Optimizing the Performance of Chip Shooter Machine Based on Ant Colony Algorithm

Abstract

The component placement sequence and feeder arrangement are two critical factors determining the assembly time of chip-shooter machine (CS). In addition, the different size of component and different arrangement strategy affect the feeder arrangement and component placement sequence. Based on the engineering analysis, an integrated optimization model of printed circuit board (PCB) assembly for CS machine is established. According to the parallel placement character of CS machine, "Max-Min Ant Colony Algorithm with Communication function (MMAC)" is designed based on traditional Ant Colony Algorithm. The idea that two ants with different duties collaborate to solve the optimization problem is presented. Guide ants optimize placement sequence while executant ants optimize feeder arrangement according to the components placement sequence. The component placement sequence and feeder arrangement are optimized simultaneously