高速车削镍基高温合金GH4169的切削力仿真研究

基于Deform 3D仿真软件建立了GH4169高温合金高速车削的有限元模型,采用四因素三水平正交试验方法研究了切削用量和刀具几何参数对切削力的影响规律,并建立了切削力经验公式。研究结果表明:在高速车削GH4169的过程中,对切削力影响最大的参数是切削深度,其次是进给量和前角,最后是刀尖圆弧半径;切削力随切削深度和进给量的增大而增大,随前角的增大呈现先降低又升高的趋势,而刀尖圆弧半径增大时切削力变化不大;最佳参数组合为:进给量0.2mm/r,切削深度0.4mm,前角10°,刀尖圆弧半径0.2mm。     

Optimization of end mill tool geometry parameters for Al7075-T6 machining operations based on vibration amplitude by response surface methodology

This paper aims at developing a statistical model to envisage vibration amplitude in terms of geometrical parameters such as radial rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Experiments were conducted through response surface methodology experimental design. The material chosen is Aluminum (Al 7075-T6) and the tool used was high speed steel end mill cutter with different tool geometry. Two channels piezoelectric accelerometers were used to measure the vibration amplitude. The second order mathematical model in terms of machining parameters was built up to predict the vibration amplitude and ANOVA was used to verify the competency of the model. Further investigation on the direct and interactive effect of the process parameter with vibration amplitude was carried out for the selection of process parameter so that the vibration amplitude was maintained at the minimum which ensures the stability of end milling process. The optimum values obtained from end milling process are Radial rake angle-12°, Nose radius-0.8 mm, Cutting speed-115 m/min, Cutting feed rate-0.04 mm/tooth, axial depth of cut-2.5 mm. The vibration amplitude exhibited negative relationship with radial rake angle and nose radius. The dominant factors on the vibration amplitude are feed rate and depth of cut. Thus it is envisaged that the predictive models in this study could produce values of the vibration amplitude close to the experimental readings with a 95% confidence interval.     

Multiple-response optimization of turning machining by the taguchi method and the utility concept using uni-directional glass fiber-reinforced plastic composite and carbide (k10) cutting tool

This paper presents a utility concept for multi-response optimization in turning uni-directional glass fiber-reinforced plastics composite using Carbide (K10) cutting tool. The single response optimization resulted in the non-optimization of other responses. The Taguchi method (Orthogonal L₁₈ array) was employed in the experimental work. The process parameters selected for this study were tool nose radius, tool rake angle, feed rate, cutting speed, depth of cut, and cutting environment. Statistically significant parameters were found to simultaneously minimize surface roughness and maximize the material removal rate by ANOVA. The results were further verified by confirmation experiments.     

An empirical survey on the influence of machining parameters on tool wear in diamond turning of large single-crystal silicon optics

We conducted a series of screening experiments to survey the influence of machining parameters on tool wear during ductile regime diamond turning of large single-crystal silicon optics. The machining parameters under investigation were depth-of-cut, feed rate, surface cutting speed, tool radius, tool rake angle and side rake angle, and cutting fluid. Using an experimental design technique, we selected twenty-two screening experiments. For each experiment we measured tool wear by tracing the tool edge with an air bearing linear variable differential transformer before and after cutting and recording the amount of tool edge recession. Using statistical tools, we determined the significance of each cutting parameter within the parameter space investigated. We found that track length, chip size, tool rake angle and surface cutting speed significantly affect tool wear, while cutting fluid and side rake angle do not significantly affect tool wear within the ranges tested. The track length, or machining distance, is the single most influential characteristic that causes tool wear. For a fixed part area, a decrease in track length corresponds to an increase in feed rate. Less tool wear occurred on experiments with negative rake angle tools, larger chip sizes and higher surface velocities. The next step in this research is to perform more experiments in this region to develop a predictive model that can be used to select cutting parameters that minimize tool wear.     

[刀具及切削工艺]典型钛合金TC17车削过程鳞刺生成规律及其抑制措施

为研究钛合金车削过程中鳞刺生成规律及有效抑制措施,分析了影响鳞刺生成的主要因素,采用弯矩法解析了鳞刺折断规律,进而建立了切削参数、刀具几何参数与刀尖弯矩的数学描述模型;通过MATLAB对模型进行求解,获知切削速度对刀尖弯矩的影响最小,而切削深度、进给量、刀尖圆弧以及刀具主偏角4个因素决定了刀尖弯矩的大小。为验证描述模型的正确性,进行了典型钛合金TC17外圆周断续切削实验,采集在恒定切削速度、不同切削深度、不同进给量、不同主偏角及不同刀尖圆弧条件下的鳞刺样本数据,并获得鳞刺折断规律曲线。实验结果表明：在小于临界切削深度和大于临界进给量条件下,实验结果与数学描述模型整体趋势一致,证明了数学描述模型的正确性。研究结果可为钛合金的高品质加工提供工艺技术及刀具优选方面的数据支撑。     

基于实验Inconel718正交切削有限元仿真分析

为研究犁削效应和前刀面粘压对Inconel718切削过程的影响.基于正交切削实验建立Inconel718有限元切削模型,模型结果同实验值对比以验证模型可靠性.通过改变刀具圆角半径和负前角参数,提取并比较不同的切削力时域曲线和刀具温度,分析犁削效应和前刀面粘压.研究表明犁削效应提高进给力数值,刀具圆角半径由0变为5μm,Inconel718切削进给力均值提高7％：前刀面粘压提高刀具和切屑温度,有利于切屑分离.但刀具负前角为-20＆#176;,切削加工不稳定.     

Blend of sharpness and strength on a ball nose endmill geometry for high speed machining of Ti6Al4V

The applications of titanium alloys are increasingly common at marine, aerospace, bio-medical and precision engineering due to its high strength to weight ratio and high temperature-withstanding properties. However, whilst machining the titanium alloys using the solid carbide tools, even with application of high pressure coolant, reduced tool life was widely reported. The generation of high temperatures at the tool–work interface causes adhesion of work material on the cutting edges, and hence, shorter tool life was reported. In order to reduce the high tool–work interface temperature-positive rake angle, higher primary relief and higher secondary relief were configured on the ball nose endmill cutting edges. Despite of careful consideration of tool geometry, after an initial working period, the growth of flank wear accelerates the high cutting forces followed by work material adhesion on the cutting edges. Hence, it is important to blend the strength, sharpness, geometry and surface integrity on the cutting edges so that the ball nose endmill would exhibit an extended tool life. This paper illustrates the effect of ball nose endmill geometry on high speed machining of Ti6Al4V. Three different ball nose endmill geometries were configured, and high speed machining experiments were conducted to study the influence of cutting tool geometry on the metal cutting mechanism of Ti-6Al-4V alloy. The high speed machining results predominantly emphasize the significance of cutting edge features such as K-land, rake angle and cutting edge radius. The ball nose endmills featured with a short negative rake angle of value ?5° for 0.05～0.06 mm, i.e. K-land followed by positive rake angle of value 8°, has produced lower cutting forces signatures for Ti-6Al-4V alloy.     

Experimental observations on surface roughness, chip morphology, and tool wear behavior in machining Fe-based amorphous alloy overlay for remanufacture

Fe-based amorphous alloy, a new-type material, was developed as a special-purpose welt overlay for remanufacture. It was deposited on the worn-out part for resuming and upgrading part performance. The microstructure characteristics of the overlay was characterized, including microstructure, phase composition, thermostability, and microhardness. In order to get a comprehensive insight to the machining process of amorphous overlay, this paper presents an experimental investigation into the effect of various machining parameters and tool geometry (Edge) on the surface roughness, tool wear, chip morphology, and surface damage. Comparing larger rake angle of 15°and smaller nose radius of 0.4 mm with 5° and 0.8 mm at the same cutting parameters, we found that larger rake angle of 15° and smaller nose radius of 0.4 mm increased the R _a surface roughness parameter. In the tests, crater wear was not observed, and the friction and wear on the minor cutting edge wear were heavy due to the spring back of the machined surface. In brief,abrasion, adhesion, fatigue, and chipping are the main wear mechanism. As the feed rate reduced and the depth of cut increased (from feed rate?=?0.06 mm/rev and depth of cut?=?0.3 mm to feed rate?=?0.09 mm/rev and depth of cut?=?0.2 mm), a number of physical changes occurred in the chip including reduced distance between serrations, increased shear band angle, and changed chip morphology from spiral to ribbon shape. The results show that strain and strain rate rises in the chips’ inside with the increase in cutting temperature. When the thermal softening exceeded strain hardening, the shear resistance decreased rapidly. Thus, the free surface of the chip presents the nodular and lamella structure. It was noted that specimens generated by larger rake angle of 15° and smaller nose radius of 0.4 mm showed poor surface roughness as well as extensive surface damage.     

FUZZY CLUSTERING MODELLING FOR SURFACE FINISH PREDICTION IN FINE TURNING PROCESS

ABSTRACT

In this paper, fuzzy subtractive clustering based system identification and Sugeno type fuzzy inference system are used to model the surface finish of the machined surfaces in fine turning process to develop a better understanding of the effect of process parameters on surface quality. Such an understanding can provide insight into the problems of controlling the quality of the machined surface when the process parameters are adjusted to obtain certain characteristics. Surface finish data were generated for aluminum alloy 390 (73 BHN), ductile cast iron (186 BHN), and inconel 718 (BHN 335) for a wide range of machining conditions defined by cutting speed, cutting feed rate and cutting tool nose radius. These data were used to develop a surface finish prediction fuzzy clustering model as a function of hardness of the machined material, cutting speed, cutting feed rate, and cutting tool nose radius. Surface finish of the machined part is the output of the process. The model building process is carried out by using fuzzy subtracting clustering based system identification in both input and output space. Minimum error is obtained through numerous searches of clustering parameters. The fuzzy logic model is capable of predicting the surface finish for a given set of inputs (workpiece hardness, cutting speed, cutting feed rate and nose radius of the cutting tool). As such, the machinist may predict the quality of the surface for a given set of working parameters and may also set the process parameters to achieve a certain surface finish. The model is verified experimentally by further experimentation using different sets of inputs. This study deals with the experimental results obtained during fine turning operation. The findings indicate that while the effects of cutting feed and tool nose radius on surface finish were generally consistent for all materials, the effect of cutting speed was not. The surface finish improved for aluminum alloy and ductile cast iron but it deteriorated with speed for inconel.     

A FINITE ELEMENT ANALYSIS OF BURR FORMATION IN FACE MILLING OF A CAST ALUMINUM ALLOY

The research discussed in this article focuses on the effects of tool geometry (i.e., rake angle and cutting edge radius) and flank wear upon burr formation in face milling of a cast aluminum alloy. As to tool edge preparation, the use of a tool with variable cutting edge radius was investigated using FEM, and compared for its cutting performance (i.e., burr reduction and tool life) with a conventional tool with uniform cutting edge radius. In order to evaluate 3D face milling through 2D orthogonal cutting simulations, the cross-sections that consist in the cutting speed direction and chip flow direction were selected at different locations along the tool rounded corner. At these cross-sections, the local value of cutting edge radius and their associated tool rake angles as well as the effective uncut chip thickness were determined for 2D cutting simulations. In addition, 3D face milling simulations were conducted to investigate more realistic chip flow and burr generation. Comparisons were made for burrs produced from 3D simulations with a sharp tool, 3D simulations with a worn tool and face milling experiments. Finally, recommendations for cutting tool design are made to reduce burr formation in face milling.     

FUZZY CLUSTERING MODELLING FOR SURFACE FINISH PREDICTION IN FINE TURNING PROCESS

In this paper, fuzzy subtractive clustering based system identification and Sugeno type fuzzy inference system are used to model the surface finish of the machined surfaces in fine turning process to develop a better understanding of the effect of process parameters on surface quality. Such an understanding can provide insight into the problems of controlling the quality of the machined surface when the process parameters are adjusted to obtain certain characteristics. Surface finish data were generated for aluminum alloy 390 (73 BHN), ductile cast iron (186 BHN), and inconel 718 (BHN 335) for a wide range of machining conditions defined by cutting speed, cutting feed rate and cutting tool nose radius. These data were used to develop a surface finish prediction fuzzy clustering model as a function of hardness of the machined material, cutting speed, cutting feed rate, and cutting tool nose radius. Surface finish of the machined part is the output of the process. The model building process is carried out by using fuzzy subtracting clustering based system identification in both input and output space. Minimum error is obtained through numerous searches of clustering parameters. The fuzzy logic model is capable of predicting the surface finish for a given set of inputs (workpiece hardness, cutting speed, cutting feed rate and nose radius of the cutting tool). As such, the machinist may predict the quality of the surface for a given set of working parameters and may also set the process parameters to achieve a certain surface finish. The model is verified experimentally by further experimentation using different sets of inputs. This study deals with the experimental results obtained during fine turning operation. The findings indicate that while the effects of cutting feed and tool nose radius on surface finish were generally consistent for all materials, the effect of cutting speed was not. The surface finish improved for aluminum alloy and ductile cast iron but it deteriorated with speed for inconel.     

单刀片镗削加工时的力学建模

介绍镗削加工的力学模型.沿切削刃切屑厚度的分布,被作为刀具刃倾角、刀尖圆弧半径、切削深度和进给量的函数被建模.使用机械的和直角到斜角切削转变两种方法,建立该过程的切削力学模型。     

Finite element simulation and experimental investigation of tool temperature during ultrasonically assisted turning of aerospace aluminum using multicoated carbide inserts

This paper summarizes the results of thermal finite element simulation and experimental studies of tool temperature in ultrasonic-assisted turning (UAT) of aerospace aluminum using multicoated carbide inserts. At first, mathematical models were developed in order to study the effects of tool coating, rake angle, cutting speed, and feed rate on the friction coefficient. Then with respect to the kinematics of the process, the cutting velocity model would be presented. This velocity model is used in combination with the mathematical model to define the friction coefficient during UAT. The mentioned frictional model is used to write a user subroutine to incorporate the effect of friction coefficient as a function of cutting parameters in the finite element program Abaqus. The results of this simulation make it possible to determine cutting temperature patterns accurately. It is also used to study the effect of cutting parameters (cutting speed, feed rate, rake angle, and vibration amplitude) on UAT. Finally, the simulation results are compared with experimental measurements of cutting temperatures from ultrasonic-assisted turning tests. The results show that ultrasonic-assisted turning is able to lower the maximum cutting temperature in cutting tool, about 29 %, in low feed rates (≈0.14 mm/rev), with a vibration amplitude of ≈10 μm and work velocity of ≈0.5 m/s.     

硬质合金切槽车刀性能分析

运用有限元方法对钛合金环槽车削过程进行数值模拟计算,得到硬质合金切槽车刀表面的温度,并应用Usui磨损理论计算刀具磨损速率。通过改变切削速度和进给量,获得不同工艺参数下刀具最高温度及刀具前刀面磨损速率。对环槽车削过程的热力耦合模拟结果进行分析,获得刀具切削过程中的温度及磨损速率的变化规律。结果表明,刀具温度和刀具前刀面磨损速率与工艺参数之间存在密切关系,合理选择工艺参数能有效提高硬质合金切槽车刀的性能。     

Investigation of cutting parameters effect for minimization of sur face roughness in internal turning

Minimizing the surface roughness is one of the primary objectives in most of the machining operations in general and in internal turning in particular. Poor control on the cutting parameters due to long boring bar generates non conforming parts which results in increase in cost and loss of productivity due to rework or scrap. In this study, the Taguchi method is used to minimize the surface roughness by investigating the rake angle effect on surface roughness in boring performed on a CNC lathe. The control parameters included besides tool rake angle were insert nose radius, cutting speed, depth of cut, and feedrate. Slight tool wear was included as a noise factor. Based on Taguchi Orthogonal Array L18, a series of experiments were designed and performed on AISI 1018 steel. Analysis of variance, ANOVA, was employed to identify the significant factors affecting the surface roughness and S/N ratio was used to find the optimal cutting combination of the parameters. It was concluded that tool with a high positive rake angle and smaller insert nose radius produced lower surface roughness value in an internal turning operation. It was also concluded that high feedrate and low cutting speed has produced the lowest surface roughness.     

基于AdvantEdge的6061铝合金高速铣削刀具结构参数优化研究

高速铣削过程中,刀具结构参数对刀具的切削性能有非常重要的影响。本文利用专用切削加工有限元分析软件AdvantEdge对6061铝合金高速铣削刀具进行了有限元分析。采用等效二维有限元仿真方法,结合单因素寻优设计方法,分析了硬质合金和高速钢刀具主要的宏、微观参数(包括刀具刃口钝圆半径、前角和后角等)对铣削加工过程中的温度、应变、切削力等参数的影响趋势。仿真结果显示,为获得较好的切削效果,铣刀取较小的刃口钝圆半径(即0.04mm左右);可取较大的前角和后角,前角为12°-15°,后角为15°-20°。     

Multi-objective optimization of oblique turning operations using finite element model and genetic algorithm

Multi-objective optimization of oblique turning operations while machining AISI H13 tool steel has been carried out using developed finite element (FE) model and multi-objective genetic algorithm (MOGA-II). The turning operation is optimized in terms of cutting force and temperature with constraints on required material removal rate and cutting power. The developed FE model is capable to simulate cutting forces, temperature and stress distributions, and chip morphology. The tool is modeled as a rigid body, whereas the workpiece is considered as elastic–thermoplastic with strain rate sensitivity and thermal softening effect. The effects of cutting speed, feed rate, rake angle, and inclination angle are modeled and compared with experimental findings. FE model is run with different parameters with central composite design used to develop a response surface model (RSM). The developed RSM is used as a solver for the MOGA-II. The optimal processing parameters are validated using FE model and experiments.     

Finite element simulation of diamond tool geometries affecting the 3D surface topography in fly cutting of KDP crystals

Diamond tool has significant influences on the finished surface quality in fly cutting of potassium dihydrogen phosphate (KDP) crystals. In this work, the nanoindentation and dimensional analysis are employed to establish the material constitutive equation of KDP crystals, i.e., the variation curve of flow stress vs. plastic strain. As expected, a novel 3D finite element (FE) model is developed for diamond fly cutting of KDP crystals, and the generation of 3D surface topography is simulated by multi-run cutting calculations, in which the movements of diamond tool are configured to be identical to the actual feed rate and cutting velocity. Subsequently, the coordinates of the nodes on the topmost surface as freshly machined are collected to evaluate the surface roughness, which enables the detailed analyses of the effect of diamond tool geometries on the achieved surface roughness of KDP crystals. The results suggest an optimal selection of tool geometries, i.e. ?25° rake angle and 8° clearance angle. With the increment of tool nose radius, surface roughness decreases correspondingly. Moreover, the larger defect or sharpness of tool cutting edge produces the worse surface roughness. Diamond fly cutting experiments are carried out with different rake angles, in which the cutting parameters are the same as the values used in FE simulations. The measured surface roughness has a satisfied consistency with the simulated data, which demonstrates that the developed 3D FE cutting model and the related simulations are reliable.     

Construction of a surface roughness prediction model for high speed machining

In manufacturing environment prediction of surface roughness is very important for product quality and production time. For this purpose, the finite element method and neural network is coupled to construct a surface roughness prediction model for high-speed machining. A finite element method based code is utilized to simulate the high-speed machining in which the cutting tool is incrementally advanced forward step by step during the cutting processes under various conditions of tool geometries (rake angle, edge radius) and cutting parameters (yielding strength, cutting speed, feed rate). The influences of the above cutting conditions on surface roughness variations are thus investigated. Moreover, the abductive neural networks are applied to synthesize the data sets obtained from the numerical calculations. Consequently, a quantitative prediction model is established for the relationship between the cutting variables and surface roughness in the process of high-speed machining. The surface roughness obtained from the calculations is compared with the experimental results conducted in the laboratory and with other research studies. Their agreements are quite well and the accuracy of the developed methodology may be verified accordingly. The simulation results also show that feed rate is the most important cutting variable dominating the surface roughness state.     

FORCE ANALYSIS OF ORTHOGONAL CUTTING OF BOVINE CORTICAL BONE

In orthopedic operations, no sound solutions exist to avoid conditions like tool breakage, bone fracture/cracks and thermal necrosis for lacking understanding of the mechanics of the bone cutting process. In this work, analysis of variance (ANOVA) and regression analysis were performed to investigate effects of cutting conditions on cutting and thrust forces based on a full factorial design. Then applicability of Merchant's analysis for calculating cutting force with respect to rake angle and feed was evaluated by comparison with experiments. Finally, the friction coefficient was evaluated by calculation. ANOVA shows that forces are much more sensitive to feed, cutting direction and rake angle than to cutting speed. Regression equations including all four factors were obtained by introduction of dummy variables. Cutting forces from experiments and from Merchant's analysis are partially comparable (maximum relative error = 34%) when feed and rake angle are changed. Friction coefficient was affected by rake angle and cutting direction. Cutting speed had little effect on the coefficient. These results can deepen the understanding of the mechanics of the bone-cutting process and assist the development of innovative cutting devices and selection of favorable cutting conditions for the procedure.