1. Equipment and material preparation: Select a mold suitable for the size and shape of the miniLED circuit board, ensure the cutting accuracy and sharpness of the mold, regularly inspect the mold to ensure it is not worn or deformed, confirm the type and specifications of the miniLED circuit board material: PCB board, flexible circuit board, ensure that the material meets production requirements, inspect and debug the stamping equipment to ensure that the equipment is operating normally, and set appropriate stamping pressure, speed and other parameters; S2. High-Precision Positioning: A high-precision visual recognition system monitors the size and position of the circuit board in real time, quickly identifying its exact location. Sensors are used to detect positioning errors in real time, ensuring the board's position in the mold is always accurate. By analyzing and learning from changes in the board during production, the visual recognition system can dynamically adjust during production to continuously optimize positioning accuracy. If deviations occur, the system automatically corrects them. S3. Die-punching process: Adjust stamping parameters such as pressure, speed, and stroke depth for different materials, circuit board thicknesses, and specifications to reduce damage and inaccuracies caused by excessive impact. By fine-tuning the punching force and speed, and using machine learning algorithms to intelligently select the optimal stamping parameters based on real-time data for each circuit board (such as material, thickness, temperature, and humidity), the adaptive stamping process improves the flexibility and accuracy of the stamping process. When the punching of the circuit board is more complex, a step-by-step stamping method is adopted to gradually complete the die-punching operation, thereby ensuring the accuracy of each operation. S4. Automated Retrieving System: The automated retrieving system uses suction arms, robotic arms, and other automated equipment to accurately extract circuit boards from molds. The system utilizes an intelligent control system to automatically adjust suction and clamping force based on the position and shape of the circuit board to accommodate circuit boards of varying sizes and shapes, ensuring efficiency and accuracy in the retrieving process. S5. High-precision monitoring and feedback: During the stamping and retrieving process, the system uses sensors and visual inspection equipment to monitor the accuracy of each circuit board in real time. The monitoring system can detect any potential deviations and provide immediate feedback to the control system to ensure operational accuracy. If position errors or poor stamping are detected, the system will automatically make adjustments to ensure that subsequent operations are not affected. S6. Fine post-processing: After stamping, the edges of the circuit board are deburred to ensure that there is no damage or burrs that affect subsequent assembly. After the board is taken out, it is cleaned to remove any impurities or oil residue on the surface to ensure that the surface of the circuit board is smooth and free of substances that affect welding and other subsequent processes. S7. Quality Inspection and Rejection of Defective Products: After removing the printed circuit boards, the size and hole positions are inspected to ensure they meet the design requirements. High-precision inspection is performed using laser measurement and CCD visual inspection technology. The circuit boards are also tested for electrical functionality to ensure they will not have any problems in subsequent use. Any problematic circuit boards found during inspection will be rejected by the automated system to prevent unqualified products from entering the subsequent production line. S8. Overall optimization and production efficiency improvement: According to different production requirements, the system can automatically adjust the stamping parameters and material collection methods to accommodate circuit boards of different specifications and shapes, thereby improving overall production flexibility.

[0004] Furthermore, a high-precision material extraction method for miniLED circuit board die punching is provided. In step S2, sensors are used to detect the positioning error of the circuit board in real time. By real-time analysis and learning of changes in the circuit board during the production process, the visual recognition system makes dynamic adjustments during the production process to continuously optimize the positioning accuracy. The specific steps are as follows; S21. Sensor Placement: High-precision sensors are used to monitor PCB positioning errors in real time, capturing key data such as PCB position, angle, and tilt. Sensors are installed in key locations, such as where PCBs enter and exit the mold, and in the reclaim area, to ensure comprehensive monitoring of PCB position changes throughout the production process. S22. Parameter Setting: Based on the size, shape, and characteristics of the circuit board, set the initial parameters of the visual recognition system, including the camera's resolution, exposure, focal length, and image processing algorithm, to ensure the system can clearly identify the circuit board's location. S23. Real-time Monitoring and Error Detection: The visual recognition system and sensors work synchronously to collect real-time position data of the circuit board. The sensors continuously monitor the actual position of the circuit board and compare it with the desired position. By calculating the error between the actual position and the target position, the board's offset is detected. Positioning errors include positional errors (such as displacement deviation) and angular errors (such as rotational deviation). S24. Data Analysis and Error Correction: Sensor data is integrated and analyzed with data fed back by the vision system to construct a more accurate PCB position model. The least squares method, a data processing algorithm, is used to eliminate noise and improve positioning accuracy. Based on the detected errors, an algorithm is used to calculate the required correction values. These correction instructions are then transmitted to the production line control system, which automatically adjusts the PCB's position, corrects errors, and ensures the PCB maintains its precise position within the mold. S25. Dynamic Adjustment: During the production process, the system requires real-time feedback and adjustment. Through dual monitoring by sensors and vision systems, when the position of the circuit board deviates from the set value, the operating parameters are immediately adjusted, such as adjusting the position of the material handling robot arm and changing the motion trajectory of the stamping die. S26. Collaborative work and automated adjustment: When it is detected that the positioning error of the circuit board exceeds the predetermined threshold, the automation system will perform corrective operations: automatically adjust the position of the robotic arm and the suction arm to ensure that the circuit board can be accurately grasped, and enable the visual recognition system, sensor system and automation equipment to work together. When the sensor detects a position error of the circuit board, the visual system will compare the image data of the circuit board, automatically correct the deviation and send adjustment instructions to the mechanical equipment on the production line to avoid delays and errors in human operation.

[0005] Furthermore, a high-precision material extraction method for miniLED circuit board die punching is provided. In step S4, the material picking system automatically adjusts the suction and clamping force according to the position and shape of the circuit board through the intelligent control system to adapt to circuit boards of different sizes and shapes, as follows; S41. Detection and recognition of circuit board position and shape: Using 3D sensors (such as laser scanning and stereo vision), the specific position, size, and shape of the circuit board are scanned. The vision system must identify the circuit board's outline, locate its center, edges, and key corner features, and automatically calculate the length, width, thickness, and any possible deformation, such as bending and warping, of the circuit board. This data is then transmitted to the intelligent control system. S42. Intelligent Adjustment of Suction and Clamping Force: The suction cup's suction force is automatically adjusted based on the material, size, and shape of the circuit board. Smaller, thinner circuit boards require less suction force to avoid damage caused by excessive suction. Larger, thicker circuit boards require stronger suction force to ensure reliable gripping. A pressure sensor monitors the suction cup's suction force in real time and automatically adjusts it based on the circuit board's surface characteristics, such as flatness and smoothness. A PID control algorithm is used to precisely adjust the suction force, continuously monitoring feedback data and adjusting the suction output to achieve the optimal value. For irregularly shaped circuit boards that require additional fixturing, a clamping robot or gripper system is used for auxiliary gripping. The intelligent control system automatically adjusts the clamping force based on the size, shape, weight, and other information of the circuit board. The clamping force is monitored by a force sensor to ensure that the clamping force can firmly grasp the circuit board without damaging it. S43. Monitoring and Adjusting PCB Status: Real-time monitoring of PCB position, clamping force, and suction status ensures optimal operation. If a PCB is detected to be offset, tilted, or unstable during the retrieving process, the intelligent control system immediately issues adjustment instructions, using the visual recognition system to reposition the PCB and adjust suction and clamping force to ensure stable gripping. S44. Automated path planning and adjustment: After the circuit board is sucked in, the intelligent control system uses a path planning algorithm to determine the optimal material picking path and calculates the motion trajectory of the robotic arm. According to the shape and size of the circuit board, the system optimizes the path to avoid excessive movement and collisions. The system adjusts the path planning in real time according to the actual shape and position of the circuit board to ensure a smooth and efficient material picking process. When there are protrusions or damage on the edge of the circuit board, the path planning system will avoid collisions to ensure smooth material picking. During the material picking process, the system will continuously detect the position and shape of the circuit board, and dynamically adjust the speed, angle and movement mode of the material picking robotic arm based on the feedback.

[0006] Furthermore, a high-precision material extraction method for miniLED circuit board die punching is provided. Specifically, in step S43, the circuit board is repositioned and the suction and clamping forces are adjusted by the visual recognition system. The automated process for adjusting the suction and clamping forces is as follows: S431. Data Input and Parameter Setting: The size, shape, and material information of the circuit board are transmitted to the intelligent control system as initial parameters for adjusting suction and clamping force. The intelligent system sets appropriate suction and clamping force based on the different characteristics of the circuit board (such as smooth, rough, or porous surface). S432. Suction Force Adjustment: The control system uses feedback sensors to adjust the suction force of the suction cup in real time. Based on the shape and material of the circuit board, the intelligent control system dynamically adjusts the suction force. For smooth circuit board surfaces, the suction force is reduced to avoid excessive suction. For rough or porous surfaces, the suction force is automatically increased to ensure a secure hold. S433. Clamping force adjustment: For irregularly shaped circuit boards, the control system monitors the clamping force through force sensors to ensure that the clamping device grasps the circuit board with appropriate force. During the clamping process, the force of the clamping arm will be dynamically adjusted according to the edge shape of the circuit board and the actual situation.

[0007] A miniLED circuit board die punching high-precision material picking system, the miniLED circuit board die punching high-precision material picking system is used to implement any miniLED circuit board die punching high-precision material picking method; the miniLED circuit board die punching high-precision material picking system includes: Visual recognition and positioning module: Scans the position, size, and shape of the circuit board using a high-definition camera or 3D sensor, and uses image processing algorithms to accurately identify the positioning error of the circuit board based on the acquired image data; Intelligent control and adjustment module: Automatically adjusts suction and clamping force based on real-time data of the circuit board: position, shape, size, surface characteristics, to ensure precise gripping and positioning, including a control system that automatically adjusts suction force of the suction cup and clamping force of the gripper; Automated material handling and gripping module: The robotic arm and suction device are responsible for grabbing the miniLED circuit board from the mold. The module needs to dynamically adjust the gripping method, gripping path, speed, and gripping force based on the visual system and sensor feedback; Dynamic adjustment and feedback control module: Through the feedback control system, the material picking action and clamping force are adjusted in real time, including error correction, clamping force adjustment and position feedback; Path planning and motion control module: Based on the real-time position and shape data of the circuit board, it plans the optimal material picking path and controls the motion trajectory of the robotic arm and the picking device; Quality monitoring and verification module: During the material picking and handling process, the quality of the circuit boards is monitored in real time to ensure that each circuit board is not damaged or has position deviation during operation, including visual inspection and force feedback quality control.

[0008] Beneficial effects of the present invention: By introducing the visual recognition and positioning module, the system can accurately identify the position, shape and size of the circuit board, and adjust and correct the positioning error of the circuit board in real time. The system can effectively avoid material picking errors caused by inaccurate positioning and improve the accuracy of material picking. It reduces the positioning error of the circuit board, improves the stability of production, reduces the scrap rate and rework rate, and ensures that each operation meets the quality standards. Through the intelligent control and adjustment module, according to the real-time data of the circuit board, the system can automatically adjust the suction and clamping force to ensure that the circuit board can be safely grasped without damage or displacement. The system can dynamically adjust according to different circuit board materials, sizes, and shapes, improve the material picking accuracy, and reduce damage to the circuit board, especially for fragile and surface-sensitive miniLED circuit boards, to ensure high-precision operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 This is a flow chart of a method for high-precision material extraction for miniLED circuit board die punching; DETAILED DESCRIPTION

[0010] A high-precision material extraction method for miniLED circuit board die punching includes the following steps: S1. Equipment and material preparation: Select a mold suitable for the size and shape of the miniLED circuit board, ensure the cutting accuracy and sharpness of the mold, regularly inspect the mold to ensure it is not worn or deformed, confirm the type and specifications of the miniLED circuit board material: PCB board, flexible circuit board, ensure that the material meets production requirements, inspect and debug the stamping equipment to ensure that the equipment is operating normally, and set appropriate stamping pressure, speed and other parameters; S2. High-Precision Positioning: A high-precision visual recognition system monitors the size and position of the circuit board in real time, quickly identifying its exact location. Sensors are used to detect positioning errors in real time, ensuring the board's position in the mold is always accurate. By analyzing and learning from changes in the board during production, the visual recognition system can dynamically adjust during production to continuously optimize positioning accuracy. If deviations occur, the system automatically corrects them. S3. Die-punching process: Adjust stamping parameters such as pressure, speed, and stroke depth for different materials, circuit board thicknesses, and specifications to reduce damage and inaccuracies caused by excessive impact. By fine-tuning the punching force and speed, and using machine learning algorithms to intelligently select the optimal stamping parameters based on real-time data for each circuit board (such as material, thickness, temperature, and humidity), the adaptive stamping process improves the flexibility and accuracy of the stamping process. When the punching of the circuit board is more complex, a step-by-step stamping method is adopted to gradually complete the die-punching operation, thereby ensuring the accuracy of each operation. S4. Automated Retrieving System: The automated retrieving system uses suction arms, robotic arms, and other automated equipment to accurately extract circuit boards from molds. The system utilizes an intelligent control system to automatically adjust suction and clamping force based on the position and shape of the circuit board to accommodate circuit boards of varying sizes and shapes, ensuring efficiency and accuracy in the retrieving process. S5. High-precision monitoring and feedback: During the stamping and retrieving process, the system uses sensors and visual inspection equipment to monitor the accuracy of each circuit board in real time. The monitoring system can detect any potential deviations and provide immediate feedback to the control system to ensure operational accuracy. If position errors or poor stamping are detected, the system will automatically make adjustments to ensure that subsequent operations are not affected. S6. Fine post-processing: After stamping, the edges of the circuit board are deburred to ensure that there is no damage or burrs that affect subsequent assembly. After the board is taken out, it is cleaned to remove any impurities or oil residue on the surface to ensure that the surface of the circuit board is smooth and free of substances that affect welding and other subsequent processes. S7. Quality Inspection and Rejection of Defective Products: After removing the printed circuit boards, the size and hole positions are inspected to ensure they meet the design requirements. High-precision inspection is performed using laser measurement and CCD visual inspection technology. The circuit boards are also tested for electrical functionality to ensure they will not have any problems in subsequent use. Any problematic circuit boards found during inspection will be rejected by the automated system to prevent unqualified products from entering the subsequent production line. S8. Overall optimization and production efficiency improvement: According to different production requirements, the system can automatically adjust the stamping parameters and material collection methods to accommodate circuit boards of different specifications and shapes, thereby improving overall production flexibility.

[0011] Furthermore, a high-precision material extraction method for miniLED circuit board die punching is provided. In step S2, sensors are used to detect the positioning error of the circuit board in real time. By real-time analysis and learning of changes in the circuit board during the production process, the visual recognition system makes dynamic adjustments during the production process to continuously optimize the positioning accuracy. The specific steps are as follows; S21. Sensor Placement: High-precision sensors are used to monitor PCB positioning errors in real time, capturing key data such as PCB position, angle, and tilt. Sensors are installed in key locations, such as where PCBs enter and exit the mold, and in the reclaim area, to ensure comprehensive monitoring of PCB position changes throughout the production process. S22. Parameter Setting: Based on the size, shape, and characteristics of the circuit board, set the initial parameters of the visual recognition system, including the camera's resolution, exposure, focal length, and image processing algorithm, to ensure the system can clearly identify the circuit board's location. S23. Real-time Monitoring and Error Detection: The visual recognition system and sensors work synchronously to collect real-time position data of the circuit board. The sensors continuously monitor the actual position of the circuit board and compare it with the desired position. By calculating the error between the actual position and the target position, the board's offset is detected. Positioning errors include positional errors (such as displacement deviation) and angular errors (such as rotational deviation). S24. Data Analysis and Error Correction: Sensor data is integrated and analyzed with data fed back by the vision system to construct a more accurate PCB position model. The least squares method, a data processing algorithm, is used to eliminate noise and improve positioning accuracy. Based on the detected errors, an algorithm is used to calculate the required correction values. These correction instructions are then transmitted to the production line control system, which automatically adjusts the PCB's position, corrects errors, and ensures the PCB maintains its precise position within the mold. S25. Dynamic Adjustment: During the production process, the system requires real-time feedback and adjustment. Through dual monitoring by sensors and vision systems, when the position of the circuit board deviates from the set value, the operating parameters are immediately adjusted, such as adjusting the position of the material handling robot arm and changing the motion trajectory of the stamping die. S26. Collaborative work and automated adjustment: When it is detected that the positioning error of the circuit board exceeds the predetermined threshold, the automation system will perform corrective operations: automatically adjust the position of the robotic arm and the suction arm to ensure that the circuit board can be accurately grasped, and enable the visual recognition system, sensor system and automation equipment to work together. When the sensor detects a position error of the circuit board, the visual system will compare the image data of the circuit board, automatically correct the deviation and send adjustment instructions to the mechanical equipment on the production line to avoid delays and errors in human operation.

[0012] Furthermore, a high-precision material extraction method for miniLED circuit board die punching is provided. In step S4, the material picking system automatically adjusts the suction and clamping force according to the position and shape of the circuit board through the intelligent control system to adapt to circuit boards of different sizes and shapes, as follows; S41. Detection and recognition of circuit board position and shape: Using 3D sensors (such as laser scanning and stereo vision), the specific position, size, and shape of the circuit board are scanned. The vision system must identify the circuit board's outline, locate its center, edges, and key corner features, and automatically calculate the length, width, thickness, and any possible deformation, such as bending and warping, of the circuit board. This data is then transmitted to the intelligent control system. S42. Intelligent Adjustment of Suction and Clamping Force: The suction cup's suction force is automatically adjusted based on the material, size, and shape of the circuit board. Smaller, thinner circuit boards require less suction force to avoid damage caused by excessive suction. Larger, thicker circuit boards require stronger suction force to ensure reliable gripping. A pressure sensor monitors the suction cup's suction force in real time and automatically adjusts it based on the circuit board's surface characteristics, such as flatness and smoothness. A PID control algorithm is used to precisely adjust the suction force, continuously monitoring feedback data and adjusting the suction output to achieve the optimal value. For irregularly shaped circuit boards that require additional fixturing, a clamping robot or gripper system is used for auxiliary gripping. The intelligent control system automatically adjusts the clamping force based on the size, shape, weight, and other information of the circuit board. The clamping force is monitored by a force sensor to ensure that the clamping force can firmly grasp the circuit board without damaging it. S43. Monitoring and Adjusting PCB Status: Real-time monitoring of PCB position, clamping force, and suction status ensures optimal operation. If a PCB is detected to be offset, tilted, or unstable during the retrieving process, the intelligent control system immediately issues adjustment instructions, using the visual recognition system to reposition the PCB and adjust suction and clamping force to ensure stable gripping. S44. Automated path planning and adjustment: After the circuit board is sucked in, the intelligent control system uses a path planning algorithm to determine the optimal material picking path and calculates the motion trajectory of the robotic arm. According to the shape and size of the circuit board, the system optimizes the path to avoid excessive movement and collisions. The system adjusts the path planning in real time according to the actual shape and position of the circuit board to ensure a smooth and efficient material picking process. When there are protrusions or damage on the edge of the circuit board, the path planning system will avoid collisions to ensure smooth material picking. During the material picking process, the system will continuously detect the position and shape of the circuit board, and dynamically adjust the speed, angle and movement mode of the material picking robotic arm based on the feedback.

[0013] Furthermore, a high-precision material extraction method for miniLED circuit board die punching is provided. In the specific step S43, the circuit board is repositioned and the suction and clamping forces are adjusted by the visual recognition system. The automated process of adjusting the suction and clamping forces is as follows: S431. Data Input and Parameter Setting: The size, shape, and material information of the circuit board are transmitted to the intelligent control system as initial parameters for adjusting suction and clamping force. The intelligent system sets appropriate suction and clamping force based on the different characteristics of the circuit board (such as smooth, rough, or porous surface). S432. Suction Force Adjustment: The control system uses feedback sensors to adjust the suction force of the suction cup in real time. Based on the shape and material of the circuit board, the intelligent control system dynamically adjusts the suction force. For smooth circuit board surfaces, the suction force is reduced to avoid excessive suction. For rough or porous surfaces, the suction force is automatically increased to ensure a secure hold. S433. Clamping force adjustment: For irregularly shaped circuit boards, the control system monitors the clamping force through force sensors to ensure that the clamping device grasps the circuit board with appropriate force. During the clamping process, the force of the clamping arm will be dynamically adjusted according to the edge shape of the circuit board and the actual situation.

[0014] A miniLED circuit board die punching high-precision material picking system, the miniLED circuit board die punching high-precision material picking system is used to implement any miniLED circuit board die punching high-precision material picking method; the miniLED circuit board die punching high-precision material picking system includes: Visual recognition and positioning module: Scans the position, size, and shape of the circuit board using a high-definition camera or 3D sensor, and uses image processing algorithms to accurately identify the positioning error of the circuit board based on the acquired image data; Intelligent control and adjustment module: Automatically adjusts suction and clamping force based on real-time data of the circuit board: position, shape, size, surface characteristics, to ensure precise gripping and positioning, including a control system that automatically adjusts suction force of the suction cup and clamping force of the gripper; Automated material handling and gripping module: The robotic arm and suction device are responsible for grabbing the miniLED circuit board from the mold. The module needs to dynamically adjust the gripping method, gripping path, speed, and gripping force based on the visual system and sensor feedback; Dynamic adjustment and feedback control module: Through the feedback control system, the material picking action and clamping force are adjusted in real time, including error correction, clamping force adjustment and position feedback; Path planning and motion control module: Based on the real-time position and shape data of the circuit board, it plans the optimal material picking path and controls the motion trajectory of the robotic arm and the picking device; Quality monitoring and verification module: During the material picking and handling process, the quality of the circuit boards is monitored in real time to ensure that each circuit board is not damaged or has position deviation during operation, including visual inspection and force feedback quality control.

Claims

1. A high-precision die-punching method for miniLED circuit boards, characterized in that: The following steps are included: S1. Equipment and material preparation: Select a mold suitable for the size and shape of the miniLED circuit board, ensure the cutting accuracy and sharpness of the mold, inspect the mold regularly, confirm the type and specifications of the miniLED circuit board materials: PCB board, flexible circuit board, inspect and debug the stamping equipment to ensure the equipment is operating normally, and set the appropriate stamping pressure and speed parameters; S2. High-Precision Positioning: A high-precision visual recognition system monitors the size and position of circuit boards in real time, quickly identifying their exact location. Sensors are used to detect positioning errors in real time. By analyzing and learning from changes in the circuit boards during production, the visual recognition system dynamically adjusts during production to continuously optimize positioning accuracy. If deviations occur, the system automatically corrects them. S3. Die-punching process: Adjust stamping parameters such as pressure, speed, and stroke depth for different materials, circuit board thicknesses, and specifications to reduce damage and inaccuracies caused by excessive impact. By fine-tuning the punching force and speed, and using machine learning algorithms to intelligently select the optimal stamping parameters based on each circuit board's real-time data: material, thickness, temperature, and humidity. The adaptive stamping process improves the flexibility and accuracy of the stamping process. When the punching of the circuit board is more complex, a step-by-step stamping method is adopted to gradually complete the die-punching operation, thereby ensuring the accuracy of each operation. S4. Automated Retrieving System: The automated retrieving system uses suction arms, robotic arms, and other automated equipment to accurately extract circuit boards from molds. The system utilizes an intelligent control system to automatically adjust suction and clamping force based on the position and shape of the circuit board to accommodate circuit boards of varying sizes and shapes, ensuring efficiency and accuracy in the retrieving process. S5. High-precision monitoring and feedback: During the stamping and retrieving processes, the system uses sensors and visual inspection equipment to monitor the accuracy of each circuit board in real time. The monitoring system can detect any potential deviations and provide immediate feedback to the control system. If it detects position errors or poor stamping of the circuit board, it will automatically make adjustments to ensure that subsequent operations are not affected. S6. Fine post-processing: Deburr the edges of the circuit board after stamping, clean the circuit board after taking out the material, remove the impurities or oil stains on the surface, and make sure there are no substances that affect welding and other subsequent processes; S7. Quality Inspection and Rejection of Defective Products: After the PCB is taken, its dimensions and hole positions are inspected. High-precision inspection is performed using laser measurement and CCD visual inspection technology. The PCB is also tested for electrical functionality. Any defective PCBs found during inspection are automatically rejected by the automated system to prevent defective products from entering the subsequent production line. S8. Overall optimization and production efficiency improvement: According to different production requirements, the system can automatically adjust the stamping parameters and material collection methods to accommodate circuit boards of different specifications and shapes, thereby improving overall production flexibility.

2. A high-precision die-punching method for miniLED circuit boards as claimed in claim 1, characterized in that: In step S2, sensors are used to detect the positioning error of the circuit board in real time. By real-time analysis and learning of changes in the circuit board during the production process, the visual recognition system is dynamically adjusted during the production process to continuously optimize the positioning accuracy. The specific steps are as follows; S21. Sensor Placement: High-precision sensors are used to monitor PCB positioning errors in real time, capturing key data such as PCB position, angle, and tilt. Sensors are installed in key locations, such as where PCBs enter and exit the mold, and in the reclaim area, to comprehensively monitor PCB position changes throughout the production process. S22. Parameter Setting: Based on the size, shape, and characteristics of the circuit board, set the initial parameters of the visual recognition system, including the camera's resolution, exposure, focal length, and image processing algorithm, to clearly identify the position of the circuit board. S23. Real-time Monitoring and Error Detection: The visual recognition system and sensors work synchronously to collect real-time position data of the circuit board. The sensors continuously monitor the actual position of the circuit board and compare it with the desired position. By calculating the error between the actual position and the target position, the board's offset is detected. Positioning errors include position error (displacement deviation) and angular error (rotational deviation). S24. Data Analysis and Error Correction: Sensor data is integrated and analyzed with data fed back by the vision system to construct a more accurate PCB position model. The least squares method, a data processing algorithm, is used to eliminate noise and improve positioning accuracy. Based on the detected errors, an algorithm is used to calculate the required correction values. These correction instructions are then transmitted to the production line control system, which automatically adjusts the PCB's position, corrects errors, and ensures the PCB maintains its precise position within the mold. S25. Dynamic Adjustment: During the production process, the system requires real-time feedback and adjustment. Through dual monitoring by sensors and vision systems, when the position of the circuit board deviates from the set value, the operating parameters are immediately adjusted, such as adjusting the position of the material handling robot arm and changing the motion trajectory of the stamping die. S26. Collaborative work and automated adjustment: When it is detected that the positioning error of the circuit board exceeds the predetermined threshold, the automation system will perform corrective operations: automatically adjust the position of the robotic arm and the suction arm to ensure that the circuit board can be accurately grasped, and enable the visual recognition system, sensor system and automation equipment to work together. When the sensor detects a position error of the circuit board, the visual system will compare the image data of the circuit board, automatically correct the deviation and send adjustment instructions to the mechanical equipment on the production line to avoid delays and errors in human operation.

3. A high-precision die-punching method for miniLED circuit boards as claimed in claim 1, characterized in that: In step S4, the material picking system automatically adjusts the suction and clamping force according to the position and shape of the circuit board through the intelligent control system to adapt to circuit boards of different sizes and shapes, as follows; S41. Detection and recognition of circuit board position and shape: Utilizing 3D sensors and laser scanning to identify the specific position, size, and shape of the circuit board, a vision system identifies the circuit board's contours, locates key features such as its center, edges, and corners, and automatically calculates the length, width, thickness, and any possible deformations such as bending and warping, transmitting this data to the intelligent control system. S42. Intelligent Adjustment of Suction and Clamping Force: The suction cup's suction force is automatically adjusted based on the PCB's material, size, and shape. A pressure sensor monitors the suction force in real time and automatically adjusts the force based on the PCB's surface characteristics, such as flatness and smoothness. A PID control algorithm is used to precisely adjust the suction force, continuously monitoring feedback data and adjusting the suction output to achieve the optimal value. For irregularly shaped PCBs that require additional fixturing, a gripping robot and a gripper system are used for auxiliary gripping. The intelligent control system automatically adjusts the gripping force based on the PCB's size, shape, and weight, and the gripping force is monitored by a force sensor. S43. Monitoring and Adjusting PCB Status: Real-time monitoring of PCB position, clamping force, and suction status ensures optimal operation. If a PCB is detected to be offset, tilted, or unstable during the retrieving process, the intelligent control system immediately issues adjustment instructions, using the visual recognition system to reposition the PCB and adjust suction and clamping force to ensure stable gripping. S44. Automated path planning and adjustment: After the circuit board is sucked in, the intelligent control system uses a path planning algorithm to determine the optimal material picking path and calculates the motion trajectory of the robotic arm. According to the shape and size of the circuit board, the system optimizes the path to avoid excessive movement and collisions. The system adjusts the path planning in real time according to the actual shape and position of the circuit board to ensure a smooth and efficient material picking process. When there are protrusions or damage on the edge of the circuit board, the path planning system will avoid collisions to ensure smooth material picking. During the material picking process, the system will continuously detect the position and shape of the circuit board, and dynamically adjust the speed, angle and movement mode of the material picking robotic arm based on the feedback.

4. A high-precision die-punching method for miniLED circuit boards as claimed in claim 1, characterized in that: Specifically, in step S43, the circuit board is repositioned and the suction and clamping forces are adjusted by the visual recognition system. The automated process for adjusting the suction and clamping forces is as follows: S431. Data Input and Parameter Setting: The size, shape, and material information of the circuit board are transmitted to the intelligent control system as initial parameters for adjusting suction and clamping force. The intelligent system sets appropriate suction and clamping force based on the different characteristics of the circuit board, such as smooth, rough, or porous surfaces. S432. Suction Force Adjustment: The control system uses feedback sensors to adjust the suction force of the suction cup in real time. Based on the shape and material of the circuit board, the intelligent control system dynamically adjusts the suction force. For smooth circuit board surfaces, the suction force is reduced to avoid excessive suction. For rough or porous surfaces, the suction force is automatically increased to ensure a secure hold. S433. Clamping force adjustment: For irregularly shaped circuit boards, the control system monitors the clamping force through force sensors to ensure that the clamping device grasps the circuit board with appropriate force. During the clamping process, the force of the clamping arm will be dynamically adjusted according to the edge shape of the circuit board and the actual situation.

5. A high-precision material extraction system for miniLED circuit board die punching, characterized in that: The miniLED circuit board die punching high-precision material picking system is used to implement the miniLED circuit board die punching high-precision material picking method according to any one of claims 1 to 4; the miniLED circuit board die punching high-precision material picking system comprises: Visual recognition and positioning module: uses high-definition cameras and 3D sensors to scan the position, size, and shape of the circuit board. Based on the acquired image data, image processing algorithms are used to accurately identify the positioning error of the circuit board. Intelligent control and adjustment module: Automatically adjusts suction and clamping force based on real-time data of the circuit board: position, shape, size, surface characteristics, to ensure precise gripping and positioning, including a control system that automatically adjusts suction force of the suction cup and clamping force of the gripper; Automated material handling and gripping module: The robotic arm and suction device are responsible for grabbing the miniLED circuit board from the mold. The module dynamically adjusts the gripping method, gripping path, speed and gripping force based on the visual system and sensor feedback; Dynamic adjustment and feedback control module: Through the feedback control system, the material picking action and clamping force are adjusted in real time, including error correction, clamping force adjustment and position feedback; Path planning and motion control module: Based on the real-time position and shape data of the circuit board, it plans the optimal material picking path and controls the motion trajectory of the robotic arm and the picking device; Quality monitoring and verification module: During the material picking and handling process, the quality of the circuit boards is monitored in real time to ensure that each circuit board is not damaged or has position deviation during operation, including visual inspection and force feedback quality control.

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