Int. J. Simul. Multidisci. Des. Optim.
Volume 13, 2022
Computation Challenges for engineering problems
|Number of page(s)||13|
|Published online||06 January 2022|
Numerical investigation of dimple-texturing on the turning performance of hardened AISI H-13 steel
Research Scholar, Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore 641 021, India
2 Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore 641 021, India
* e-mail: email@example.com
Accepted: 29 November 2021
Forming micro-dimples nearer to the cutting edge on the rack face of the tungsten carbide cutting inserts will positively influence the machinability. However, it is challenging to machine the perfect micro-dimple dimensions by utilizing the available machining techniques. Finite element analysis can be an efficient way to observe the influence of dimple-texture area density, micro-dimple size, and various micro-dimple shapes on cutting inserts' machinability. This paper numerically analyses the impact of micro-dimple-textured cutting inserts in dry machining of AISI H-13 steel using AdvantEdge (virtual machining and finite element analysis software). Micro-dimples are formed on the rack face of tungsten carbide cutting inserts to observe the effect of dimple-textured cutting inserts on machinability compared to non-textured cutting inserts in terms of micro-dimple shape, micro-dimple size, and micro-dimple area density ratio. Their outcomes are analysed in terms of chip-insert contact length, main cutting force, and thrust force. It is observed that micro-dimple textured cutting inserts exhibit minimal main cutting force and thrust force in line with increasing the cutting insert life span. The abrasive wear was reduced in dimple-textured cutting inserts due to minimal contact between the cutting insert and chip developed compared to non-textured cutting inserts.
Key words: Dimple-textured cutting insert / FEM analysis / cutting force / abrasive wear / dimple area density
© G. Vignesh et al., published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.