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Title of Project : A Genetic Algorithm for Optimizing Component Placement Sequence in Printed Circuit Board (PCB) Assembly.

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The problem of minimizing the time required to place component sequence of printed circuit board (PCB) assembly is considered in this project. In the assembly of PCB?s, the component placement process is often the bottleneck, and the equipment to complete component placement is often the largest capital investment. The number of components placed on a PCB can range from few to hundreds.

The complexity of the optimization problem of minimizing the assembly time results in that acquiring its desired solution is difficult. For it is of a combinatorial nature and NP-hard, there is no exact algorithm for it. As a result, developing an application to determine a placement sequence heuristically can translate into reduced cycle times for the overall assembly process and reduced assembly costs. As an efficient and useful procedure for solving combinatorial optimization problem, a Genetic Algorithm (GA) is proposed in this project.

For this purpose, a mathematical model of the problem will be proposed. In GA, crossover operator plays a vital role. All existing crossover operators will be evaluated for the problem and best crossover operator will be considered in our study.The GA will incorporate reproduction, crossover and mutation operators. A designed experiment will be carried out to determine the best crossover probability, mutation probability, and population size for our GA to solve the problem.

Then optimization software will be developed and an experiment will be carried out by solving different known problems, and thus validates the software. Finally, the total assembly time will be compared with those by some existing algorithms.