OPTIMIZATION OF PROCESS PLANNING PARAMETERS FOR ROTATIONAL COMPONENTS BY GENETIC ALGORITHMS

In CAPP systems process parameter optimization is one of the key areas for research and development. Traditional techniques have very limited scope because of the complexity of the optimization problem. Due to the rapid development of computer technology Genetic Algorithms (GAs), which are robust search algorithm, have been found to be suitable and efficient tools for optimization in such cases. In this work process planning parameters for machining rotational components are optimized by a Genetic Algorithm Optimization Toolbox developed in Matlab environment. Here machining time is considered as the objective function and constraints are machine capacity, limits of feed rate, depth of cut, cutting speed etc. Machining time is minimized through a series of generations while some genetic operators are applied at each generation. The result of the work shows how a complex optimization problem is handle by a genetic algorithm and converges very quickly.