Experimental Investigation and Numerical Prediction of the Effects of Cutting Tool Geometry During Turning of AISI 316L Steel

Authors

  • Amor Benmeddour
    Affiliation
    Department of Mechanical Engineering, Faculty of Sciences Technology, University of Brothers Mentouri, 25000 Constantine, 1 Route de Ain El Bey, Algeria
https://doi.org/10.3311/PPme.16844

Abstract

In this work, a numerical and an experimental study aimed to gain a better understanding of the impact of tool geometry such as (rake angle and cutting edge radius) on the temperature distribution and residual stresses in machining surface of AISI 316L stainless steel have been presented. To evaluate the experimental results, various experimental equipment was used, such as a conventional lathe to carry out the machining operations, the cutting force was measured using a Kistler dynamometer and X-ray diffraction technique was employed for determination of the residual stresses distribution on the machined surfaces. In addition, A thermo-mechanically coupled finite element (FE) analysis for cutting process is developed through ABAQUS code to predict the temperature distribution and residual stresses using an Arbitrary Lagrangian-Eulerian (ALE) approach. An inverse identification method has been used to determine the adequate Johnson-Cook (JC) material model parameters to obtain a good correlation between the cutting force measurements and numerical one. The FE model was then validated by comparison of the numerical results of residual stresses with experimental measurements for different tool geometries, which revealed a reasonable agreement.

Keywords:

metal cutting, FEM, JC material parameters, tool geometry, cutting force, temperature distribution, residual stress

Citation data from Crossref and Scopus

Published Online

2021-09-24

How to Cite

Benmeddour, A. “Experimental Investigation and Numerical Prediction of the Effects of Cutting Tool Geometry During Turning of AISI 316L Steel”, Periodica Polytechnica Mechanical Engineering, 65(4), pp. 293–301, 2021. https://doi.org/10.3311/PPme.16844

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Articles