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Erschienen in: Advances in Manufacturing 1/2017

18.02.2017

Comparative study between wear of uncoated and TiAlN-coated carbide tools in milling of Ti6Al4V

verfasst von: M. S. Uddin, Binh Pham, Ahmed Sarhan, Animesh Basak, Alokesh Pramanik

Erschienen in: Advances in Manufacturing | Ausgabe 1/2017

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Abstract

As is recognized widely, tool wear is a major problem in the machining of difficult-to-cut titanium alloys. Therefore, it is of significant interest and importance to understand and determine quantitatively and qualitatively tool wear evolution and the underlying wear mechanisms. The main aim of this paper is to investigate and analyse wear, wear mechanisms and surface and chip generation of uncoated and TiAlN-coated carbide tools in a dry milling of Ti6Al4V alloys. The quantitative flank wear and roughness were measured and recorded. Optical and scanning electron microscopy (SEM) observations of the tool cutting edge, machined surface and chips were conducted. The results show that the TiAlN-coated tool exhibits an approximately 44% longer tool life than the uncoated tool at a cutting distance of 16 m. A more regular progressive abrasion between the flank face of the tool and the workpiece is found to be the underlying wear mechanism. The TiAlN-coated tool generates a smooth machined surface with 31% lower roughness than the uncoated tool. As is expected, both tools generate serrated chips. However, the burnt chips with blue color are noticed for the uncoated tool as the cutting continues further. The results are shown to be consistent with observation of other researchers, and further imply that coated tools with appropriate combinations of cutting parameters would be able to increase the tool life in cutting of titanium alloys.

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Metadaten
Titel
Comparative study between wear of uncoated and TiAlN-coated carbide tools in milling of Ti6Al4V
verfasst von
M. S. Uddin
Binh Pham
Ahmed Sarhan
Animesh Basak
Alokesh Pramanik
Publikationsdatum
18.02.2017
Verlag
Shanghai University
Erschienen in
Advances in Manufacturing / Ausgabe 1/2017
Print ISSN: 2095-3127
Elektronische ISSN: 2195-3597
DOI
https://doi.org/10.1007/s40436-016-0166-1

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