A hybrid genetic algorithm for sequencing PCB component placement

A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable X-Y table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic algorithm to optimize the sequence of component placements for a chip shooter machine. The objective of the problem is to minimize the total traveling distance of the X-Y table or the board. The genetic algorithm developed in the paper hybridizes the nearest neighbor heuristic, and an iterated swap procedure, which is a new improved heuristic. We have compared the performance of the hybrid genetic algorithm with that of the approach proposed by other researchers and have demonstrated our algorithm is superior in terms of the distance traveled by the X-Y table or the board.

A hybrid genetic algorithm for component sequencing and feeder arrangement

This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total travelling distance, or the travelling time, of the placement head. The genetic algorithm developed in the paper hybrisizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance travelled by the placement head.

A genetic algorithm to optimise the component placement process in the PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.