The optimization problems of industrial process attracted many researches since the early 90's of the last century. The production volume increase, lifespan shorten of the products and technological advances pushed the industries to seek for low cost and quick implementation solutions. One of the processes that became the core for increasing the sales volumes was the Surface Mount Technology -SMT composed by printing, automated chip mounting and reflow which replaced the Through Hole Technology -THT. This paper formulated a new point of view for modular chip mounters based on the already known feeder assignment problem and head motion problem applying the global optimization using the nonsorting dominance genetic algorithm the NSGAII in regard of the total cycle time reduction. The modeling of the fitness functions were presented and the multi criteria optimization tool was described using the machine functions and constraints. The same method could be applied to describe other type of machines to support future research.
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