Optimizing the Performance of Chip Shooter Machine Based on Improved Genetic Algorithm

Abstract

The component placement sequence and feeder arrangement are two critical factors determining the assembly time of chip-shooter machine. 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 chip-shooter machine is established. The improved genetic algorithm (IGA) proposes a two-dimensional coding method. In the individual chromosome, the component number describes the component placement sequence, the slot number describes the feeder arrangement, and the component type number describes the relation between the component placement sequence and feeder arrangement. The IGA uses the improved order crossover, adaptive mutation, local search, and the parallel structure. The component placement sequence and feeder arrangement are optimized simultaneously. The performance of IGA is superior to other algorithms.