Dry sliding friction and casing wear behavior of PCD reinforced WC matrix composites

The friction and casing wear properties of PCD reinforced WC matrix composites were investigated using a cylinder-on-ring wear-testing machine against N80 casing steel counterface under dry sliding conditions. The results indicate that the friction and casing wear rate of PCD reinforced WC matrix composites are the lowest among the materials. As the applied load and sliding speed steadily increase, the friction coefficients of PCD reinforced WC matrix composites decrease. In addition, the casing wear rates increase with increasing load, but decline with sliding velocity. The dominant wear mechanism of the PCD composite is the micro-cutting wear, accompanied by adhesive wear.     

聚晶金刚石复合片的电火花线切割精密加工试验

为了提高聚晶金刚石(PCD)刀具的生产效率,改进加工表面质量并减少刃磨余量,利用慢走丝电火花线切割机床(WEDM)对PCD复合片进行了加工工艺试验.对PCD复合片进行了5次切割,并分别测量了每次加工后的表面粗糙度、富钴界面层凹槽深度及宽度和PCD层刃口加工质量.试验结果表明:PCD复合片经慢走丝线切割多次加工,能够得到较好的表面质量,在众多影响因素中金刚石颗粒大小对加工质量影响较大;其中CTH025型号和CTB010型号的最终表面粗糙度分别为Ra=0.85 μm和Ra=0.57 μm,富钴界面层凹槽的深度分别为16.3 μm和5.7 μm,刃口处切口缺陷的尺寸也与金刚石颗粒的尺寸相当.经WEDM加工后的PCD复合片的刃磨余量可控制在4～15 μm左右.     

Investigation of the burnishing process with PCD tool on non-ferrous metals

It is well known that the no-chip machining process, burnishing, can easily improve surface roughness, waviness and hardness. To get the practical useful parameters, the effects of various burnishing parameters (spindle speed, depth, feed, burnishing radius and lathe) on surface roughness and waviness of the non-ferrous components were studied experimentally with a theoretical analysis. The experiments were conducted with a simply designed cylindrical surfaced polycrystalline diamond tool developed by us. It was found that smaller parameters do not mean lower surface roughness or waviness and different optimum burnishing parameters can be got under different burnishing conditions.     

Optimisation of parameters affecting surface roughness of Co28Cr6Mo medical material during CNC lathe machining by using the Taguchi and RSM methods

This study involves modelling of experimental data of surface roughness of Co28Cr6Mo medical alloy machined on a CNC lathe based on cutting parameters (spindle rotational speed, feed rate, depth of cut and tool tip radius). In order to determine critical states of the cutting parameters variance analysis (ANOVA) was applied while optimisation of the parameters affecting the surface roughness was achieved with the Response Surface Methodology (RSM) that is based on the Taguchi orthogonal test design. The validity of the developed models necessary for estimation of the surface roughness values (Ra, Rz), was approximately 92%. It was found that for Ra 38% of the most effective parameters is on the tool tip radius, followed by 33% on the feed rate whereas for Rz tool tip radius occupied 43% with the feed being at 33% rate. To achieve the minimum surface roughness, the optimum values obtained for spindle rpm, feed rate, depth of cut and tool tip radius were respectively, 318 rpm, 0.1 mm/rev, 0.7 mm and 0.8 mm.     

基于田口法的高速切削参数优化研究与应用

应用田口法对切削速度、背吃刀量以及每齿进给量三个主要影响表面粗糙度的因素进行分析,求出各个因素不同水平的平均表面粗糙度和信噪比(S/N),得到最优切削参数。预测经最优切削参数加工得到的表面粗糙度值,最后通过确认实验验证了其正确性。     

聚晶金刚石刀具切削各向同性热解石墨过程中的磨损机理

针对各向同性热解石墨切削过程中刀具磨损过快的问题,采用聚晶金刚石（PCD）刀具进行了切削加工试验。研究了切削过程中PCD刀具的磨损形式、磨损规律以及刀具磨损对表面加工质量的影响。试验结果表明：PCD刀具磨损主要发生在后刀面上,磨损形式为磨粒磨损和氧化磨损。磨损区域可以分为平行沟槽和严重磨损两种形貌。初始磨损阶段,磨损带长度急剧增大,并在切削1200m后进入正常磨损阶段。切削过程中还出现了石墨切屑在磨损区域的黏附堆积和刀具崩刃现象。切削初期,随着切削距离的增大,加工表面粗糙度值急剧增大,切削距离为600m时表面粗糙度达到最大值1.7μm。     

Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method

This study focuses on optimizing turning parameters based on the Taguchi method to minimize surface roughness (Ra and Rz). Experiments have been conducted using the L9 orthogonal array in a CNC turning machine. Dry turning tests are carried out on hardened AISI 4140 (51 HRC) with coated carbide cutting tools. Each experiment is repeated three times and each test uses a new cutting insert to ensure accurate readings of the surface roughness. The statistical methods of signal to noise ratio (SNR) and the analysis of variance (ANOVA) are applied to investigate effects of cutting speed, feed rate and depth of cut on surface roughness. Results of this study indicate that the feed rate has the most significant effect on Ra and Rz. In addition, the effects of two factor interactions of the feed rate-cutting speed and depth of cut-cutting speed appear to be important. The developed model can be used in the metal machining industries in order to determine the optimum cutting parameters for minimum surface roughness.     

Validation of a method using Taguchi,response surface,neural network,and genetic algorithm

Piston is one of the important parts for aircraft engine, and the quality of piston affects the efficiency and safety of the engine. This study applies Taguchi method, response surface methodology (RSM), and back-propagation neural networks (BPNN) combining with genetic algorithm (GA) on the quality improvement of piston manufacturing processes to enhance the process yield. The Taguchi parameter design concerns three nominal-the-best specifications, including ring groove diameter specification, inner groove diameter specification, and inner diameter of pistons. Together with five control factors consisting of (1) type of carbon steel, (2) type of cutting fluid, (3) cutting depth, (4) spindle speed, and (5) chuck pressure, the L₂₇(3¹³) orthogonal array was selected for this experiment. Three models: (1) Taguchi model, (2) Taguchi_RSM model, and (3) Taguchi_BPNN_GA model were constructed to find the parameter combinations of five control factors for each model. Confirmation experiments were done for each model and the performances of three models were also compared to indict the enhancement of manufacturing quality of piston.     

Cutting forces,tool wear and surface finish in high speed diamond machining

We have investigated the cutting forces, the tool wear and the surface finish obtained in high speed diamond turning and milling of OFHC copper, brass CuZn39Pb3, aluminum AlMg5, and electroless nickel. In face turning experiments with constant material removal rate the cutting forces were recorded as a function of cutting speed between v_c = 150 m/min and 4500 m/min revealing a transition to adiabatic shearing which is supported by FEM simulations of the cutting process. Fly-cutting experiments carried out at low (v_c = 380 m/min) and at high cutting speed (v_c = 3800 m/min) showed that the rate of abrasive wear of the cutting edge is significantly higher at ordinary cutting speed than at high cutting speed in contrast to the experience made in conventional machining. Furthermore, it was found that the rate of chemically induced tool wear in diamond milling of steel is decreasing with decreasing tool engagement time per revolution. High speed diamond machining may also yield an improved surface roughness which was confirmed by comparing the step heights at grain boundaries obtained in diamond milling of OFHC copper and brass CuZn39Pb3 at low (v_c = 100 m/min) and high cutting speed (v_c = 2000 m/min). Thus, high speed diamond machining offers several advantages, let alone a major reduction of machining time.     

Optimisation of machining parameters for turning operations based on response surface methodology

Design of experiments has been used to study the effect of the main turning parameters such as feed rate, tool nose radius, cutting speed and depth of cut on the surface roughness of AISI 410 steel. A mathematical prediction model of the surface roughness has been developed in terms of above parameters. The effect of these parameters on the surface roughness has been investigated by using Response Surface Methodology (RSM). Response surface contours were constructed for determining the optimum conditions for a required surface roughness. The developed prediction equation shows that the feed rate is the main factor followed by tool nose radius influences the surface roughness. The surface roughness was found to increase with the increase in the feed and it decreased with increase in the tool nose radius. The verification experiment is carried out to check the validity of the developed model that predicted surface roughness within 6% error.     

Tool wear and its effect on surface roughness in diamond cutting of glass soda-lime

For the technology of diamond cutting of optical glass, the high tool wear rate is a main reason for hindering the practical application of this technology. Many researches on diamond tool wear in glass cutting rest on wear phenomenon describing simply without analyzing the genesis of wear phenomenon and interpreting the formation process of tool wear in mechanics. For in depth understanding of the tool wear and its effect on surface roughness in diamond cutting of glass, experiments of diamond turning with cutting distance increasing gradually are carried out on soda-lime glass. The wear morphology of rake face and flank face, the corresponding surface features of workpiece and the surface roughness, and the material compositions of flank wear area are detected. Experimental results indicate that the flank wear is predominant in diamond cutting glass and the flank wear land is characterized by micro-grooves, some smooth crater on the rake face is also seen. The surface roughness begins to increase rapidly, when the cutting mode changes from ductile to brittle for the aggravation of tool wear with the cutting distance over 150 m. The main mechanisms of inducing tool wear in diamond cutting of glass are diffusion, mechanical friction, thermo-chemical action and abrasive wear. The proposed research makes analysis and research from wear mechanism on the tool wear and its effect on surface roughness in diamond cutting of glass, and provides theoretical basis for minimizing the tool wear in diamond cutting brittle materials, such as optical glass.     

A study of the Taguchi optimization method for surface roughness in finish milling of mold surfaces

The objective of this paper is to develop a Taguchi optimization method for low surface roughness in terms of process parameters when milling the mold surfaces of 7075-T6 aluminum material. Considering the process parameters of feed, cutting speed, axial-radial depth of cut, and machining tolerance, a series of milling experiments were performed to measure the roughness data. A regression analysis was applied to determine the fitness of data used in the Taguchi optimization method using milling experiments based on a full factorial design. Taguchi orthogonal arrays, signal-to-noise (S/N) ratio, and analysis of variance (ANOVA) are used to find the optimal levels and the effect of the process parameters on surface roughness. A confirmation experiment with the optimal levels of process parameters was carried out in order to demonstrate the effectiveness of the Taguchi method. It can be concluded that Taguchi method is very suitable in solving the surface quality problem of mold surfaces.     

聚晶金刚石刀具的断屑槽尺寸参数设计

为解决聚晶金刚石(PCD)刀具在铝合金材料切削过程中的切屑缠绕问题,在PCD刀具的前刀面上设计了断屑槽.通过对切屑受力过程和断屑槽断屑机理的分析、切削几何关系的推导和有限元切削仿真实验,提取了5个PCD刀具断屑槽参数,即棱带宽度、倾角、反屑角、槽宽和反屑面转角.建立了PCD刀具断屑槽棱带宽度和反屑角的计算公式;改进了槽...     

The effect of cutting parameters and cutting tools on machining performance of carbon graphite material

Abstract

The present study focuses on the effects of cutting speed, feed rate and cutting tool material on the machining performance of carbon graphite material. Polycrystalline Diamond (PCD) cutting tools are used in machining experiments and its performance is compared with the tungsten carbide (WC) and Cubic Boron Nitride (CBN) tools. Machining performance criteria such as flank and nose wear and resulting surface topography and roughness of machined parts were studied. This study illustrates that feed rate and cutting tool material play a dominant role in the progressive wear of the cutting tool. The highest feed rate and cutting speed profoundly reduce the tool wear progression. The surface roughness and topography of specimens are remarkably influenced from the tool wear. Major differences are found in the wear mechanisms of PCD and WC and CBN cutting tools.     

Optimization of surface roughness and flank wear using the Taguchi method in milling of Hadfield steel with PVD and CVD coated inserts

In this paper, the Taguchi method and regression analysis have been applied to evaluate the machinability of Hadfield steel with PVD TiAlN- and CVD TiCN/Al₂O₃-coated carbide inserts under dry milling conditions. Several experiments were conducted using the L₁₈ (2 × 3 × 3) full-factorial design with a mixed orthogonal array on a CNC vertical machining center. Analysis of variance (ANOVA) was used to determine the effects of the machining parameters on surface roughness and flank wear. The cutting tool, cutting speed and feed rate were selected as machining parameters. The analysis results revealed that the feed rate was the dominant factor affecting surface roughness and cutting speed was the dominant factor affecting flank wear. Linear and quadratic regression analyses were applied to predict the outcomes of the experiment. The predicted values and measured values were very close to each other. Confirmation test results showed that the Taguchi method was very successful in the optimization of machining parameters for minimum surface roughness and flank wear in the milling the Hadfield steel.     

Optimization of surface roughness and tool wear in hard turning of austempered ductile iron (grade 3) using Taguchi method

In this work, the cutting parameters are optimized in hard turning of ADI using carbide inserts based on Taguchi method. The cutting insert CVD coated with AL₂O₃/MT TICN. Experiments have been carried out in dry condition using L₁₈ orthogonal array. The cutting parameters selected for machining are cutting speed, feed rate and depth of cut with each three levels, nose radius in two levels maintaining other cutting parameters constant. The ANOVA and signal to noise ratio are used to optimize the cutting parameters. The cutting speed is the most dominant factor affecting the surface roughness and tool wear. In optimum cutting condition, the confirmation tests are carried out. The optimum cutting condition results are predicted using signal to noise ratio and regression analysis. The predicted and experimental values for surface roughness and tool wear adhere closer to 9.27% and 1.05% of deviations respectively.     

On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations

This research work concerns the elaboration of a surface roughness model in the case of hard turning by exploiting the response surface methodology (RSM). The main input parameters of this model are the cutting parameters such as cutting speed, feed rate, depth of cut and tool vibration in radial and in main cutting force directions. The machined material tested is the 42CrMo4 hardened steel by Al₂O₃/TiC mixed ceramic cutting tool under different conditions. The model is able to predict surface roughness of Ra and Rt using an experimental data when machining steels. The combined effects of cutting parameters and tool vibration on surface roughness were investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of cutting parameters and tool vibration with respect to announced objectives which are the prediction of surface roughness. The adequacy of the model was verified when plotting the residuals values. The results indicate that the feed rate is the dominant factor affecting the surface roughness, whereas vibrations on both pre-cited directions have a low effect on it. Moreover, a good agreement was observed between the predicted and the experimental surface roughness. Optimal cutting condition and tool vibrations leading to the minimum surface roughness were highlighted.     

Application of Taguchi coupled Fuzzy Multi Attribute Decision Making (FMADM) for optimizing surface quality in turning austenitic and duplex stainless steels

In the present study, Taguchi approach is coupled with fuzzy-multiple attribute decision making methods for achieving better surface quality in constant cutting speed face turning of EN 1.4404 austenitic, EN 1.4462 standard duplex and EN 1.4410 super duplex stainless steels. Two typical multiple attribute decision making techniques were simultaneously adopted to determine multi-surface quality characteristics indices. The differences in rankings among derived indices are solved through converting each crisp values into trapezoidal fuzzy number and unifying them using fuzzy simple additive weight method. The fuzzy numbers are then deffuzified into crisp values employing techniques like; the spread, mode and area between centroid of centroids. Through this procedure, the decision maker is provided with necessary decision tools to optimize the cutting conditions with less sensitivity to the change of weights and no difference in ranking among the deffuzification techniques. Additionally, results of analyses of means and the validation experiments confirm that the optimum cutting conditions derived by this method produce far better surface finish than the best finish obtained during the course of experimentation. Analyses of variance results have shown the predominant effect of feed rate on surface quality. Finally, the collected chip at constant cutting speed and varying feed rates and depth of cuts has shown that friendlier-to-machine chips are obtained when machining austenitic stainless steels than duplex stainless steel grades.     

Application of Taguchi method for determining optimum surface roughness in turning of high-alloy white cast iron

This paper focused on optimizing the cutting conditions for the average surface roughness (R_a) obtained in machining of high-alloy white cast iron (Ni-Hard) at two different hardness levels (50 HRC and 62 HRC). Machining experiments were performed at the CNC lathe using ceramic and cubic boron nitride (CBN) cutting tools on Ni-Hard materials. Cutting speed, feed rate and depth of cut were chosen as the cutting parameters. Taguchi L₁₈ orthogonal array was used to design of experiment. Optimal cutting conditions was determined using the signal-to-noise (S/N) ratio which was calculated for R_a according to the “the-smaller-the-better” approach. The effects of the cutting parameters and tool materials on surface roughness were evaluated by the analysis of variance. The statistical analysis indicated that the parameters that have the biggest effect on R_a for Ni-Hard materials with 50 HRC and 62 HRC are the cutting speed and feed rate, respectively. Additionally, the optimum cutting conditions for the materials with 50 HRC and 62 HRC was found at different levels.