Investigation of machining characteristics of hard-to-machine Ti-6Al-4V-ELI alloy for biomedical applications
Author(s) -
Swastik Pradhan,
Sunpreet Singh,
Chander Prakash,
Grzegorz Królczyk,
Alokesh Pramanik,
Catalin I. Pruncu
Publication year - 2019
Publication title -
journal of materials research and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.832
H-Index - 44
eISSN - 2214-0697
pISSN - 2238-7854
DOI - 10.1016/j.jmrt.2019.08.033
Subject(s) - machining , materials science , surface roughness , chip , tool wear , chip formation , mechanical engineering , flank , finite element method , surface finish , titanium alloy , composite material , alloy , metallurgy , structural engineering , computer science , engineering , telecommunications , sociology , anthropology
Dry machining of Ti-6Al-4V alloy was investigated using SNMA120408 grade inserts. The material studied is designed for orthopedic applications. The effects of main cutting speed (VC), at constant feed rate (F) and depth of cut (DC) on machining characteristics (Feed force (Ff), radial force (Rf), Tangential Force (Tf)) and surface integrity (i.e., tool-chip contact length, chip segmentation, surface roughness, and tool wear) were examined. Experimental data indicate the cutting speed as the major parameter with direct impact on the machining characteristics. Increasing of the cutting speed promotes higher tangential forces that allow a decrease of the chip contact length; a smaller contact length results in a lower surface roughness and flank wear rate, respectively. To gain further insight from the simulated turning process an advanced Finite Element (FE) model was developed. The numerical model was built on the DEFORM-3D commercial software by incorporating the experimental cutting parameters. The numerical simulations results agree very well with experimental outputs in terms of cutting forces (FCS), tool-chip (T-C) contact length. Therefore, it was possible to estimate with accuracy the effective stress (σE) and the cutting temperature (TC). Further, due to its high robustness, the numerical model developed can be implemented in solving the industrial challenge (i.e., biomedical field) for predicting formations of serrated chip segment, chip thickness, potential types of chips, types of fracture mechanism and tool wear mechanism/rate generated during machining process.
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