3D FINITE ELEMENT MODELING FOR ESTIMATING KEY MACHINABILITY ASPECTS IN TURNING OF COMMERCIALLY PURE TITANIUM

Akhtar Khan () and Kalipada Maity
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Akhtar Khan: Department of Mechanical Engineering, National Institute of Technology Rourkela, 769008, Odisha, India
Kalipada Maity: Department of Mechanical Engineering, National Institute of Technology Rourkela, 769008, Odisha, India

Surface Review and Letters (SRL), 2019, vol. 26, issue 01, 1-20

Abstract: The present work aims at numerical approximation in combination with experimental validation of some of the important performance measures in turning of commercially pure titanium (CP-Ti) with uncoated carbide inserts. A three-dimensional (3D) finite element model was developed based on Lagrangian criterion. Simulation of the turning operation was performed using DEFORM 3D software in order to approximate the responses viz. feed force (Fx), radial force (Fy), tangential force (Fz), flank wear (Vb) and machining temperature (Tm). Usui’s tool wear model was used to predict the flank wear. Morphology of the free and back surfaces of the chips was examined under a field emission electron microscope (FESEM). Turning experiments were carried out on a heavy duty lathe equipped with a 3D dynamometer. Secondly, a quadratic model was acquired for all the aforementioned quality characteristics using response surface methodology (RSM). Analysis of variance (ANOVA) test was performed to confirm the adequacy of the developed quadratic model. The results obtained from simulation and quadratic model were compared with the experimental data sets. Finally, an error analysis was done to determine the percentage inaccuracy of both the models. The percentage error for all the turning responses, was observed within 6% which showed the satisfactoriness of the proposed approximation tools. However, the simulation model exhibited lower prediction error when compared with the quadratic counterpart.

Keywords: Analysis of variance; commercially pure titanium; deform 3D; response surface methodology; tool wear (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S0218625X18501366

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