hrvatski

Optimization of Turning using Evolutionary Algorithms

Advanced manufacturing requires a powerful tool for reliable modeling and solving the complex machining optimization problems. A non-conventional approach using evolutionary algorithms inspired by Darwinian findings about the evolution of the biological species and the survival of the fittest organisms (i.e. natural selection) is proposed in this paper. It is illustrated with an experiment of rough longitudinal turning. Genetic programming (GP) is used to develop the models of the tool life, the tangential cutting force component and the surface roughness considering the cutting speed, the feed and the depth of cut as predetermined cutting parameters. Finally, genetic algorithm (GA) is applied for their optimization.

turning; optimization; evolutionary algorithms

nije evidentirano

engleski

Optimization of Turning using Evolutionary Algorithms

Advanced manufacturing requires a powerful tool for reliable modeling and solving the complex machining optimization problems. A non-conventional approach using evolutionary algorithms inspired by Darwinian findings about the evolution of the biological species and the survival of the fittest organisms (i.e. natural selection) is proposed in this paper. It is illustrated with an experiment of rough longitudinal turning. Genetic programming (GP) is used to develop the models of the tool life, the tangential cutting force component and the surface roughness considering the cutting speed, the feed and the depth of cut as predetermined cutting parameters. Finally, genetic algorithm (GA) is applied for their optimization.

turning; optimization; evolutionary algorithms

nije evidentirano