Multi-objective optimization of quality in laser cutting based on response surface model

DOI

10.2991/iccia.2012.315How to use a DOI?

Keywords

laser cutting, multi-objective optimization, RSM, improved Pareto genetic algorithm

Abstract

Prediction and optimization of quality characteristics is an important means to improve the quality of laser cutting. Kerf width (KW) and material removal rate(MRR) are selected as the quality characteristics in this paper. The fitting response surface models (RSM) of KW and MRR are considered as the optimization objective function in pulsed Nd: YAG laser cutting of alloy steel for multi-objective optimization. An improved Pareto genetic algorithm is used in the optimization, and the significant factors have been found. The predicted results are basically consistent with the experimental. Therefore, the method used in this paper can be used for optimization of KW and MRR in pulse Nd: YAG laser cutting. The study can provide theoretical basis fo

Copyright

© 2013, 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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TY  - CONF
AU  - Huijuan Hao
AU  - Maoli Wang
AU  - Fengqi Hao
PY  - 2014/05
DA  - 2014/05
TI  - Multi-objective optimization of quality in laser cutting based on response surface model
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1271
EP  - 1274
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.315
DO  - 10.2991/iccia.2012.315
ID  - Hao2014/05
ER  -