Influence of machining parameters on surface roughness in finish cut of WEDM

Surface roughness is significant to the finish cut of wire electrical discharge machining (WEDM). This paper describes the influence of the machining parameters (including pulse duration, discharge current, sustained pulse time, pulse interval time, polarity effect, material and dielectric) on surface roughness in the finish cut of WEDM. Experiments proved that the surface roughness can be improved by decreasing both pulse duration and discharge current. When the pulse energy per discharge is constant, short pulses and long pulses will result in the same surface roughness but dissimilar surface morphology and different material removal rates. The removal rate when a short pulse duration is used is much higher than when the pulse duration is long. Moreover, from the single discharge experiments, we found that a long pulse duration combined with a low peak value could not produce craters on the workpiece surface any more when the pulse energy was reduced to a certain value. However, the condition of short pulse duration with high peak value still could produce clear craters on the workpiece surface. This indicates that a short pulse duration combined with a high peak value can generate better surface roughness, which cannot be achieved with long pulses. In the study, it was also found that reversed polarity machining with the appropriate pulse energy can improve the machined surface roughness somewhat better compared with normal polarity in finish machining, but some copper from the wire electrode is accreted on the machined surface.     

Effect of machining parameters on surface roughness and tool wear for 7075 Al alloy SiC composite

In the present study, an attempt has been made to investigate the influence of cutting speed, depth of cut, and feed rate on surface roughness during machining of 7075 Al alloy and 10 wt.% SiC particulate metal-matrix composites. The experiments were conducted on a CNC Turning Machine using tungsten carbide and polycrystalline diamond (PCD) inserts. Surface roughness of 7075Al alloy with 10 wt.% SiC composite during machining by tungsten carbide tool was found to be lower in the feed range of 0.1 to 0.3 mm/rev and depth of cut (DOC) range of 0.5 to 1.5 mm as compared to surface roughness at other process parameters considered. Above cutting speed of 220 m/min surface roughness of SiC composite during machining by PCD tool was less as compared to surface roughness at other values of cutting speed considered. Wear of tungsten carbide and PCD inserts was analyzed using a metallurgical microscope and scanning electron microscope. Flanks wear of carbide tool increased by a factor of 2.4 with the increase of cutting speed from 180 to 240 m/min at a feed of 0.1 mm/rev and a DOC of 0.5 mm. On the other hand, flanks wear of PCD insert increased by only a factor of 1.3 with the increase of cutting speed from 180 to 240 m/min at feed of 0.1 mm/rev and DOC 0.5 mm.     

Optimization of turning parameters for surface roughness and tool life based on the Taguchi method

In this study, the effect and optimization of machining parameters on surface roughness and tool life in a turning operation was investigated by using the Taguchi method. The experimental studies were conducted under varying cutting speeds, feed rates, and depths of cut. An orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) were employed to the study the performance characteristics in the turning of commercial Ti-6Al-4V alloy using CNMG 120408-883 insert cutting tools. The conclusions revealed that the feed rate and cutting speed were the most influential factors on the surface roughness and tool life, respectively. The surface roughness was chiefly related to the cutting speed, whereas the axial depth of cut had the greatest effect on tool life.     

Effect of high speed turning operation on surface roughness of hybrid metal matrix (Al-SiCp-fly ash) composite

This paper explains the effect of turning parameters such as cutting speed, feed rate, depth of cut and cutting tool nose radius on surface roughness of hybrid metal matrix (Al-SiC_p-Fly ash) composite. Experiments have been conducted based on the orthogonal array L16(4)⁵ and surface roughness was tested on the composites turned by an high speed CNC centre lathe. Analysis of variance (ANOVA) was performed to predict the significant parameters and their contribution towards surface finish of the composite. A mathematical model was developed using non-linear regression analysis. Taguchi method and Genetic algorithm have been employed to optimize the turning parameters for optimum surface roughness of the composite. The optimum turning parametric conditions have been checked with the confirmation experiments. It has been noted that the optimum condition of genetic algorithm exhibited better results than the experimental results based on the orthogonal array and the optimum condition of Taguchi method.     

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.     

Application of Taguchi and response surface methodologies for surface roughness in machining glass fiber reinforced plastics by PCD tooling

This paper discusses the use of Taguchi and response surface methodologies for minimizing the surface roughness in machining glass fiber reinforced (GFRP) plastics with a polycrystalline diamond (PCD) tool. The experiments have been conducted using Taguchi’s experimental design technique. The cutting parameters used are cutting speed, feed and depth of cut. The effect of cutting parameters on surface roughness is evaluated and the optimum cutting condition for minimizing the surface roughness is determined. A second-order model has been established between the cutting parameters and surface roughness using response surface methodology. The experimental results reveal that the most significant machining parameter for surface roughness is feed followed by cutting speed. The predicted values and measured values are fairly close, which indicates that the developed model can be effectively used to predict the surface roughness in the machining of GFRP composites. The predicted values are confirmed by using validation experiments.     

A hybrid Taguchi-artificial neural network approach to predict surface roughness during electric discharge machining of titanium alloys

In the present study, electric discharge machining process was used for machining of titanium alloys. Eight process parameters were varied during the process. Experimental results showed that current and pulse-on-time significantly affected the performance characteristics. Artificial neural network coupled with Taguchi approach was applied for optimization and prediction of surface roughness. The experimental results and the predicted results showed good agreement. SEM was used to investigate the surface integrity. Analysis for migration of different chemical elements and formation of compounds on the surface was performed using EDS and XRD pattern. The results showed that high discharge energy caused surface defects such as cracks, craters, thick recast layer, micro pores, pin holes, residual stresses and debris. Also, migration of chemical elements both from electrode and dielectric media were observed during EDS analysis. Presence of carbon was seen on the machined surface. XRD results showed formation of titanium carbide compound which precipitated on the machined surface.     

Influence of surface preparation on roughness parameters,friction and wear

The aim of the present research was to investigate influence of surface preparation on roughness parameters and correlation between roughness parameters and friction and wear. First the correlation between different surface preparation techniques and roughness parameters was investigated. For this purpose 100Cr6 steel plate samples were prepared in terms of different average surface roughness, using different grades of grinding, polishing, turning and milling. Different surface preparation techniques resulted in different R_a values from 0.02 to 7 μm. After this, correlation between surface roughness parameters and friction and wear was investigated. For this reason dry and lubricated pin-on-disc tests, using different contact conditions, were carried out, where Al₂O₃ ball was used as counter-body. It was observed that parameters R_ku, R_sk, R_pk and R_vk tend to have influence on coefficient of friction.     

Modeling and optimization of Al/SiCp MMC machining using Taguchi approach

This paper presents the influence of process parameters like cutting speed, feed and depth of cut on flank wear (VBc) and surface roughness (Ra) in turning Al/SiCp metal matrix composites using uncoated tungsten carbide insert under dry environment. The experiments have been conducted based on Taguchi’s L₉ orthogonal array. Abrasion and adhesion are observed to be the principal wear mechanism from images of tool tip. No premature tool failure by chipping and fracturing was observed and machining was steady using carbide insert. Built-up-edge formation is noticed at low and higher cutting speed and at high feed combination and consequently surface quality affected adversely. The optimal parametric combination for flank wear and surface roughness are found to be v1–f1–d3 and v3–f1–d3 respectively and is greatly improved through Taguchi approach. Mathematical models for flank wear and surface roughness are found to be statistically significant.     

高速走丝线切割中电极丝对加工表面粗糙度的影响

工件的表面粗糙度是高速走丝线切割中一项重要的加工工艺指标.本文主要从电极丝的直径大小、走丝速度、变频进给速度、张力、换向次数和垂直度,对高速走丝线切割加工工件的表面粗糙度进行了分析.并结合生产实际,介绍了如何合理的选用电极丝的各参数.     

铣削表面粗糙度在线监测与加工参数的自适应优化

针对实际加工中工件与刀具之间的无规律振动而导致零件表面粗糙度不受控制的问题,提出了一种融合在线监测和自适应加工的方法.以主轴转速、背吃刀量、进给速度以及工件振动量为特征,基于XGBOOST算法对表面粗糙度进行回归分析,建立表面粗糙度的预测模型;在加工中对工件振动量进行实时采集,结合主轴转速、背吃刀量、切削速度和进给量建立实时表面粗糙度在线监测系统;当预测结果超出警戒值时,系统自动对切削参数背吃刀量、切削速度和进给量进行优化,进而减小工件振动,从而保证被加工零件的表面粗糙度.与传统的先加工后测量的方法相比,提出的方法实现了在加工的同时进行预测、分析与切削参数的自适应优化,有效地控制了被加工零件的表面粗糙度.     

铣削表面粗糙度在线监测与加工参数的自适应优化

针对实际加工中工件与刀具之间的无规律振动而导致零件表面粗糙度不受控制的问题,提出了一种融合在线监测和自适应加工的方法.以主轴转速、背吃刀量、进给速度以及工件振动量为特征,基于XGBOOST算法对表面粗糙度进行回归分析,建立表面粗糙度的预测模型;在加工中对工件振动量进行实时采集,结合主轴转速、背吃刀量、切削速度和进给量建立实时表面粗糙度在线监测系统;当预测结果超出警戒值时,系统自动对切削参数背吃刀量、切削速度和进给量进行优化,进而减小工件振动,从而保证被加工零件的表面粗糙度.与传统的先加工后测量的方法相比,提出的方法实现了在加工的同时进行预测、分析与切削参数的自适应优化,有效地控制了被加工零件的表面粗糙度.     

Influence of surface roughness effects on the performance of non-recessed hybrid journal bearings

The effect of journal and bearing surface roughness on the performance of a capillary compensated hole-entry hybrid journal bearing system has been theoretically studied. The analysis considers the average Reynold’s equation for the solution of lubricant flow field in the clearance space of a rough surface journal bearing system. The finite element method and Galarkin’s technique has been used to derive the system equation for the lubricant flow field. The non-dimensional parameters Λ (surface roughness parameter) and γ (surface pattern parameter) have been defined to represent the magnitude of height distribution of surface irregularities and their orientation, respectively. The influence of surface roughness on the bearing performance has been studied for the transverse, isotropic and longitudinal surface patterns. The bearing performance characteristics have been computed for both symmetric and asymmetric capillary compensated hole-entry journal bearing configurations for the various values of surface roughness parameter (Λ), surface pattern parameter (γ) and restrictor design parameter ( ). The computed results indicate that the inclusion of surface roughness effects in the analysis affects the performance of a bearing quite significantly vis-à-vis smooth surface bearing. The study indicates that for generation of accurate bearing characteristic data, the inclusion of surface roughness effects in the analysis is essential.     

Study on tool wear and surface roughness in machining of particulate aluminum metal matrix composite-response surface methodology approach

Metal matrix composites (MMC) have become a leading material among composite materials, and in particular, particle reinforced aluminum MMCs have received considerable attention due to their excellent engineering properties. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like silicon carbide particles (SiC_p). In this study, an attempt has been made to model the machinability evaluation through the response surface methodology in machining of homogenized 20% SiC_p LM25 Al MMC manufactured through stir cast route. The combined effects of four machining parameters including cutting speed (s), feed rate (f), depth of cut (d), and machining time (t) on the basis of two performance characteristics of flank wear (VB_max) and surface roughness (Ra) were investigated. The contour plots were generated to study the effect of process parameters as well as their interactions. The process parameters are optimized using desirability-based approach response surface methodology.     

An experimental study for determination of the effects of machining parameters on surface roughness in electrical discharge machining (EDM)

Electrical discharge machining (EDM) is a non-traditional production method that has been widely used in the production of dies throughout the world in recent years. The most important performance measure in EDM is the surface roughness; among other measures material removal and tool wear rates could be listed. In this study, experiments were performed to determine parameters effecting surface roughness. The data obtained for performance measures have been analyzed using the design of experiments methods. A considerably profound equation is obtained for the surface roughness using power, pulse time, and spark time parameters. The results are discussed.     

超声波振动挤压加工表面粗糙度试验研究

对超声波振动挤压加工中工件表面粗糙度的形成机理及规律进行了试验研究及分析,并对其主要工艺参数进行优选.     

Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method

This paper presents a new approach for the optimization of drilling parameters on drilling Al/SiC metal matrix composite with multiple responses based on orthogonal array with grey relational analysis. Experiments are conducted on LM25-based aluminium alloy reinforced with green bonded silicon carbide of size 25 μm (10% volume fraction). Drilling tests are carried out using TiN coated HSS twist drills of 10 mm diameter under dry condition. In this study, drilling parameters namely cutting speed, feed and point angle are optimized with the considerations of multi responses such as surface roughness, cutting force and torque. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in drilling process can be improved effectively through the new approach.     

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。     

微小型车铣加工表面粗糙度正交试验研究

铣车转速比、工件转速、轴向进给量以及切削深度是车铣加工中相对独立的四个重要切削参数.运用正交试验法研究微小型零件车铣加工表面粗糙度与上述四因素的关系.试验数据分析结果表明,该四因素对表面粗糙度的影响程度从大到小依次为:铣车转速比、轴向进给量、工件转速、切削深度.而且转速比的提高对粗糙度值的影响是单调的,转速比越高粗糙度越低.这一结论也与单因素试验结果相吻合.由试验结果分析还得到各切削参数的优化匹配关系.