| Issue |
Int. J. Simul. Multidisci. Des. Optim.
Volume 12, 2021
Advances in Modeling and Optimization of Manufacturing Processes
|
|
|---|---|---|
| Article Number | 27 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/smdo/2021025 | |
| Published online | 29 October 2021 | |
Research Article
Theoretical approaches for determining machining conditions affecting a machined surface topography in filleted end milling
Department of Systems Design Engineering, Faculty of Science and Technology, Seikei University, Tokyo 180-8633, Japan
* e-mail: ts_s@outlook.com
Received:
10
April
2021
Accepted:
3
October
2021
This study demonstrates theoretical approaches useful for practical determination of machining conditions affecting machined surface topography in filleted end milling. Tool orientation is investigated in particular. There are dominant processing parameters' optimizations from various perspectives, whereas a few comprehensive strategies have been proposed to determine machining conditions in filleted end milling. It is also practically scarce to discover the optimization strategy taking path interval determination as the theoretical fountainhead. In this study, theoretical approaches were described to determine machining conditions affecting machined surface topography in filleted end milling. After geometrical description was arranged to model multi-axis filleted end milling, multi-layer approach and the other computable parameters were proposed to obtain decent surface topography generated in filleted end milling. The analytical example focusing on tool orientation was provided with discussion. As a result, some characteristics of theoretical approaches were revealed with the visual evidences. Finally, optimal tool orientation will be arranged based on the findings.
Key words: Machined surface / surface roughness optimization / path interval / multi-axis CNC machining / filleted end mill
© T. Sekine, Published by EDP Sciences, 2021
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.
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