Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering

Research on Parameter Optimization Algorithms of Numerical Control Machining Process for Complex Curved Surface

Authors
Mei Tian
Corresponding Author
Mei Tian
Available Online July 2016.
DOI
10.2991/icsnce-16.2016.123How to use a DOI?
Keywords
Complex curved surface; Process parameters; Optimization algorithm; Numerical control
Abstract

Through the establishment the parameters optimization model of milling machine, the optimal solution of the cutting parameters for complex surface is obtained by using some optimization algorithms for parameter optimization. Based on analyzing the main factors influencing on the milling process, the optimized functions and the corresponding constraint functions are obtained. And in order to improve production efficiency, ensure product quality and reduce production costs, the theoretical optimization results were simulated and processed by software.

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/).

Download article (PDF)

Volume Title
Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
Series
Advances in Engineering Research
Publication Date
July 2016
ISBN
978-94-6252-217-6
ISSN
2352-5401
DOI
10.2991/icsnce-16.2016.123How 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  - Mei Tian
PY  - 2016/07
DA  - 2016/07
TI  - Research on Parameter Optimization Algorithms of Numerical Control Machining Process for Complex Curved Surface
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 634
EP  - 638
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.123
DO  - 10.2991/icsnce-16.2016.123
ID  - Tian2016/07
ER  -