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An analytical model of orthogonal metal cutting: implementation using LMFIT library in Python

Abstract : In this study, an analytical model for orthogonal metal cutting is presented for predicting cutting forces and temperature at tool-chip interface. In this approach, the properties of the materials are modeled by the Johnson-Cook constitutive material flow law, where the stress is a function of strain, strain rate, and temperature. The aim of the proposed work is to improve the numerical resolution of the analytical model. The determination of the optimal cutting parameters is based on the use of the Nonlinear Least-Squares Minimization and Curve-Fitting library for Python (LMFIT) whith a dual Levenberg-Marquardt optimization algorithm that has been developed and implemented in Python. The performance of the developed model has been studied by comparing its predictions with some experimental machining data for 1045 steels. A good correlation between the results of the proposed model and those resulting from literature and experiments has been demonstrated.
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Submitted on : Tuesday, November 12, 2019 - 3:12:01 PM
Last modification on : Thursday, July 23, 2020 - 4:30:16 PM
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  • HAL Id : hal-02359773, version 1
  • OATAO : 22948

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Maxime Dawoua Kaoutoing, Raymond Houé Ngouna, Tibi Beda, Olivier Pantalé. An analytical model of orthogonal metal cutting: implementation using LMFIT library in Python. The 8th International Conference on Structural Analysis of Advanced Materials (ICSAAM 2018), Aug 2018, Tarbes, France. pp.0. ⟨hal-02359773⟩

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