Multi-objective optimization of quality in laser cutting based on response surface model
- https://doi.org/10.2991/iccia.2012.315How to use a DOI?
- laser cutting, multi-objective optimization, RSM, improved Pareto genetic algorithm
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
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Cite this article
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 - https://doi.org/10.2991/iccia.2012.315 ID - Hao2014/05 ER -