CN-121974148-A - Digital sorting system

CN121974148ACN 121974148 ACN121974148 ACN 121974148ACN-121974148-A

Abstract

The invention discloses a digital sorting system, which relates to digital sorting, wherein before production begins, sorting parameters are set according to material characteristics of materials, sample wafers are sorted according to the sorting parameters, feeding distances and feeding routes are calculated and output in real time by adopting a center point grabbing strategy according to the sorting of the sample wafers, the sizes of the sample wafers and the working radius of a single-arm robot, the positions of grabbing actuators arranged at grabbing ends of the single-arm robot are controlled by rotation and movement of the single-arm robot, materials are grabbed and transferred from a material receiving table to a material discharging area according to the feeding routes, a grabbing path model is established according to historical path data of sample wafer grabbing in the material grabbing process, an optimal feeding route is optimally generated and output for the current grabbing path model according to external instructions or sorting information of residual materials, dynamic and intelligent sample wafer grabbing is realized, and the flexibility and the sorting efficiency and accuracy of sample wafer grabbing are improved.

Inventors

DAI YICHENG
CHEN HAO
ZHOU LUJIA
HUANG LEI

Assignees

杭州爱科科技股份有限公司

Dates

Publication Date: 20260505
Application Date: 20260122

Claims (10)

1. A digital sortation system, comprising: The feeding module is used for conveying the sample wafer which is cut in the cutting bed area to a feeding area of the material collecting table; The data classification module is used for classifying the sample wafer according to classification parameters corresponding to sample wafer characteristics of the sample wafer before production begins, and providing and outputting position information of a classification area for the sample wafer according to the classification parameters, wherein the material characteristics comprise at least one of geometric characteristics of the sample wafer, material characteristics of materials of the sample wafer and process characteristics of the sample wafer; The position output module is used for outputting the initial sample position of the receiving platform according to the position information of the feeding area and the classification area; The grabbing module is used for controlling the running state of a grabbing executor on the single-arm robot, and completing the action of grabbing or releasing when the single-arm robot reaches the position point of the material receiving table or the classification area, so as to grab and transfer the sample from the material receiving table to a blanking area; The path output module is connected with the grabbing module, the data classification module and the position output module and is used for combining historical path information, calculating in real time by adopting a center point grabbing strategy according to the classification of the sample, the size of the sample and the working radius of the single-arm robot, and outputting the feeding distance and the feeding route of the sample to the grabbing module; The path optimization module is connected with the path output module and is used for establishing a grabbing path model according to the grabbing historical path data and grabbing modes of the sample wafer of the grabbing module and optimizing the current grabbing path model to generate and output an optimal feeding route according to an external instruction or classification information of the residual sample wafer.
2. The digital sortation system of claim 1, further comprising a real-time collision detection model module coupled to said path output module for optimizing said feed route output by said path output module in conjunction with a real-time collision detection model.
3. The digital sorting system of claim 2, further comprising a self-matching classification module connected to the path optimization module, wherein the self-matching classification module is configured to compare the feature information of the sample acquired by the vision system with classification parameters of the sample, output a category to which the sample belongs to the sample, and perform balanced classification on the remaining samples according to the category to which the sample belongs, output classification parameters of a next sample, and control the classification parameters latest by the capturing module to capture the sample.
4. The digital sorting system according to claim 3, further comprising a maximum grasping amount path planning unit and a maximum area path planning unit, wherein the maximum area path planning unit is arranged in the path optimizing module and is used for calculating time and paths for moving all the samples to the blanking area according to the position information of the samples and the size information of the samples, the maximum grasping amount path planning unit is used for sorting according to the number of samples grasped at a time and calculating the optimal path for moving all the samples to the blanking area according to the position information of the samples and the size information of the materials.
5. The digital sorting system of claim 4, further comprising a counting module connected to the grabbing module and the feeding module, for counting a total number, a remaining number, and a gripping number of the samples in the feeding area of the receiving station, and sending a sample transmission request to the feeding module after the remaining number is zero, and controlling the cutting bed area to transmit the newly cut samples to the feeding area.
6. The digital sortation system of claim 5, further comprising an encoder feedback module disposed at said feed module for obtaining sample position information for said samples in real time and for transmitting said sample position information to said feed module.
7. The digital sortation system of any of claims 1-6, further comprising a pre-processing and dimension adaptation module coupled to said gripper module for detecting dimension information of said dailies and transmitting said dimension information to said gripper module, said gripper module replacing a gripper actuator that matches a dimension of said dailies after determining that said dailies are greater than a maximum grippable dimension of said gripper actuator.
8. The digital sortation system of claim 7, further comprising a spring buffer structure disposed at said gripper actuator of said gripper module, said gripper actuator being a suction cup array gripper actuator, said suction cup array gripper actuator being mounted to said single arm robot by said spring buffer structure.
9. The digital sortation system as recited in claim 8, wherein said single arm robot is a4 axis industrial robot or a 6 axis industrial robot.
10. The digital sortation system of claim 9, further comprising an out-of-range prevention sensor disposed at said receiving station for sending an alert signal to said feeding module upon detecting said dailies of said receiving station exceeding the confines of said feeding area, said out-of-range prevention sensor comprising at least one of an infrared correlation sensor, a laser reflection sensor, a vibration sensor, and an image recognition based sensor.

Description

Digital sorting system Technical Field The invention relates to the technical field of digital sorting, in particular to a digital sorting system. Background In the industries of composite materials, printing and packaging, and the like, sorting materials after cutting by a cutting bed is a key link of a production flow. At present, most enterprises still adopt a manual sorting mode, and the problems of high labor intensity, low sorting efficiency, easy error and the like exist. Currently, there are single-arm robotic sorting systems in the industry that employ PLC (programmable logic controller) and teach pendant based programming. The system forms a preset running program by recording a series of fixed space coordinates and action instructions in a teaching stage. In production, the robot exactly reproduces the preset tracks, and grabs and places the materials. The technical scheme realizes automation to a certain extent, but is rigid automation in nature. The working logic is completely dependent on the preset programming operation without external perception correction, and does not have the capability of self-optimization according to the real-time working condition. Therefore, the existing traditional sorting mode has the problems of low efficiency, high error rate, poor flexibility and the like, the traditional manual sorting or fixed program controlled sorting system has the problems of low efficiency, high error rate and insufficient flexibility, is difficult to adapt to the production requirements of multiple styles and small batches, has poor positioning precision in a complex sorting scene, and cannot be dynamically adjusted according to the characteristics of materials and the production requirements. Disclosure of Invention The invention aims to provide a digital sorting system which can realize dynamic adjustment and multifunctional sorting, optimize feeding, sorting, grabbing and blanking processes in real time according to material characteristics and production requirements, improve sorting efficiency and accuracy, and meet the requirements of industries such as composite materials, printing and packaging and the like on efficient, accurate and flexible sorting. In order to solve the above technical problems, an embodiment of the present invention provides a digital sorting system, including: The feeding module is used for conveying the sample wafer which is cut in the cutting bed area to a feeding area of the material collecting table; The data classification module is used for classifying the sample wafer according to classification parameters corresponding to sample wafer characteristics of the sample wafer before production begins, wherein the sample wafer characteristics comprise at least one of physical characteristics of the sample wafer, material characteristics of the sample wafer and process characteristics of the sample wafer; The position output module is used for outputting the initial sample position of the receiving platform according to the position information of the feeding area and the classification area; The grabbing module is used for controlling the running state of a grabbing executor on the single-arm robot, completing the actions of grabbing and releasing when the single-arm robot reaches the position points of the material receiving table and the classification area, and realizing grabbing and transferring the sample wafer from the material receiving table to the blanking area; the path output module is connected with the grabbing module, the data classification module and the position output module and is used for combining historical path information, calculating and outputting the feeding distance and the feeding route of the sample to the grabbing module in real time by adopting a center point grabbing strategy according to the classification of the sample, the size of the sample and the working radius of the single-arm robot; The path optimizing module is connected with the path output module and is used for establishing a grabbing path model according to the grabbing historical path data and grabbing modes of the sample wafer of the grabbing module, and optimizing the current grabbing path model according to the external instruction or the classification information of the residual sample wafer to generate and output an optimal feeding route. The system further comprises a real-time collision detection model module connected with the path output module, and the real-time collision detection model module is used for optimizing the feeding route output by the path output module by combining the real-time collision detection model. The system comprises a path optimizing module, a self-matching classifying module, a capturing module and a control module, wherein the path optimizing module is used for acquiring characteristic information of a sample through the path optimizing module, comparing the characteristic information with classifying parameters of the sa