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Design of fuzzy expert system for predicting of surface roughness in high-pressure jet assisted turning using bioinspired algorithms

  • Davorin Kramar (a1), Djordje Cica (a2), Branislav Sredanovic (a2) and Janez Kopac (a1)

Abstract

The surface roughness of the machined parts is one of the most important factors that have considerable influence on the quality and functional properties of products. The objective of this study is development of a surface roughness prediction model for machining Inconel 718 in high-pressure jet assisted turning using the fuzzy expert system, where the fuzzy system is optimized using two bioinspired algorithms: genetic algorithm and particle swarm optimization. The effect of various influential machining parameters, such as diameter of the nozzle, pressure of the jet, cutting speed, feed rate, and distance between the impact point of the jet and cutting edge were taken into consideration in this study. The predicted surface roughness values obtained from developed fuzzy expert systems were compared with the experimental data, and the results indicate that proposed systems can be effectively used to estimate the surface roughness in high-pressure jet assisted turning.

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Corresponding author

Reprint requests to: Davorin Kramar, University of Ljubljana, Faculty of Mechanical Engineering, Askerceva 6, 1000 Ljubljana, Slovenia. E-mail: davorin.kramar@fs.uni-lj.si

References

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Design of fuzzy expert system for predicting of surface roughness in high-pressure jet assisted turning using bioinspired algorithms

  • Davorin Kramar (a1), Djordje Cica (a2), Branislav Sredanovic (a2) and Janez Kopac (a1)

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