A method and system for optimizing placement efficiency of multi-head placement machines based on bat algorithm

Abstract

The invention discloses a method and system for optimizing the mounting efficiency of a multi-head chip mounter based on the bat algorithm. S1: Construct the main body code and hidden layer code of the chip mounter; S2: Initialize a random integer code for the body code. Group sequence to get the initialization population; S3: Construct the fitness function, calculate the fitness value of each bat in the initialization population, and get the optimal bat position; S4: Use the Hamming distance to adjust the speed update, and put the i-th bat at t The speed at the first iteration is related to the current optimal bat position; S5: calculate the current bat position through position update, and the current bat position is regarded as the local optimal path; S6: mutate the main body code, loop through steps S2 to S5, and get The global optimal path for the placement of the placement machine to optimize the placement efficiency of the placement machine; through this application, the calculation efficiency and accuracy of solving the optimization problem of the placement process are improved.

Description

technical field [0001] The invention relates to the technical field of placement devices, in particular to a method and system for optimizing the placement efficiency of a multi-head placement machine based on a bat algorithm. Background technique [0002] The placement machine is widely used in the assembly line of printed circuit boards. The production speed of an SMT production line is determined by the placement machine. Therefore, the placement machine is the core technology part of the entire production line. It has very important practical significance and engineering value to optimize the process and shorten the placement time. In the actual production process, if the placement time is too long, the solder paste printed on the PCB will fail, which will make the effect of reflow soldering worse and seriously affect the product quality. [0003] At present, the application of algorithms on the placement efficiency of multi-head arch mounters can be roughly divided int...

AI Technical Summary

Problems solved by technology

[0005] In the actual application process, commonly used integer crossover operators include PMX (Partial-Mapped Crossover), OX (Order Crossover), PBX (Position-based Crossover), OBX (Order-Based Crossover) and CX (Cycle Crossover), etc. Through comparative tests, it is found that when these types of crossover operators are used, the search ability is not significantly improved, the convergence speed is slow, the solution is very destructive, and it is difficult to achieve the expected optimization effect.

This causes the staff to spend a lot of time on the improvement of the algorithm, and it is difficult to have more energy to focus on the actual application scenario, which shifts the focus of work to a certain extent

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