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LED chip mounter pick-and-paste path optimization method based on hybrid genetic algorithm

A hybrid genetic algorithm and LED placement machine technology, applied in the field of electrical technology and electrical engineering, can solve the problems of low LED patch production work efficiency, long pick-up and placement path, limited search ability, etc., and achieve optimal allocation and path problems. The method is fast and effective, improving production efficiency, and the effect of large search space

Active Publication Date: 2020-07-31
宁波智能装备研究院有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0025] The purpose of the present invention is to solve the problem that the current commercial software adopts a fixed optimization strategy, which has limited search ability for feasible solutions, resulting in long pick-up path and low efficiency of LED patch production, and proposes a hybrid genetic algorithm-based Optimizing method for pick-and-place path of LED pick-and-place machine

Method used

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  • LED chip mounter pick-and-paste path optimization method based on hybrid genetic algorithm
  • LED chip mounter pick-and-paste path optimization method based on hybrid genetic algorithm
  • LED chip mounter pick-and-paste path optimization method based on hybrid genetic algorithm

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specific Embodiment approach 1

[0042] Specific implementation mode one: the specific process of a method for optimizing the pick-and-place path of LED placement machine based on hybrid genetic algorithm in this implementation mode is as follows:

[0043] Step 1. Preparatory work before production, importing machine parameters and PCB data file information;

[0044] Step 2. According to the machine parameters determined in step 1 and the PCB data file information, determine the feeder slot allocation position that makes the placement head move the shortest distance;

[0045] Step 3. Plan the pick-and-place path of the parallel chip mounter, use the midpoint of the feeder slot allocation determined in step 2 as the starting point and end point of the pick-and-place path optimization, use the hybrid genetic algorithm to search for a feasible solution to the pick-and-place path, and keep The solution with the shortest mounting path;

[0046] Step 4: Output the solution with the shortest mounting path found in st...

specific Embodiment approach 2

[0048] Specific embodiment two: the difference between this embodiment and specific embodiment one is: the preparatory work before production in described step one, import machine parameter and PCB data file information; Concrete process is:

[0049] Step 11: Import the coordinate information of the mounting point;

[0050] Before the pick and place optimization of the placement machine, it is necessary to import the production data information in advance, that is, the PCB data file. The PCB data file contains information such as component name, component type, X-axis and Y-axis coordinates of the component;

[0051] It is stipulated that when the operator is facing the machine, the lower left corner of the PCB circuit board is the reference origin, and the right and front of the operator are the growth directions of the X-axis and Y-axis respectively, Cp x (c) indicates the X-axis coordinates of component c relative to the reference origin, Cp y (c) indicates the Y-axis coor...

specific Embodiment approach 3

[0055] Specific embodiment three: the difference between this embodiment and specific embodiments one to two is: in the second step, according to the machine parameters determined in the step one and the PCB data file information, determine the feeder slot that makes the placement head move the shortest distance Assign location; the specific process is:

[0056] Step 21: Calculate the average coordinates of the components to be picked and pasted:

[0057] aveCp x =[Cp x (1)+Cp x (2)+…+Cp x (numCp)] / numCp,

[0058] In the formula, aveCp x is the average coordinate of the component to be picked; Cp x (1) Indicates the X-axis coordinates of component 1 relative to the reference origin; Cp x (numCp) represents the X-axis coordinates of the element numCp relative to the reference origin;

[0059] Step 22: Calculate the slot number corresponding to the center position of the feeder group, so that the center coordinates of the feeder group aveFeeder x As close as possible to...

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Abstract

The invention discloses an LED chip mounter pick-and-paste path optimization method based on a hybrid genetic algorithm, and relates to a chip mounter pick-and-paste path optimization method. The objective of the invention is to solve the problems of long pick-up path and low LED patch production work efficiency of an existing method. The method comprises the following steps of: 1, preparing before production, and importing machine parameters and PCB data file information; 2, according to the machine parameters and the PCB data file information determined in the step 1, determining a feeder slot allocation position enabling the movement distance of the chip mounting head to be the shortest; 3, planning a parallel chip mounting head chip picking path, taking the determined feeder slot position distribution midpoint as a starting point and an ending point for optimizing the chip mounting path, searching a feasible solution of the chip mounting path by adopting a hybrid genetic algorithm,and reserving the shortest solution of the chip mounting path; and 4, outputting the solution with the shortest mounting path searched in the step 3 as an optimal solution. The method is applied to the fields of electric appliance technology and electrical engineering.

Description

technical field [0001] The invention relates to a pick-and-stick path optimization method for a placement machine, and belongs to the fields of electrical technology and electrical engineering. Background technique [0002] Nowadays, printed circuit boards (PCB) are widely used in modern electronic equipment, and are one of the indispensable production and daily necessities in people's daily life. High-precision, high-efficiency PCB production solutions are of great significance to the upgrading of electronic and electrical related industries, and placement machines are fully automatic production equipment used to pick and place components and assemble PCBs, and are also the most critical and complex process in PCB production. The most time-consuming production equipment. However, the small size of LEDs and the large workload of pick-and-place determine that the processing time required in actual production is relatively long. [0003] Generally, "SMD component" refers to ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H05K3/30G06N3/12G06Q10/04
CPCG06N3/126G06Q10/047H05K3/30
Inventor 高会军李政锴卢光宇邱剑彬于兴虎
Owner 宁波智能装备研究院有限公司
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