OPTIMIZATION OF MACHINING PROCESSES USING THE ABC METHOD AND GENETIC ALGORITHM

Abstract

Optimization of machining processes is one of the most important elements in the planning of metal parts production. In this paper, we have applied ABC methods to determine the cost of all processes that are used in production of homocinetical sleeve joint. After that we have used multy-criterion optimization technique based on genetic algorithms, in order to optimize the basic parameters of all the processes: the speed and feed. The objective function is given in a form of specific cost for each processe, for which minimization it is need to consider the appropriate mechanical and manufacturing constraints. The proposed model uses a genetic algorithm, so that after a certain number of iterations optimal result is reached that will satisfy the objective function and all anticipated limitations. Obtained results shows that GA solves the optimization problem in an efficient and effective manner, so that the results can be integrated into an intelligent manufacturing system for solving complex optimization problems in machine production processes.