Multiple setup printed circuit board assembly planning using genetic algorithms

A Genetic Algorithm (GA) program is developed for simultaneously optimizing component placement sequence and feeder assignments in the assembly of Printed Circuit Boards (PCBs). The program extends the application of GA to this problem by providing handling of two practical but complicating factors: (1) feeder constraints forcing multiple setups, and (2) new generation assembly machines which can place from both sequenced tape and component feeders within the same setup. This paper details the algorithm developed, demonstrates the approach on several examples, and investigates the performance of the GA and the impact of its various parameters.