| Surface mount technology (SMT) has already been widely applied to printed circuit board (PCB) production in order to meet the need of board level circuit modules for military electronic equipment of a considerable variety, variable requirement of batch, short period, low cost, high quality, miniaturization as well as fast upgrade. A surface mount-placement machine, whose assembly planning is the bottleneck of the productivity improvement of SMT system, is the most important equipment of the whole system. This paper considers the problem of optimizing the PCB assembly planning which contains several heads and types of components, and the intention is to propose an optimization method which has a better performance, lower complexity and higher practicability, so that we can reduce the overall assembly time and improve the system productivity.The assembly planning of gantry machines was analyzed, and then an integrated optimization model was founded according to the factors we induced that affected the efficiency. The advantages and disadvantages of genetic algorithms (GA) and simulated annealing algorithm (SA) were analyzed. Fitness linear scaling, crossover and mutation operation of GA were modified firstly, and a special chromosome coding and encoding method was proposed according to assembly characteristics. The important parameters of GA and SA were designed carefully. For the first time, a genetic simulated annealing algorithm (GSA), which combines the advantages of the GA and SA, was employed to plan PCB assembly.The results show that the required time for mounting electronic parts can be decreased obviously,and our method can resolve the problem more effectively than unitary GA and SA. |
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