Multi-objective optimization of parameters in turning of N-155 iron-nickel-base superalloy using gray relational analysis

Technical Paper
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Abstract

Obtaining high surface quality with minimum tool wear values is one of the most important goals of turning process. Moreover, when it comes to process costs, the volume of material removed is very important and should be considered when optimizing cutting variables. In this work, gray relational analysis was employed with the aim of simultaneously optimizing surface roughness, tool wear and volume of material removed. Cutting speed, feed rate and depth of cut were chosen as process control factors. Optimization results showed that cutting speed of 80 m/min, feed rate of 0.1 mm/rev and depth of cut of 1.5 mm were the optimum set of cutting parameters. Scanning electron microscope images of worn cutting edges revealed that depth-of-cut notch, built-up edge, and adhesion are dominant wear mechanisms. Finally, confirmation test proved the accuracy of the prediction carried out by the optimization process.

Keywords

Iron-nickel-base superalloy Turning Gray relational analysis Tool wear mechanism Surface roughness Volume of material removed 

Notes

Acknowledgements

The authors would like to thank Mr. Ali Dastani, the CEO of the Zangan Part Ghate Industrial Co., for his kind support of this research.

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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2018

Authors and Affiliations

  1. 1.Department of Manufacturing Engineering, Faculty of Mechanical EngineeringUniversity of TabrizTabrizIran
  2. 2.School of Mechanical EngineeringIran University of Science and TechnologyTehranIran
  3. 3.Department of Mechanical EngineeringÉcole Polytechnique de MontréalMontréalCanada

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