数控铣削加工工艺参数优化方法综述
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摘要
介绍了铣削力、铣削用量等数控铣削加工工艺参数,分析了材料去除率、表面粗糙度、能耗、铣刀颤振等工艺指标,并给出了数控铣削加工工艺参数的优化目标、优化方法、现有试验研究,以及近似模型。所做研究可以为数控铣削加工工艺参数的选择和优化提供理论参考。
The process parameters for CNC milling such as milling force and milling amount were introduced. The technical indexes such as material removal rate, surface roughness, energy consumption and mill flutter were analyzed. The optimization targets & optimization methods of process parameters for CNC milling, existing experimental studies, and approximate models were given. The research can provide a theoretical reference for the selection and optimization of processing parameters for CNC milling.
The process parameters for CNC milling such as milling force and milling amount were introduced. The technical indexes such as material removal rate, surface roughness, energy consumption and mill flutter were analyzed. The optimization targets & optimization methods of process parameters for CNC milling, existing experimental studies, and approximate models were given. The research can provide a theoretical reference for the selection and optimization of processing parameters for CNC milling.
引文
[1]周济.智能制造---“中国制造2025”的主攻方向[J].中国机械工程,2015,26(17):2273-2284.
[2]李初晔,王海涛,王增新.铣削加工过程中的材料去除率计算[J].工具技术,2016,50(1):55-60.
[3]DRAGANESCU F,GHEORGHE M,DOICIN C V.Models of Machine Tool Efficiency and Specific Consumed Energy[J].Journal of Materials Processing Technology,2003,141(1):9-15.
[4]ZHOU J H,REN J X,YAO C F.Multi-objective Optimization of Multi-axis Ball-end Milling Inconel 718 via Grey Relational Analysis Coupled with RBF Neural Network and PSO Algorithm[J].Measurement,2017,102:271-285.
[5]YILDIZ A R.Cuckoo Search Algorithm for the Selection of Optimal Machining Parameters in Milling Operations[J].The International Journal of Advanced Manufacturing Technology,2013,64(1-4):55-61.
[6]KURAM E,OZCELIK B.Multi-objective Optimization Using Taguchi Based Grey Relational Analysis for Micro-milling of Al 7075 Material with Ball Nose end Mill[J].Measurement,2013,46(6):1849-1864.
[7]马卫东,薛冰.基于P20材料的数控铣削加工参数优化[J].煤矿机械,2014,35(3):106-108.
[8]黄拯滔,杨杰,张超勇,等.面向能耗的数控铣削过程建模与参数优化[J].中国机械工程,2016,27(18):2524-2532.
[9]ZHANG H,DENG Z H,FU Y H,et al.A Process Parameters Optimization Method of Multi-pass Dry Milling for High Efficiency,Low Energy and Low Carbon Emissions[J].Journal of Cleaner Production,2017,148:174-184.
[10]YAN J H,LI L.Multi-objective Optimization of Milling Parameters-The Trade-offs between Energy,Production Rate and Cutting Quality[J].Journal of Cleaner Production,2013,52:462-471.
[11]LIN W W,YU D Y,WANG S,et al.Multi-objective Teaching-Learning-Based Optimization Algorithm for Reducing Carbon Emissions and Operation Time in Turning Operations[J].Engineering Optimization,2015,47(7):994-1007.
[12]MALGHAN R L,RAO K M C,SHETTIGAR A K,et al.Application of Particle Swarm Optimization and Response Surface Methodology for Machining Parameters Optimization of Aluminium Matrix Composites in Milling Operation[J].Journal of the Brazilian Society of Mechanical Sciences and Engineering,2016,39(9):3541-3553.
[13]PEREIRA R B D,LEITE R R,ALVIM A C,et al.Multi=objective Robust Optimization of the Sustainable Helical Milling Process of the Aluminum Alloy Al 7075 Using the Augmented-enhanced Normalized Normal Constraint Method[J].Journal of Cleaner Production,2017,152:474-496.
[14]BHAVSAR S N,ARAVINDAN S,RAO P V.Investigating Material Removal Rate and Surface Roughness Using Multi=objective Optimization for Focused Ion Beam(FIB)Micro=milling of Cemented Carbide[J].Precision Engineering,2015,40:131-138.
[15]KLANCNIK S,HRELJA M,BALIC J,et al.Multi-objective Optimization of the Turning Process Using a Gravitational Search Algorithm(GSA)and NSGA-ⅡApproach[J].Advances in Production Engineering&Management,2016,11(4):366-376.
[16]YANG D,LIU Z Q,REN X P,et al.Hybrid Modeling with Finite Element and Statistical Methods for Residual Stress Prediction in Peripheral Milling of Titanium Alloy Ti-6Al-4V[J].International Journal of Mechanical Sciences,2016,108-109:29-38.
[17]SANTHANAKRISHNAN M,SIVASAKTHIVEL P S,SUDHAKARAN R.Modeling of Geometrical and Machining Parameters on Temperature Rise while Machining Al 6351Using Response Surface Methodology and Genetic Algorithm[J].Journal of the Brazilian Society of Mechanical Sciences and Engineering,2015,39(2):487-496.
[18]DAS B,ROY S,RAI R N,et al.Application of Grey Fuzzy Logic for the Optimization of CNC Milling Parameters for Al-4.5%Cu-TiC MMCs with Multi-performance Characteristics[J].Engineering Science and Technology,An International Journal,2016,19(2):857-865.
[19]KARABULUT S.Optimization of Surface Roughness and Cutting Force during AA7039/Al2O3Metal Matrix Composites Milling Using Neural Networks and Taguchi Method[J].Measurement,2015,66:139-149.
[20]马廉洁,李琛,曹小兵,等.基于GA和DEFORM的陶瓷材料铣削力数值模拟[J].东北大学学报(自然科学版),2014,35(12):1773-1777.
[21]WANG Q L,LIU F,WANG X L.Multi-objective Optimization of Machining Parameters Considering Energy Consumption[J].The International Journal of Advanced Manufacturing Technology,2014,71(5-8):1133-1142.
[22]李聪波,肖溱鸽,李丽,等.基于田口法和响应面法的数控铣削工艺参数能效优化方法[J].计算机集成制造系统,2015,21(12):3182-3191.
[23]ZHANG Y,MABROUKI T,NELIAS D,et al.Cutting Simulation Capabilities Based on Crystal Plasticity Theory and Discrete Cohesive Elements[J].Journal of Materials Processing Technology,2012,212(4):936-953.
[24]周超,李勋,陈五一.钛合金TC4粗加工刀具优选及铣削参数优化[J].航空制造技术,2015(10):70-73,82.
[25]盘家俊,罗樟圳,文章,等.铣削加工仿真及工艺参数优化[J].现代制造技术与装备,2017(5):94-97.
[26]ATLATI S,HADDAG B,NOUARI M,et al.Thermomechanical Modelling of the Tool-Workmaterial Interface in Machining and Its Implementation Using the ABAQUS VUINTER Subroutine[J].International Journal of Mechanical Sciences,2014,87:102-117.
[27]WU H B,ZHANG S J.3D FEM Simulation of Milling Process for Titanium Alloy Ti6Al4V[J].The International Journal of Advanced Manufacturing Technology,2014,71(5-8):1319-1326.
[28]WU H B,ZHANG S J.Effects of Cutting Conditions on the Milling Process of Titanium Alloy Ti6Al4V[J].The International Journal of Advanced Manufacturing Technology,2015,77(9-12):2235-2240.
[29]JI C H,LI Y H,QIN X D,et al.3D FEM Simulation of Helical Milling Hole Process for Titanium Alloy Ti-6Al-4V[J].The International Journal of Advanced Manufacturing Technology,2015,81(9-12):1733-1742.
[30]GAO L,HUANG J D,LI X Y.An Effective Cellular Particle Swarm Optimization for Parameters Optimization of a Multi-pass Milling Process[J].Applied Soft Computing,2012,12(11):3490-3499.
[31]陈国三,黄晓华,陈龙高,等.钛合金Ti6Al4V高速铣削三维有限元仿真分析[J].组合机床与自动化加工技术,2016(4):43-46.
[32]THEPSONTHI T,OZEL T.3-D Finite Element Process Simulation of Micro-end Milling Ti-6Al-4V Titanium Alloy:Experimental Validations on Chip Flow and Tool Wear[J].Journal of Materials Processing Technology,2015,221:128-145.
[33]黄政,陈为国.基于VERICUT的数控铣床仿真与优化[J].航空制造技术,2015(15):42-45.
[34]陈贞奇,刘涛.基于VERICUT软件的数控加工中两道工序合并翻面模拟仿真及参数设置[J].新技术新工艺,2015(3):47-49.
[35]羊毅,钱俊宏,朱平平.基于AdvantEdge 3D的7075铝合金加工每齿进给量对铣削力和温度的影响的仿真研究[J].科技风,2015(13):82.
[36]晏升辉,张海鸥,王桂兰,等.基于OpenGL的五轴数控铣削仿真[J].机械制造,2012,50(2):45-47.
[37]ZONG W J,LI Z Q,ZHANG L,et al.Finite Element Simulation of Diamond Tool Geometries Affecting the 3DSurface Topography in Fly Cutting of KDP Crystals[J].The International Journal of Advanced Manufacturing Technology,2013,68(9-12):1927-1936.
[38]KIVAK T.Optimization of Surface Roughness and Flank Wear Using the Taguchi Method in Milling of Hadfield Steel with PVD and CVD Coated Inserts[J].Measurement,2014,50:19-28.
[39]KLEIJNEN J P C.Regression Metamodels for Generalizing Simulation Results[J].IEEE Transactions on Systems,Man,and Cybernetics,1979,9(2):93-96.
[40]KLEIJNEN J P C.The Role of Statistical Methodology in Simulation[J].ACM SIGSIM Simulation Digest,1978,10(1-2):51-52.
[41]KLEIJNEN J P C.Statistical Tools for Simulation Practitioners[M].New York:Marcel Dekker,Inc,1987.
[42]SEN O,GAUL N J,CHOI K K,et al.Evaluation of Kriging Based Surrogate Models Constructed from Mesoscale Computations of Shock Interaction with Particles[J].Journal of Computational Physics,2017,336:235-260.
[43]WANG Z L,IERAPETRITOU M.A Novel Feasibility Analysis Method for Black-box Processes Using a Radial Basis Function Adaptive Sampling Approach[J].AIChEJournal,2017,63(2):532-550.
[44]MIRZAEI D.Analysis of Moving Least Squares Approximation Revisited[J].Journal of Computational and Applied Mathematics,2015,282:237-250.
[45]DONG L T,HAYNES R,ATLURI S N.On Improving the Celebrated Paris’Power Law for Fatigue,by Using Moving Least Squares[J].Computers,Materials and Continua,2015,45(1):1-15.
[46]黄健.数控铣削工艺参数优化研究[J].时代农机,2017,44(2):31-32.
[47]CHASKAR P R,LAD A S,MANE J K,et al.Optimization of CNC Milling Parameters Using“Artificial Neural Network”[J].Imperial Journal of Interdisciplinary Research,2017,3(2):683-687.
[48]LI L,LIU F,CHEN B,et al.Multi-objective Optimization of Cutting Parameters in Sculptured Parts Machining Based on Neural Network[J].Journal of Intelligent Manufacturing,2015,26(5):891-898.
[49]LI C B,CHEN X Z,TANG Y,et al.Selection of Optimum Parameters in Multi-pass Face Milling for Maximum Energy Efficiency and Minimum Production Cost[J].Journal of Cleaner Production,2017,140:1805-1818.
[50]祁雪沙,戚厚军.基于遗传算法的数控铣削参数优化[J].煤矿机械,2015,36(11):143-145.
[51]沈宏.基于SP-ABC算法的数控铣削参数优化[J].航空制造技术,2016(8):105-109.
[52]李爱平,鲍进,李聪,等.基于低能耗的平面端铣削粗/精加工参数全局多目标优化[J].中国机械工程,2015,26(14):1888-1894.
[2]李初晔,王海涛,王增新.铣削加工过程中的材料去除率计算[J].工具技术,2016,50(1):55-60.
[3]DRAGANESCU F,GHEORGHE M,DOICIN C V.Models of Machine Tool Efficiency and Specific Consumed Energy[J].Journal of Materials Processing Technology,2003,141(1):9-15.
[4]ZHOU J H,REN J X,YAO C F.Multi-objective Optimization of Multi-axis Ball-end Milling Inconel 718 via Grey Relational Analysis Coupled with RBF Neural Network and PSO Algorithm[J].Measurement,2017,102:271-285.
[5]YILDIZ A R.Cuckoo Search Algorithm for the Selection of Optimal Machining Parameters in Milling Operations[J].The International Journal of Advanced Manufacturing Technology,2013,64(1-4):55-61.
[6]KURAM E,OZCELIK B.Multi-objective Optimization Using Taguchi Based Grey Relational Analysis for Micro-milling of Al 7075 Material with Ball Nose end Mill[J].Measurement,2013,46(6):1849-1864.
[7]马卫东,薛冰.基于P20材料的数控铣削加工参数优化[J].煤矿机械,2014,35(3):106-108.
[8]黄拯滔,杨杰,张超勇,等.面向能耗的数控铣削过程建模与参数优化[J].中国机械工程,2016,27(18):2524-2532.
[9]ZHANG H,DENG Z H,FU Y H,et al.A Process Parameters Optimization Method of Multi-pass Dry Milling for High Efficiency,Low Energy and Low Carbon Emissions[J].Journal of Cleaner Production,2017,148:174-184.
[10]YAN J H,LI L.Multi-objective Optimization of Milling Parameters-The Trade-offs between Energy,Production Rate and Cutting Quality[J].Journal of Cleaner Production,2013,52:462-471.
[11]LIN W W,YU D Y,WANG S,et al.Multi-objective Teaching-Learning-Based Optimization Algorithm for Reducing Carbon Emissions and Operation Time in Turning Operations[J].Engineering Optimization,2015,47(7):994-1007.
[12]MALGHAN R L,RAO K M C,SHETTIGAR A K,et al.Application of Particle Swarm Optimization and Response Surface Methodology for Machining Parameters Optimization of Aluminium Matrix Composites in Milling Operation[J].Journal of the Brazilian Society of Mechanical Sciences and Engineering,2016,39(9):3541-3553.
[13]PEREIRA R B D,LEITE R R,ALVIM A C,et al.Multi=objective Robust Optimization of the Sustainable Helical Milling Process of the Aluminum Alloy Al 7075 Using the Augmented-enhanced Normalized Normal Constraint Method[J].Journal of Cleaner Production,2017,152:474-496.
[14]BHAVSAR S N,ARAVINDAN S,RAO P V.Investigating Material Removal Rate and Surface Roughness Using Multi=objective Optimization for Focused Ion Beam(FIB)Micro=milling of Cemented Carbide[J].Precision Engineering,2015,40:131-138.
[15]KLANCNIK S,HRELJA M,BALIC J,et al.Multi-objective Optimization of the Turning Process Using a Gravitational Search Algorithm(GSA)and NSGA-ⅡApproach[J].Advances in Production Engineering&Management,2016,11(4):366-376.
[16]YANG D,LIU Z Q,REN X P,et al.Hybrid Modeling with Finite Element and Statistical Methods for Residual Stress Prediction in Peripheral Milling of Titanium Alloy Ti-6Al-4V[J].International Journal of Mechanical Sciences,2016,108-109:29-38.
[17]SANTHANAKRISHNAN M,SIVASAKTHIVEL P S,SUDHAKARAN R.Modeling of Geometrical and Machining Parameters on Temperature Rise while Machining Al 6351Using Response Surface Methodology and Genetic Algorithm[J].Journal of the Brazilian Society of Mechanical Sciences and Engineering,2015,39(2):487-496.
[18]DAS B,ROY S,RAI R N,et al.Application of Grey Fuzzy Logic for the Optimization of CNC Milling Parameters for Al-4.5%Cu-TiC MMCs with Multi-performance Characteristics[J].Engineering Science and Technology,An International Journal,2016,19(2):857-865.
[19]KARABULUT S.Optimization of Surface Roughness and Cutting Force during AA7039/Al2O3Metal Matrix Composites Milling Using Neural Networks and Taguchi Method[J].Measurement,2015,66:139-149.
[20]马廉洁,李琛,曹小兵,等.基于GA和DEFORM的陶瓷材料铣削力数值模拟[J].东北大学学报(自然科学版),2014,35(12):1773-1777.
[21]WANG Q L,LIU F,WANG X L.Multi-objective Optimization of Machining Parameters Considering Energy Consumption[J].The International Journal of Advanced Manufacturing Technology,2014,71(5-8):1133-1142.
[22]李聪波,肖溱鸽,李丽,等.基于田口法和响应面法的数控铣削工艺参数能效优化方法[J].计算机集成制造系统,2015,21(12):3182-3191.
[23]ZHANG Y,MABROUKI T,NELIAS D,et al.Cutting Simulation Capabilities Based on Crystal Plasticity Theory and Discrete Cohesive Elements[J].Journal of Materials Processing Technology,2012,212(4):936-953.
[24]周超,李勋,陈五一.钛合金TC4粗加工刀具优选及铣削参数优化[J].航空制造技术,2015(10):70-73,82.
[25]盘家俊,罗樟圳,文章,等.铣削加工仿真及工艺参数优化[J].现代制造技术与装备,2017(5):94-97.
[26]ATLATI S,HADDAG B,NOUARI M,et al.Thermomechanical Modelling of the Tool-Workmaterial Interface in Machining and Its Implementation Using the ABAQUS VUINTER Subroutine[J].International Journal of Mechanical Sciences,2014,87:102-117.
[27]WU H B,ZHANG S J.3D FEM Simulation of Milling Process for Titanium Alloy Ti6Al4V[J].The International Journal of Advanced Manufacturing Technology,2014,71(5-8):1319-1326.
[28]WU H B,ZHANG S J.Effects of Cutting Conditions on the Milling Process of Titanium Alloy Ti6Al4V[J].The International Journal of Advanced Manufacturing Technology,2015,77(9-12):2235-2240.
[29]JI C H,LI Y H,QIN X D,et al.3D FEM Simulation of Helical Milling Hole Process for Titanium Alloy Ti-6Al-4V[J].The International Journal of Advanced Manufacturing Technology,2015,81(9-12):1733-1742.
[30]GAO L,HUANG J D,LI X Y.An Effective Cellular Particle Swarm Optimization for Parameters Optimization of a Multi-pass Milling Process[J].Applied Soft Computing,2012,12(11):3490-3499.
[31]陈国三,黄晓华,陈龙高,等.钛合金Ti6Al4V高速铣削三维有限元仿真分析[J].组合机床与自动化加工技术,2016(4):43-46.
[32]THEPSONTHI T,OZEL T.3-D Finite Element Process Simulation of Micro-end Milling Ti-6Al-4V Titanium Alloy:Experimental Validations on Chip Flow and Tool Wear[J].Journal of Materials Processing Technology,2015,221:128-145.
[33]黄政,陈为国.基于VERICUT的数控铣床仿真与优化[J].航空制造技术,2015(15):42-45.
[34]陈贞奇,刘涛.基于VERICUT软件的数控加工中两道工序合并翻面模拟仿真及参数设置[J].新技术新工艺,2015(3):47-49.
[35]羊毅,钱俊宏,朱平平.基于AdvantEdge 3D的7075铝合金加工每齿进给量对铣削力和温度的影响的仿真研究[J].科技风,2015(13):82.
[36]晏升辉,张海鸥,王桂兰,等.基于OpenGL的五轴数控铣削仿真[J].机械制造,2012,50(2):45-47.
[37]ZONG W J,LI Z Q,ZHANG L,et al.Finite Element Simulation of Diamond Tool Geometries Affecting the 3DSurface Topography in Fly Cutting of KDP Crystals[J].The International Journal of Advanced Manufacturing Technology,2013,68(9-12):1927-1936.
[38]KIVAK T.Optimization of Surface Roughness and Flank Wear Using the Taguchi Method in Milling of Hadfield Steel with PVD and CVD Coated Inserts[J].Measurement,2014,50:19-28.
[39]KLEIJNEN J P C.Regression Metamodels for Generalizing Simulation Results[J].IEEE Transactions on Systems,Man,and Cybernetics,1979,9(2):93-96.
[40]KLEIJNEN J P C.The Role of Statistical Methodology in Simulation[J].ACM SIGSIM Simulation Digest,1978,10(1-2):51-52.
[41]KLEIJNEN J P C.Statistical Tools for Simulation Practitioners[M].New York:Marcel Dekker,Inc,1987.
[42]SEN O,GAUL N J,CHOI K K,et al.Evaluation of Kriging Based Surrogate Models Constructed from Mesoscale Computations of Shock Interaction with Particles[J].Journal of Computational Physics,2017,336:235-260.
[43]WANG Z L,IERAPETRITOU M.A Novel Feasibility Analysis Method for Black-box Processes Using a Radial Basis Function Adaptive Sampling Approach[J].AIChEJournal,2017,63(2):532-550.
[44]MIRZAEI D.Analysis of Moving Least Squares Approximation Revisited[J].Journal of Computational and Applied Mathematics,2015,282:237-250.
[45]DONG L T,HAYNES R,ATLURI S N.On Improving the Celebrated Paris’Power Law for Fatigue,by Using Moving Least Squares[J].Computers,Materials and Continua,2015,45(1):1-15.
[46]黄健.数控铣削工艺参数优化研究[J].时代农机,2017,44(2):31-32.
[47]CHASKAR P R,LAD A S,MANE J K,et al.Optimization of CNC Milling Parameters Using“Artificial Neural Network”[J].Imperial Journal of Interdisciplinary Research,2017,3(2):683-687.
[48]LI L,LIU F,CHEN B,et al.Multi-objective Optimization of Cutting Parameters in Sculptured Parts Machining Based on Neural Network[J].Journal of Intelligent Manufacturing,2015,26(5):891-898.
[49]LI C B,CHEN X Z,TANG Y,et al.Selection of Optimum Parameters in Multi-pass Face Milling for Maximum Energy Efficiency and Minimum Production Cost[J].Journal of Cleaner Production,2017,140:1805-1818.
[50]祁雪沙,戚厚军.基于遗传算法的数控铣削参数优化[J].煤矿机械,2015,36(11):143-145.
[51]沈宏.基于SP-ABC算法的数控铣削参数优化[J].航空制造技术,2016(8):105-109.
[52]李爱平,鲍进,李聪,等.基于低能耗的平面端铣削粗/精加工参数全局多目标优化[J].中国机械工程,2015,26(14):1888-1894.