Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)

Optimization of Cutting Power Based on Dynamic Cutting Force Model

Authors
Lei Fang, Guangrong Yan, Xiangyu Xu, Tao Ding, Genao Zang, Le LIU
Corresponding Author
Lei Fang
Available Online April 2016.
DOI
https://doi.org/10.2991/ameii-16.2016.69How to use a DOI?
Keywords
Dynamic cutting force model, cutting parameters optimization, output power smoothing
Abstract

The machine output power smoothing has an important significance to improve the efficiency and quality of machining. With the secondary development of cutting geometry simulation software, we have got the geometry cutting parameters, carried out a physical simulation of the whole cutting processing and optimized the cutting parameters in this paper. The results show that this method is efficient and practical and finally improve the stability of NC machining process.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
978-94-6252-188-9
ISSN
2352-5401
DOI
https://doi.org/10.2991/ameii-16.2016.69How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lei Fang
AU  - Guangrong Yan
AU  - Xiangyu Xu
AU  - Tao Ding
AU  - Genao Zang
AU  - Le LIU
PY  - 2016/04
DA  - 2016/04
TI  - Optimization of Cutting Power Based on Dynamic Cutting Force Model
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 334
EP  - 341
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.69
DO  - https://doi.org/10.2991/ameii-16.2016.69
ID  - Fang2016/04
ER  -