The goal of this research is to identify the best set of process machining parameters for wire-EDM(Electrical Discharge Machining)cutting of hardened SKD11 steel when machining a curve profile.The multi-objective func...The goal of this research is to identify the best set of process machining parameters for wire-EDM(Electrical Discharge Machining)cutting of hardened SKD11 steel when machining a curve profile.The multi-objective function includes reducing surface roughness and increasing MRR(Material Removal Rate).The optimization process is prepared by using Taguchi method coupled Grey Relational Analysis.The obtained results revealed that Toff has the greatest influence on the average grey value(48.30%),followed by the influence of WF(Wire Feed,15.99%),VM(Cutting Voltage,9.33%),SV(Server Voltage,5.05%),Ton(Pulse on Time,1.81%),while SPD(Cutting Speed)has a negligible effect(0.89%).Moreover,using the optimal set of machining parameters generates in surface roughness of 1.25399mm and MRR of 26.5562 mm^(2)/min.The verification experiment and Anderson-Darling method demonstrate the validity of the proposed model,which can be utilized for estimating surface roughness and MRR.展开更多
为有效控制和预测高硬度模具钢加工的表面质量和加工效率,通过设计正交切削试验,研究了在不同切削参数组合(主轴转速、进给速度、轴向切削深度和径向切削深度)及冷却润滑方式条件下、Ti Si N涂层刀具对模具钢SKD11(62HRC)的高速铣削。应...为有效控制和预测高硬度模具钢加工的表面质量和加工效率,通过设计正交切削试验,研究了在不同切削参数组合(主轴转速、进给速度、轴向切削深度和径向切削深度)及冷却润滑方式条件下、Ti Si N涂层刀具对模具钢SKD11(62HRC)的高速铣削。应用BP神经网络原理建立表面粗糙度预测模型,并进行试验验证其准确性。研究表明,在不同加工条件下,基于BP神经网络模型建立的涂层刀具铣削模具钢SKD11表面粗糙度模型有较好的预测精度,其预测误差在3.45%-6.25%之间,对于模具制造企业选择加工工艺参数、控制加工质量和降低加工成本有重要意义。展开更多
In this study, AlTiN coatings were deposited on YT14 cemented carbide balls by arc ion plating technique. The friction and wear behavior of the AlTiN-coated balls against SKD11 hardened steel was investigated by slidi...In this study, AlTiN coatings were deposited on YT14 cemented carbide balls by arc ion plating technique. The friction and wear behavior of the AlTiN-coated balls against SKD11 hardened steel was investigated by sliding tests using a ball-ondisk tribometer at various temperatures from 25 to 700 ℃ in air. The results showed that the friction and wear behavior was significantly influenced by the testing temperature. Obvious fluctuations were observed in the friction curves at elevated temperatures, which could be attributed to the formation and rupture of unstable Fe and Cr oxide layers. As the temperature increased from 25 to 500 ~C, the wear rate of the coated balls increased from the scale of 10-21-10-20 m3/ N m, and then decreased to 10-22 m3/N m as the temperature further increased to 700℃. It was also found that the friction and wear behavior of the coated balls was directly dependent on the counterpart materials. As the temperature increased, the main wear mechanism of the coated balls changed from mild abrasive wear and adhesive wear to abrasive wear failure at 500℃, and then transferred to adhesive wear and mild oxidation wear at 700℃. For SKD11 hardened steel, the primary wear mechanism changed from delamination wear to abrasive wear and then transferred to plastic deformation and fatigue wear, accompanied by adhesive wear and tribo-oxidation wear.展开更多
文摘The goal of this research is to identify the best set of process machining parameters for wire-EDM(Electrical Discharge Machining)cutting of hardened SKD11 steel when machining a curve profile.The multi-objective function includes reducing surface roughness and increasing MRR(Material Removal Rate).The optimization process is prepared by using Taguchi method coupled Grey Relational Analysis.The obtained results revealed that Toff has the greatest influence on the average grey value(48.30%),followed by the influence of WF(Wire Feed,15.99%),VM(Cutting Voltage,9.33%),SV(Server Voltage,5.05%),Ton(Pulse on Time,1.81%),while SPD(Cutting Speed)has a negligible effect(0.89%).Moreover,using the optimal set of machining parameters generates in surface roughness of 1.25399mm and MRR of 26.5562 mm^(2)/min.The verification experiment and Anderson-Darling method demonstrate the validity of the proposed model,which can be utilized for estimating surface roughness and MRR.
文摘为有效控制和预测高硬度模具钢加工的表面质量和加工效率,通过设计正交切削试验,研究了在不同切削参数组合(主轴转速、进给速度、轴向切削深度和径向切削深度)及冷却润滑方式条件下、Ti Si N涂层刀具对模具钢SKD11(62HRC)的高速铣削。应用BP神经网络原理建立表面粗糙度预测模型,并进行试验验证其准确性。研究表明,在不同加工条件下,基于BP神经网络模型建立的涂层刀具铣削模具钢SKD11表面粗糙度模型有较好的预测精度,其预测误差在3.45%-6.25%之间,对于模具制造企业选择加工工艺参数、控制加工质量和降低加工成本有重要意义。
基金supported in part by the projects of the National Natural Science Foundation of China(Grant No.51522502)the China Postdoctoral Science Foundation funded project(No.2016M600641)the Guangdong Natural Science Funds(Nos.2014A030311002 and 2016A050502056)
文摘In this study, AlTiN coatings were deposited on YT14 cemented carbide balls by arc ion plating technique. The friction and wear behavior of the AlTiN-coated balls against SKD11 hardened steel was investigated by sliding tests using a ball-ondisk tribometer at various temperatures from 25 to 700 ℃ in air. The results showed that the friction and wear behavior was significantly influenced by the testing temperature. Obvious fluctuations were observed in the friction curves at elevated temperatures, which could be attributed to the formation and rupture of unstable Fe and Cr oxide layers. As the temperature increased from 25 to 500 ~C, the wear rate of the coated balls increased from the scale of 10-21-10-20 m3/ N m, and then decreased to 10-22 m3/N m as the temperature further increased to 700℃. It was also found that the friction and wear behavior of the coated balls was directly dependent on the counterpart materials. As the temperature increased, the main wear mechanism of the coated balls changed from mild abrasive wear and adhesive wear to abrasive wear failure at 500℃, and then transferred to adhesive wear and mild oxidation wear at 700℃. For SKD11 hardened steel, the primary wear mechanism changed from delamination wear to abrasive wear and then transferred to plastic deformation and fatigue wear, accompanied by adhesive wear and tribo-oxidation wear.
