Optimización del proceso de montaje de componentes SMD usando algoritmo genético multiobjetivo en la industria

Abstract

The article proposes the optimization of the assembly sequence of SMD components on printed circuit boards using a multi-objective genetic algorithm (NSGA-II). The study was conducted in an electronics industry at the Manaus Industrial Hub, showing that the proposed algorithm outperformed the traditional machine inserter optimizer, reducing assembly time by 6 seconds per board and increasing productivity by 30%. The results highlight the effectiveness of NSGA-II in solving complex industrial optimization problems.