首页> 外文会议>International Conference on Advanced Design and Manufacturing Engineering >Optimizing the Operation Sequence of Chip Shooter Machine Based on the Particle Swarm Optimization Algorithm
【24h】

Optimizing the Operation Sequence of Chip Shooter Machine Based on the Particle Swarm Optimization Algorithm

机译:基于粒子群优化算法优化芯片射击机的操作顺序

获取原文

摘要

The mounting process is the key factor of the placement efficiency, it is also important for the improvement of the efficiency of whole production line and decrease of the cost. This paper analyzed the mounting process of the Chip Shooter machine, applied the PSO algorithm, constructed the corresponding coding system, proposed the corresponding particle update mechanism, introduced the partially matched crossover idea of the genetic algorithm into the PSO algorithm, and designed the new re-scheduling method of feeder position assignment to optimize the position assignment of feeders and the pickup and placement sequence of components, thus improved the placement efficiency. After comparing the results before and after the simulation test for selected 8 pieces of PCB, the average efficiency of this algorithm is 7.09% higher than genetic algorithm method that is based on sort encoding. The experimental result shows that, this algorithm is more efficiency on the improvement placement efficiency and decrease of the placement time for the chip shooter machine.
机译:安装过程是放置效率的关键因素,对于提高整个生产线的效率和成本降低也很重要。本文分析了芯片射击机的安装过程,应用PSO算法,构建了相应的编码系统,提出了相应的粒子更新机制,将遗传算法的部分匹配交叉思想引入PSO算法,并设计了新的重新设计 - 馈线位置分配的平移方法,以优化馈线的位置分配和拾取组件的拾取和放置序列,从而提高了放置效率。在比较所选择的8个PCB的模拟测试之前和之后的结果之后,该算法的平均效率高于基于分类编码的遗传算法方法7.09%。实验结果表明,该算法更高效率对芯片射击机的提高放置效率和放置时间的降低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号