1 Citation as: G. Bolar, S.N. Joshi, Three-dimensional numerical modeling, simulation and experimental validation of milling of a thin-wall component P. I. Mech. Eng. B-J. Eng. Manufac. January 2017, DOI: 10.1177/0954405416685387. Three-dimensional numerical modeling, simulation and experimental validation of milling of a thin-wall component Gururaj Bolar 1 , Shrikrishna N Joshi 2* 1 Research Scholar, 2 Assistant Professor Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam, INDIA *Corresponding author Email: snj@iitg.ernet.in Abstract Study on mechanics of milling of thin-wall components using a helical end mill is important in view of its complex nature and prominent applications in aerospace, automobile and electronics areas. This paper presents a realistic three-dimensional, thermo-structural, finite element based mathematical model for thin-wall milling of aerospace grade aluminum alloy. Lagrangian formulation with explicit solution scheme was employed to simulate the interaction between helical milling cutter and the workpiece. Behavior of the material at high strain, strain rate and temperature was defined by Johnson-Cook material constitutive model. Johnson-Cook damage law and friction law were used to account for chip separation and contact interaction. Experimental work was carried out to validate the results predicted by the mathematical model. The model was found to be predicting well the process performance parameters viz. cutting forces, wall deflection, and chip dimensions. The developed model predicted the forces in radial, feed and axial directions with errors of 14%, 26% and 33% respectively. The prediction errors for deflections at top, middle and bottom portions of thin wall were within 11% to 39%. The simulated chip dimensions were in good agreement with experimental results whilst the computed cutting temperature varied by 17% with respect to the experimental value. Overall it was found that the developed model predicts the process responses with fair and acceptable prediction accuracy. By using the developed model a study on the effect of process parameters