Multi-head chip mounter mounting efficiency optimization method and system based on bat algorithm

Abstract

The invention discloses a multi-head chip mounter mounting efficiency optimization method and system based on a bat algorithm. The method comprises the following steps: S1, constructing a main body code and a hidden layer code for the mounting of the chip mounter; S2, initializing a group of sequences for the main body codes by adopting a random integer coding mode to obtain an initialized population; S3, constructing a fitness function, calculating to obtain the fitness value of each bat in the initialized population, and obtaining the optimal bat position; S4, adopting Hamming distance to adjust speed updating, and associating the speed of the ith bat during t times of iteration with the current optimal bat position; S5, calculating a current bat position through position updating, wherein the current bat position is used as a locally optimal path; S6, carrying out the variation of the main body code, and circulating the steps S2 to S5 so as to obtain a global optimal path for the mounting of the chip mounter, wherein the mounting efficiency of the chip mounter is optimized; according to the multi-head chip mounter mounting efficiency optimization method and system disclosed in the invention, the calculation efficiency and the solving precision of solving the optimization problem in the mounting 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

Images