The paper presents the use of evolutionary method for improving efficiency of the production process. The purpose of research was to select the parameters of turning the monel alloy in order to increase productivity with required tool wearing resistance and surface quality. Three independent variables, cutting speed, feed rate, and cutting depth were monitored between cutting process. Those variables influence the dependent variables, i.e., tool life and surface roughness. On the basis of experimental data set, different models for tool life and surface roughness were developed by genetic programming method. The two models for tool life and surface roughness predict if the specified tool life and surface roughness are reached. The limit for high quality machining of the surface was the quality class N6 (Ra=0.8μm), whereas for tool life the time of 13 minutes and more was expected. After process modelling the parameter selection plan was developed according to predicted tool life and surface roughness. The proposed concept robustly and simply ensures monitoring and optimization of the turning process. The results of researches were transferred into practice.
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