基于响应曲面法与改进非支配遗传算法电火花线切割单晶硅工艺优化
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摘要
单晶硅加工过程中追求切削效率与表面质量既可以提高晶圆自身品质又可以降低生产成本。通过响应曲面法(RSM)建立关于输入参数电压、脉宽、脉间、线锯速度与工艺结果的二阶模型,方差分析表明模型方程可行性。运用改进非支配遗传算法(NSGA-II)对加工工艺进行优化可以得到一组关于工艺结果的非支配解,这些非支配解可以满足不同条件下工程加工者的需要。进行相应实验验证非支配解可行。
Pursuiting cutting efficiency and surface quality during machining monocrystalline silicon can improve the quality of the wafer itself and reduce the production cost. The second-order model of variable parameter voltage,pulse on time,pulse interval,wire saw speed and process result is established by response surface method,The variance analysis shows that the model equation is significant. The improved non-dominated genetic algorithm( NSGA-II) is used to optimize processing process,and we can get a set of non-dominated solutions. These non-dominated solutions can satisfy the needs of engineering workers under different conditions. The corresponding experimental proving the non-dominated solution is feasible.
Pursuiting cutting efficiency and surface quality during machining monocrystalline silicon can improve the quality of the wafer itself and reduce the production cost. The second-order model of variable parameter voltage,pulse on time,pulse interval,wire saw speed and process result is established by response surface method,The variance analysis shows that the model equation is significant. The improved non-dominated genetic algorithm( NSGA-II) is used to optimize processing process,and we can get a set of non-dominated solutions. These non-dominated solutions can satisfy the needs of engineering workers under different conditions. The corresponding experimental proving the non-dominated solution is feasible.
引文
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[2]Abbas N M,Solomon D G,Bahari M F.A review on current research trends in electrical discharge machining(EDM)[J].International Journal of machine tools and Manufacture,2007,47(7):1214-1228.
[3]李淑娟,刘永,侯晓莉.Si C单晶片加工过程中切割力的分析与建模[J].机械工程学报,2015,51(23):189-195.LI ShuJuan,LIU Yong,HOU Xiao Li.Analysis and modeling of cutting force in the process of Si C monocrystalline machining[J].Journal of Mechanical Engineering,2015,51(23):189-195(In Chinese).
[4]康仁科,田业冰,郭东明.大直径硅片超精密磨削技术的研究与应用现状[J].金刚石与磨料磨具工程,2003(4):13-18.KANG Ren Ke,TIAN YouBing,GUO DongMing.Research and application status of ultra-precision grinding technology for large diameter silicon wafer[J].Diamond&Abrasives Engineering,2003(4):13-18(In Chinese).
[5]Okada A,Uno Y,Okamoto Y,et al.A New Slicing Method of Monocrystalline Silicon Ingot by Wire EDM[J].Journal of the Japan Society of Electrical-machining Engineers,1998,34(75):14-21.
[6]Uno Y,Okada A,Okamoto Y,et al.High Performance Slicing Method of Monocrystalline Silicon Ingot by Wire EDM[J].Denki Kako Gakkaishi,2001,34(1405):219-223.
[7]Richard F G..Response surface methodology:process and product optimization using designed experiments,Technometrics,1996,38(3),284-286.
[8]Deb K,Pratap A,Agarwal S.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE transactions on evolutionary computation,2002,6(2):182-197.
[9]Srinivas N,Deb K.Muiltiobjective optimization using nondominated sorting in genetic algorithms[J].Evolutionary computation,1994,2(3):221-248.
[10]Tappeta R V,Renaud J E,Messac A,et al.Interactive physical programming:tradeoff analysis and decision making in multicriteria optimization[J].AIAA journal,2000,38(5):917-926.
[11]Tavakkoli-Moghaddam R,Rahimi-Vahed A R,Mirzaei A H.Solving a multi-objective no-wait flow shop scheduling problem with an immune algorithm[J].The International Journal of Advanced Manufacturing Technology,2008,36(9-10):969-981.
[12]杨慧娜,张永帅,刘钢.基于改进的二代非支配排序遗传算法对电子变压器多目标优化[J].科学技术与工程,2015(19):139-145.YANG Hui Na,ZHANG Yong Shuai,LIU Gang.Multi-objective optimization of electronic transformer based on improved secondgeneration non-dominated sorting genetic algorithm[J].Science Technology and Engineering,2015(19):139-145(In Chinese).
[13]Myers R H,Montgomery D C,Vining G G,et al.Response surface methodology:a retrospective and literature survey[J].Journal of quality technology,2004,36(1):53.