The Effect of Cutting Parameters on Workpiece Surface Roughness in Wire EDM

In this study, the variation of workpiece surface roughness with varying pulse duration, open circuit voltage, wire speed and dielectric fluid pressure was experimentally investigated in Wire Electrical Discharge Machining (WEDM). Brass wire with 0.25 mm diameter and SAE 4140 steel with 10 mm thickness were used as tool and workpiece materials in the experiments, respectively. It is found experimentally that the increasing pulse duration, open circuit voltage and wire speed, increase the surface roughness whereas the increasing dielectric fluid pressure decreases the surface roughness. The variation of workpiece surface roughness with machining parameters is modelled by using a power function. The level of importance of the machining parameters on the workpiece surface roughness is determined by using analysis of variance (ANOVA).     

Experimental analysis on Nd:YAG laser micro-turning of alumina ceramic

Laser micro-turning is a micro-machining strategy to machine cylindrical workpiece of hard-to-process materials such as ceramics. Laser micro-turning method is in high demand in the present high-precision manufacturing industries because of its wide and potential uses in various engineering fields such as automobile, electronics, aerospace, and biomedical applications, etc. In the present research, the experimental analysis of Nd:YAG laser micro-turning of cylindrical-shaped ceramic material has been made to explore the desired laser output responses, i.e., depth of cut and surface roughness by varying laser micro-turning process parameters such as lamp current, pulse frequency, and laser beam scanning speed. Single laser beam has been utilized for successful micro-turning operation. Experimental results revealed that the laser machining process parameters have great influences for achieving desired laser micro-turned depth and surface roughness characteristics during laser micro-turning of alumina ceramics. SEM and optical photographs have also been analyzed for better understanding of the laser micro-turning process for different parametric settings.     

Surface roughness and cutting forces modeling for optimization of machining condition in finish hard turning of AISI 52100 steel

An experimental investigation was conducted to analyze the effect of cutting parameters (cutting speed, feed rate and depth of cut) and workpiece hardness on surface roughness and cutting force components. The finish hard turning of AISI 52100 steel with coated Al₂O₃ + TiC mixed ceramic cutting tools was studied. The planning of experiment were based on Taguchi’s L₂₇ orthogonal array. The response table and analysis of variance (ANOVA) have allowed to check the validity of linear regression model and to determine the significant parameters affecting the surface roughness and cutting forces. The statistical analysis reveals that the feed rate, workpiece hardness and cutting speed have significant effects in reducing the surface roughness; whereas the depth of cut, workpiece hardness and feed rate are observed to have a statistically significant impact on the cutting force components than the cutting speed. Consequently, empirical models were developed to correlate the cutting parameters and workpiece hardness with surface roughness and cutting forces. The optimum machining conditions to produce the lowest surface roughness with minimal cutting force components under these experimental conditions were searched using desirability function approach for multiple response factors optimization. Finally, confirmation experiments were performed to verify the pertinence of the developed empirical models.     

Using optimization procedures to minimize machining time while maintaining surface quality

In this study, we present a methodology for minimizing machining time, where the surface roughness is constrained for the problem. The objective of the methodology is to encounter optimized cutting parameters which reduce machining time without reducing the surface quality of the machined workpiece. Three optimization schemes were considered to encounter the minima of a quantity which is a function of machining parameters: (a) sequential quadratic programming, (b) genetic algorithms, and (c) simulated annealing. For the discussion of the methodologies employed, an example of a machined surface is presented. The formalisms are used to obtain the parameters which minimize the machining time while maintaining the surface roughness within acceptable limits.     

Reducing electrode wear ratio using cryogenic cooling during electrical discharge machining

In this study, cooling effect of copper electrode on the die-sinking of electrical discharge machining of titanium alloy (Ti-6Al-4V) has been carried out. Investigation on the effect of cooling on electrode wear and surface roughness of the workpiece has been carried out. Design of experiment plan for rotatable central composite design of second order with four variables at five levels each has been employed to carry out the investigation. Current intensity (I), pulse on-time (t _on), pulse off-time (t _off), and gap voltage (v) were considered as the machining parameters, while electrode wear and surface roughness are the responses. Analysis of the influence of cooling on the responses has been carried out and presented in this study. It was possible to reduce electrode wear ratio up to 27% by electrode cooling. Surface roughness was also reduced while machining with electrode cooling.     

Improving surface integrity in finish machining of Inconel 718 alloy using intelligent systems

In machining of hard materials, surface integrity is one of the major customer requirements which comprise the study of the changes induced to the workpiece. Surface roughness and residual stress are often considered as the most significant indications of surface integrity. Inducing tensile residual stress during the machining processes is a critical problem which should be avoided or minimized to obtain better service quality and component life. This problem becomes more evident in the presence of rough machined surface because fatigue life of manufactured components might be decreased significantly. Inconel 718 superalloy is one of the hard materials used extensively in the aerospace industries. It is prone to tensile residual stress in machined surface. Thus, controlling and optimizing residual stress and surface roughness in machining of Inconel 718 are so needed. Intelligent techniques based on the predictive and optimization models can be used efficiently for this purpose. In this study, the optimal machining parameters including cutting speed, depth of cut, and feed rate were accessed by intelligent systems to evaluate the state of residual stress and surface roughness in finish turning of Inconel 718. The results of experiments and analyses indicated that implemented techniques in this work provided a robust framework for improving surface integrity in machining of Inconel 718 alloy. It was shown that cutting speed has more effect on surface integrity than other investigated parameters. Also, depth of cut and feed rate were found in the moderate range to obtain satisfactory state of tensile residual stress and surface roughness.     

An experimental analysis and measurement of process performances in machining of nimonic C-263 super alloy

Nimonic C-263 alloy is extensively used in the fields of aerospace, gas turbine blades, power generators and heat exchangers because of its unique properties. However, the machining of this alloy is difficult due to low thermal conductivity and work hardening characteristics. This paper presents the experimental investigation and analysis of the machining parameters while turning the nimonic C-263 alloy, using whisker reinforced ceramic inserts. The experiments were designed using Taguchi’s experimental design. The parameters considered for the experiments are cutting speed, feed rate and depth of cut. Process performance indicators, viz., the cutting force, tool wear and surface finish were measured. An empirical model has been created for predicting the cutting force, flank wear and surface roughness through response surface methodology (RSM). The desirability function approach has been used for multi response optimization. The influence of the different parameters and their interactions on the cutting force, flank wear and surface roughness are also studied in detail and presented in this study. Based on the cutting force, flank wear and surface roughness, optimized machining conditions were observed in the region of 210 m/min cutting speed and 0.05 mm/rev feed rate and 0.50 mm depth of cut. The results were confirmed by conducting further confirmation tests.     

Performance Analysis of Wire Electrodes on Machining Ti-6Al-4V Alloy using Electrical Discharge Machining Process

High-strength materials with complex shapes can be easily machined by electrical discharge machining process. In the present study, an attempt has been made to analyze the influence of wire electrode on Kerf width and workpiece surface roughness in wire EDM process. Due to its importance in the aircrafts and automobiles, Ti-6Al-4V alloy has been chosen as the workpiece material. The various experiments have been conducted based on a Taguchi L₉ orthogonal array with various types of wire electrodes, such as conventional brass wire, zinc-coated wire and diffused coated brass wire. From the experimental results, it has been observed that diffused coated wire produced better surface finish with minimum kerf width compared to the other two wire electrodes. It has also been observed that the pulse off-time has more influent nature on machining characteristics such as surface roughness and kerf width.     

Predictive model and process parameters optimization of Nd:YAG laser micro-turning of ceramics

The present work highlights laser micro-turning operation of 10-mm diameter cylindrical-shaped alumina (Al₂O₃) ceramic using pulsed Nd:YAG laser. The paper also addresses development of mathematical models for correlating the various micro-machining parameters such as laser beam average power, pulse frequency, workpiece rotational speed, assist air pressure, and Y feed rate with the response criteria such as surface roughness and deviation in turned depth for achieving desired surface quality as well as dimensional accuracy during micro-turning operation using Nd:YAG laser system. Response surface methodology-based design of experiments has been adopted for the experimentation. This investigation also highlights the various test results that confirm the validity and correctiveness of the developed mathematical models through analysis of variance test. The test results were analyzed through various response surface plots to study the effect of the process parameters on the aforementioned responses. The results of validation experimentation show a good agreement for the developed empirical models. Sensitivity analyses of the developed models have been done to find out the variation in the output with respect to variations in the significant input process parameters. Moreover, multi-performance optimization has been done to find out the optimal parametric setting for achieving the desired process performances. Analysis also has been made based on scanning electron microscopy micrographs of the laser micro-turned surface achieved during machining at multi-criteria optimization setting.     

Case-based reasoning (CBR) model for hard machining process

In this research paper, hard machining of two materials viz. AISI 52100 (bearing steel) and AISI D2 (tool steel) at a hardness of 55?HRC is addressed. Taguchi’s technique is used for the design of experiments. Eight different parameters are considered for the experimentation in order to perform comprehensive investigations on hard machining process. Case-based reasoning (CBR) model is developed for predicting the machining performance and its capability is evaluated by conducting validation experiments. The root mean squared error, mean absolute percentage error, and the correlation coefficient between the actual and the model-predicted values of surface roughness and tool life are evaluated to confirm the validity of the CBR model.     

Multi response optimization of wire EDM operations using robust design of experiments

In this present study a multi response optimization method using Taguchi’s robust design approach is proposed for wire electrical discharge machining (WEDM) operations. Experimentation was planned as per Taguchi’s L16 orthogonal array. Each experiment has been performed under different cutting conditions of pulse on time, wire tension, delay time, wire feed speed, and ignition current intensity. Three responses namely material removal rate, surface roughness, and wire wear ratio have been considered for each experiment. The machining parameters are optimized with the multi response characteristics of the material removal rate, surface roughness, and wire wear ratio. Multi response S/N (MRSN) ratio was applied to measure the performance characteristics deviating from the actual value. Analysis of variance (ANOVA) is employed to identify the level of importance of the machining parameters on the multiple performance characteristics considered. Finally experimental confirmation was carried out to identify the effectiveness of this proposed method. A good improvement was obtained.     

基于“S”形加工样件的复合数控机床几何误差逆向追踪

基于对"S"形加工样件的复合机床误差影响溯源的研究,提出一种辨识影响加工缺陷最大的误差参数的方法。该方法将"S"形样件加工缺陷与复合数控机床成形运动综合考虑,采用三次B样条曲面对"S"形样件加工缺陷进行数学表征,并逆向推导出了"S"形样件加工缺陷处对应的刀具中心的实际位置,求解出了实际加工曲面到机床刀具的映射关系。同时利用多体系统误差分析理论建立了复合机床加工缺陷生成模型,并从机床角度求解出了缺陷处误差的表达方程。接着在"S"形样件缺陷产生的位置处,根据误差参数的敏感度及其实测值计算各项误差参数对加工缺陷的贡献并进行排序,确定对加工缺陷影响较大的5项误差参数。试验结果表明:该5项误差参数和全部误差参数同时作用下各点的误差进行差值比较,发现差值最大不超过±1.5μm,因此ε_(yC_1)、δ_z(B)、ε(C_1)、ε_x(C_1)、ε_(x_1C_1)是对加工缺陷影响较大的5项误差参数。     

钛合金薄壁曲面液态金属-磨粒流加工仿真与试验研究

针对钛合金薄壁曲面工件磨粒流抛光后表面粗糙度分布不均匀的问题,提出一种基于液态金属的磨粒流加工方法。基于SST k-ω模型、OKA冲蚀模型,流体流动颗粒追踪模型,采用COMSOL有限元软件对不同电场布置下的液态金属-磨粒流动力学特性开展深入研究。仿真结果表明,通过电场的合理布置可以控制液态金属颗粒在流场中运动;合理的电场布置可以有效提高工件表面加工均匀性,并通过仿真得出了一组冲蚀较好的试验参数。基于仿真结果开展了液态金属-磨粒流加工试验,试验结果表明：液态金属-磨粒流加工方法可有效提高工件表面加工的均匀性。在加工14 h后,不加电场的磨粒流加工表面不同区域的粗糙度分布不均,工件凹陷处粗糙度明显大于凸起处,各区域表面粗糙度极差达到66.1 nm。使用液态金属-磨粒流加工后的工件表面各区域粗糙度的均匀性明显提高,各区域表面粗糙度极差减小为20.3 nm,为液态金属-磨粒流加工的开展及其调控提供了理论和试验依据。     

铣削加工表面形貌预测方法研究

在考虑了刀具和工件在切削力作用下的振动、刀具的安装误差和工件的装夹误差对刀具相对工件位姿的影响下,通过加工几何运动学建立刀刃点在加工特征点活动标架下的数学模型。根据局部活动标架特征,将铣削表面残高求解问题转化为求解非线性规划问题,通过求解非线性规划问题来预测铣削加工表面微观几何形貌及粗糙度,为合理选择工艺参数提供科学的依据。仿真试验和加工试验验证了所提出的方法的正确性和有效性。     

Modelling and analysis of hybrid electrochemical turning-magnetic abrasive finishing of 6061 Al/Al2O3 composite

This paper integrates the electrochemical turning (ECT) process and magnetic abrasive finishing (MAF) to produce a combined process that improves the material removal rate (MRR) and reduces surface roughness (SR). The present study emphasizes the features of the development of comprehensive mathematical models based on response surface methodology (RSM) for correlating the interactive and higher-order influences of major machining parameters, i.e. magnetic flux density, applied voltage, tool feed rate and workpiece rotational speed on MRR and SR of 6061 Al/Al₂O₃ (10% wt) composite. The paper also highlights the various test results that also confirm the validity and correctness of the established mathematical models for in-depth analysis of the effects of hybrid ECT- MAF process parameters on metal removal rate and surface roughness. Further, optimal combination of these parameters has been evaluated and it can be used in order to maximize MRR and minimize SR. The results demonstrate that assisting ECT with MAF leads to an increase machining efficiency and resultant surface quality significantly, as compared to that achieved with the traditional ECT of some 147.6% and 33%, respectively.     

基于RSM的SiC单晶片表面粗糙度预测及参数优化

通过响应面分析法(RSM)对超声振动辅助金刚石线锯切割SiC单晶体的工艺参数进行分析和优化。采用中心组合设计实验,考察线锯速度、工件进给速度、工件转速和超声波振幅这4个因素对SiC单晶片表面粗糙度值的影响,建立了SiC单晶片表面粗糙度的响应模型,进行响应面分析,采用满意度函数(DFM)确定了切割SiC单晶体的最佳工艺参数,验证试验表明该模型能实现相应的硬脆材料切割过程的表面粗糙度预测。     

Application of Taguchi design for quality characterization of abrasive water jet machining of TRIP sheet steels

In the present paper, the influence of sheet thickness, nozzle diameter, standoff distance, and traverse speed during abrasive water jet machining (AWJM) of transformation-induced plasticity (TRIP) sheet steels on surface quality characteristics (kerf geometry and surface roughness) was investigated. The experiments were designed using Taguchi methodology and carried out by AWJ Machining TRIP 700 CR-FH and TRIP 800 HR-FH steel sheets. As response variables, mean kerf width and average surface roughness were selected. The experimental results were analyzed using analysis of means and analysis of variance methods in order to correlate the AWJM process parameters the response variables. In addition, regression models were obtained using the experimental results and validated with six independent experiments. The reported results indicate that the proposed methodology can satisfactorily analyze the surface roughness and the mean kerf in AWJM; moreover, it can be considered as valuable tools for process planning in workshop.     

Optimization techniques for machining operations: a retrospective research based on various mathematical models

Simulated annealing, genetic algorithm, and particle swarm optimization techniques have been used for exploring optimal machining parameters for single pass turning operation, multi-pass turning operation, and surface grinding operation. The behavior of optimization techniques are studied based on various mathematical models. The objective functions of the various mathematical models are distinctly different from each other. The most affecting machining parameters are considered as cutting speed, feed, and depth of cut. Physical constraints are speed, feed, depth of cut, power limitation, surface roughness, temperature, and cutting force.     

OPTIMAL MACHINING CONDITIONS FOR TURNING OF PARTICULATE METAL MATRIX COMPOSITES USING TAGUCHI AND RESPONSE SURFACE METHODOLOGIES

The present investigation focuses on the influence of machining parameters on the surface finish obtained in turning of LM25 Al/SiC particulate composites. The experiments are conducted based on Taguchi's experimental design technique. In this work, the effect of machining parameters on the surface roughness is evaluated and optimum machining conditions for maximizing the metal removal rate and minimizing the surface roughness are determined using response surface methodology. A second-order response surface model for the surface roughness is developed to predict the surface roughness. The predicted values and measured values are fairly close to each other, which indicates that the developed model can be effectively used to predict the surface roughness on the machining of Al/SiC-MMC composites with 95% confidence intervals within the ranges of parameters studied.     

ELECTRIC DISCHARGE MILLING AND MECHANICAL GRINDING COMPOUND MACHINING OF SILICON CARBIDE CERAMIC

Silicon carbide (SiC) ceramics have been widely used in modern industry. However, the manufacture of SiC ceramics is not an efficient process. This paper proposes a new technology of machining SiC ceramics with electrical discharge milling and mechanical grinding compound method. The compound process employs the pulse generator used in electrical discharge machining, and uses a water-based emulsion as the machining fluid. It is able to effectively machine a large surface area on SiC ceramics with a good surface quality. In this paper, the effects of pulse duration, pulse interval, peak voltage, peak current and feed rate of the workpiece on the process performance parameters, such as material removal rate, relative electrode wear ratio and surface roughness, have been investigated. A L₂₅ orthogonal array based on Taguchi method is adopted, and the experimental data are statistically evaluated by analysis of variance and stepwise regression. The significant machining parameters, the optimal combination levels of machining parameters, and the mathematical models associated with the process performance are obtained. In addition, the workpiece surface microstructure is examined with a scanning electron microscope and an energy dispersive spectrometer.