单晶Si电火花线切割工艺的多目标优化研究

路雄; 李淑娟; 辛彬; 李志鹏

doi:10.13433/j.cnki.1003-8728.20180030

单晶Si电火花线切割工艺的多目标优化研究

doi: 10.13433/j.cnki.1003-8728.20180030

1.
西安理工大学机械与精密仪器工程学院, 西安 710048

基金项目:

国家自然科学基金项目（51575442）、陕西省教育厅重点实验室基金项目（2014SZS10-Z01）及陕西省自然科学基金重点项目（2016JZ0110）资助

详细信息

作者简介:
路雄(1993-),硕士研究生,研究方向为脆性材料加工与控制,luxiong2015@sina.com

通讯作者:
李淑娟,教授,博士,shujuanli@xaut.edu.com

计量
- 文章访问数: 974
- HTML全文浏览量: 43
- PDF下载量: 707
- 被引次数: 0
出版历程
- 收稿日期: 2017-06-06
- 刊出日期: 2018-08-05

Multi-objective Optimization for WEDM of Single-crystal Silicon

1.
School of Machinery and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China

摘要

摘要: 由于电火花线切割放电过程很难通过理论分析得到有效的切割机理数学模型。引入中心复合实验设计（Central composite design，CCD）实验方法，建立四因素三水平的单晶Si电火花线切割的实验方案。采用响应曲面法（Response surface methodology，RSM）建立单晶Si表面粗糙度和材料去除率与空载电压、脉冲宽度、脉冲间隔和运丝速度等主要工艺参数的二阶数学模型并进行分析。分析结果表明：预测模型具有较好的拟合度和适应性。并以提高单晶Si表面的加工质量和材料去除率为目标建立工艺参数优化模型；设计非支配快速排序遗传算法（NSGA-Ⅱ）进行优化问题求解，得到了最优的Pareto解集。实验表明，优化模型对表面粗糙度和材料去除率的预测是准确的，并且能实现相应的半导体材料的线切割过程中的粗糙度和材料去除率的预测。
- 单晶Si /
- 响应曲面法 /
- 表面粗糙度 /
- 材料去除率 /
- NSGA-Ⅱ算法
Abstract: It is difficult to obtain an effective mathematical model for cutting mechanism by using theoretical analysis. This paper introduces the experimental method of central composite design (CCD), and establishes the experimental scheme of four factors and three levels for single-crystal Silicon wire cutting. The second order mathematical model for single-crystal Silicon surface roughness and material removal rate, such as no-load voltage, pulse width, pulse interval and wire speed, was established by using response surface methodology (RSM). The results show that the prediction model has good fittness and adaptability. Non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) is used to solve the optimization problem, and the optimal Pareto solution set is obtained. The optimization of the process parameters is carried out to improve the processing quality and material removal rate of the surface of single-crystal Silicon. Experiments show that the present model is accurate for predicting the surface roughness and material removal rate, and which can realize the prediction of roughness and material removal rate during the wire cutting of the corresponding semiconductor materials.
- single-crystal silicon /
- RSM /
- surface roughness /
- material removal rate /
- NSGA-Ⅱ

HTML全文

参考文献(18)

[1]	Spur G, Scho··nbeck J. Anode erosion in Wire-EDM-a theoretical model[J]. CIRP Annals, 1993,42(1):253-256
[2]	Soundararajan R, Ramesh A, Mohanraj N, et al. An investigation of material removal rate and surface roughness of squeeze casted A413 alloy on WEDM by multi response optimization using RSM[J]. Journal of Alloys and Compounds, 2016,685:533-545
[3]	Nourbakhsh F, Rajurkar K P, Malshe A P, et al. Wire electro-discharge machining of titanium alloy[J]. Procedia Cirp, 2013,5:13-18
[4]	Mandal D, Pal S K, Saha P. Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-Ⅱ[J]. Journal of Materials Processing Technology, 2007,186(1-3):154-162
[5]	Chandrasekaran M, George J, Arunachalam R M, et al. Multi-objective parametric optimization for non-conventional machining of Inconel 825-for an industrial application[J]. Journal of Scientific and Industrial Research, 2017,76:314-319
[6]	王小军,孙振亚.硅片切割技术的现状和发展趋势[J].超硬材料工程,2011,23(6):19-23 Wang X J, Sun Z Y. Research situation and development trends of silicon wafer cutting technology[J]. Superhard Material Engineering, 2011,23(6):19-23(in Chinese)
[7]	Luo Y F, Chen C G, Tong Z F. Investigation of silicon wafering by wire EDM[J]. Journal of Materials Science, 1992,27(21):5805-5810
[8]	Saleh T, Rasheed A N, Muthalif A G A. Experimental study on improving μ-WEDM and μ-EDM of doped silicon by temporary metallic coating[J]. The International Journal of Advanced Manufacturing Technology, 2015,78(9-12):1651-1663
[9]	Yeh C C, Wu K L, Lee J W, et al. Study on surface characteristics using phosphorous dielectric on wire electrical discharge machining of polycrystalline silicon[J]. The International Journal of Advanced Manufacturing Technology, 2013,69(1-4):71-80
[10]	Yu P H, Wu K L, Lee S M, et al. Effect of voltage supply mode on electrolytic machining of polycrystalline silicon[J]. Materials and Manufacturing Processes, 2011,26(12):1459-1465
[11]	Yu P H, Hung J C, Lee H M, et al. Machining characteristics of magnetic force-assisted electrolytic machining for polycrystalline silicon[J]. Advanced Materials Research, 2011,325:523-529
[12]	Luis C J, Puertas I, Villa G. Material removal rate and electrode wear study on the EDM of silicon carbide[J]. Journal of Materials Processing Technology, 2005,164-165:889-896
[13]	Chen H R, Liu Z D, Huang S J, et al. Study of the mechanism of multi-channel discharge in semiconductor processing by WEDM[J]. Materials Science in Semiconductor Processing, 2015,32:125-130
[14]	苏军.高速走丝电火花线切割工艺建模及参数优化研究[D].西安:西安理工大学,2009 Su J. Research of process modeling and parameters optimization for high speed WEDM[D]. Xi'an:Xi'an University of Technology, 2009(in Chinese)
[15]	耿雪松,迟关心,王玉魁,等.碳化硅颗粒增强铝基复合材料微细电火花线切割加工材料去除率研究[J].兵工学报,2014,35(6):891-899 Geng X S, Chi G X, Wang Y K, et al. Research on material removal rate of SiC/Al particulate metal matrix composite by micro-wire electrical discharge machining[J]. Acta Armamentarii, 2014,35(6):891-899(in Chinese)
[16]	李明辉,杨晓欣.数控电火花线切割加工工艺及应用[M].北京:国防工业出版社,2010 Li M H, Yang X X. Machining process and application of NC WEDM[M]. Beijing:National Defense Industry Press, 2010(in Chinese)
[17]	Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm:NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002,6(2):182-197
[18]	Jayaprakasam S, Rahim S K A, Leow C Y, et al. Multiobjective beampattern optimization in collaborative beamforming via NSGA-Ⅱ with selective distance[J]. IEEE Transactions on Antennas and Propagation, 2017,65(5):2348-2357