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.     

Optimization of the EDM parameters on machining Ti–6Al–4V with multiple quality characteristics

In this paper, parameter optimization of the electrical discharge machining process to Ti–6Al–4V alloy considering multiple performance characteristics using the Taguchi method and grey relational analysis is reported. Performance characteristics including the electrode wear ratio, material removal rate and surface roughness are chosen to evaluate the machining effects. The process parameters selected in this study are discharge current, open voltage, pulse duration and duty factor. Experiments based on the appropriate orthogonal array are conducted first. The normalised experimental results of the performance characteristics are then introduced to calculate the coefficient and grades according to grey relational analysis. The optimised process parameters simultaneously leading to a lower electrode wear ratio, higher material removal rate and better surface roughness are then verified through a confirmation experiment. The validation experiments show an improved electrode wear ratio of 15%, material removal rate of 12% and surface roughness of 19% when the Taguchi method and grey relational analysis are used.     

Free abrasive wire saw machining of ceramics

Currently, many kinds of ceramics are used in advanced industrial fields due to their superior mechanical properties, such as thermal, wear, corrosion resistance, and lightweight features. Wire saw machining ceramic (Al₂O₃) was investigated by ultrasonic vibration in this study. Taguchi approach is a powerful design tool for high-quality systems. Material removal rate, wafer surface roughness, steel wire wear, kerf width, and flatness during machining ceramic were selected as quality character factors to optimize the machining parameters (swinging angle, concentration, mixed grain and direction of ultrasonic vibration) to get the larger-the-better (material removal rate) and the smaller-the-better (wafer surface roughness, steel wire wear, kerf width and flatness) machining characteristics by Taguchi method. The results indicated that wire swinging produces a higher material removal rate and good wafer surface roughness. Ultrasonic vibration improved material removal rate, without affecting the flatness under different machining conditions. Experimental results show that the optimal wire saw machining parameters based on grey relational analysis can be determined effectively and material removal rate increases from 2.972 to 3.324 mm²/min, wafer surface roughness decreases from 0.37 to 0.34 μm, steel wire wear decreases from 0.78 to 0.77 μm, kerf width decreases from 0.352 to 0.350 mm, and flatness decreases from 7.51 to 7.22 μm are observed.     

Determination of Optimal Ball-Burnishing Parameters for Plastic Injection Moulding Steel

The objective of this study is to determine the optimal plane ball-burnishing parameters for plastic injection moulding steel PDS5 on a machining centre by utilising the Taguchi’s orthogonal array method. The design and manufacture of a burnishing tool are described. Four burnishing parameters, namely the ball material, burnishing speed, burnishing force and feed, were selected as the experimental factors in Taguchi’s design of experiments to determine the optimal burnishing parameters which have the dominant influence on surface roughness. The optimal burnishing parameters were found after carrying out the experiments specified by Taguchi’s L18 orthogonal table, by the analysis of variation, and by a full factorial experiment. The optimal plane burnishing parameters for the plastic injection moulding steel PDS5 were a combination of a tungsten carbide ball, a burnishing speed of 200 mm/min, a burnishing force of 300 N and a feed of 40 μm. The surface roughness Ra of the specimen can be improved from about 1 μm to 0.07 μm by using the optimal burnishing parameters for plane burnishing.     

Modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al2O3+TiC mixed ceramic

Electric discharge machining (EDM) has achieved remarkable success in the manufacture of conductive ceramic materials for the modern metal industry. Mathematical models are proposed for the modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al₂O₃+TiC mixed ceramic which are developed using the response surface methodology (RSM) to explain the influences of four machining parameters (the discharge current, pulse on time, duty factor and open discharge voltage) on the performance characteristics of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The experiment plan adopts the centered central composite design (CCD). The separable influence of individual machining parameters and the interaction between these parameters are also investigated by using analysis of variance (ANOVA). This study highlights the development of mathematical models for investigating the influences of machining parameters on performance characteristics and the proposed mathematical models in this study have proven to fit and predict values of performance characteristics close to those readings recorded experimentally with a 95% confidence interval. Results show that the main two significant factors on the value of the material removal rate (MRR) are the discharge current and the duty factor. The discharge current and the pulse on time also have statistical significance on both the value of the electrode wear ratio (EWR) and the surface roughness (SR).     

Selection of an optimal parametric combination for achieving a better surface finish in dry milling using genetic algorithms

In machining, coolants improve machinability, increase productivity by reducing tool wear and extend tool life. However, due to ecological and human health problems, manufacturing industries are now being forced to implement strategies to reduce the amount of cutting fluids used in their production lines. A trend that has emerged to solve these problems is machining without fluid – a method called dry machining – which has been made possible due to technological innovations. This paper presents an experimental investigation of the influence of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on machining performance in dry milling with four fluted solid TiAlN-coated carbide end mill cutters based on Taguchi’s experimental design method. The mathematical model, in terms of machining parameters, was developed for surface roughness prediction using response surface methodology. The optimization is then carried out with genetic algorithms using the surface roughness model developed and validated in this work. This methodology helps to determine the best possible tool geometry and cutting conditions for dry milling.     

An experimental investigation on machining parameters of AISI D2 steel using WEDM

The performance of the wire electrodischarge machining (WEDM) machining process largely depends upon the selection of the appropriate machining variables. Optimization is one of the techniques used in manufacturing sectors to arrive for the best manufacturing conditions, which are essential for industries toward manufacturing of quality products at lowest cost. As there are many process variables involved in the WEDM machining process, it is difficult to choose a proper combination of these process variables in order to maximize material removal rate and to minimize tool wear and surface roughness. The objective of the this work is to investigate the effects of process variables like pulse on time, pulse off time, peak current, servo voltage, and wire feed on material removal rate (MRR), surface roughness (SR), gap voltage, gap current, and cutting rate in the WEDM machining process. The experiment has been done using Taguchi’s orthogonal array L27 (3⁵). Each experiment was conducted under different conditions of input parameters and statistically evaluated the experimental data by analysis of variance (ANOVA) using MINITAB and Design Expert tools. The present work also aims to develop mathematical models for correlating the inter-relationships of various WEDM machining parameters and performance parameters of machining on AISI D2 steel material using response surface methodology (RSM).The significant machining parameters and the optimal combination levels of machining parameters associated with performance parameters were also drawn. The observed optimal process parameter settings based on composite desirability (61.4 %) are pulse on time 112.66 μs, pulse off time 45 μs, spark gap voltage 46.95 V, wire feed 2 mm/min, peak current of 99.99 A for achieving maximum MRR, gap current, gap voltage, cutting rate, and minimum SR; finally, the results were experimentally verified.     

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.     

An experimental investigation of tool wear in electric discharge machining

In this study, the variations of geometrical tool wear characteristics – namely, edge and front wear – and machining performance outputs – namely, workpiece removal rate, tool wear rate, relative wear and workpiece surface roughness – were investigated with varying machining parameters. Experiments were conducted using steel workpieces and round copper tools with a kerosene dielectric under different dielectric flushing conditions (injection, suction and static), discharge currents and pulse durations. The experiments have shown that machining parameters and dielectric flushing conditions had a large effect on geometric tool wear characteristics and machining performance outputs. Additionally, published research on tool wear is presented in detail in this study.     

An experimental research on a kind of distributed-flushing ED milling

In order to reduce the electrode wear and increase the material removal, this paper proposed a kind of distributed-flushing ED milling. A rotating electrode with some distributed holes was used during the machining process. The distributed flushing developed the machining environment and increased the adhesion of debris on the electrode, thus decreasing the electrode wear rate. Compared with the material removal rate of conventional ED milling, the relative electrode wear ratio decreased by 10.7 %. Furthermore, the material removal rate of the new method increased by 21.1 %. The effects of rotating speed, peak current, pulse duration, pulse interval, and tool electrode polarity on machining performance, including material removal rate, relative electrode wear ratio, and surface roughness were researched to determine the characteristics of the new process.

     

Optimization of machining parameters for EDM operations based on central composite design and desirability approach

A novel aluminium metal matrix composite reinforced with SiC particles were prepared by liquid metallurgy route. Recent developments in composites are not only focused on the improvement of mechanical properties, but also on machinability for difficult-to-machine shapes. Electrical discharge machining (EDM) was employed to machine MMC with copper electrode. using EDM. Experiments were conducted using pulse current, gap voltage, pulse on time and pulse off time as typical process parameters. The experiment plan adopts face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions viz., pulse current, gap voltage, pulse on time and pulse off time on material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). The objective was to identify the significant process parameters that affect the output characteristics. Further a mathematical model has been formulated by applying response surface method in order to estimate the machining characteristics such as MRR, EWR and SR.     

Wire electrical discharge machining of ASP30 tool steel

Wire electrical discharge machining is a non-traditional cutting process for machining of hard and high strength materials. This study analyzed the effects of the main input parameters of wire electrical discharge machining of ASP30 steel (high alloyed Powder metallurgical [PM] high speed steel) as the workpiece on the material removal rate and surface roughness. The input parameters included spraying pressure and electric conductivity coefficient of the dielectric fluid, linear velocity of the wire and wire tension. The machined surface quality was evaluated using SEM pictures. Results indicated that increasing the spraying pressure of dielectric fluid leads to a higher material removal rate and surface roughness and that increasing the wire tension, linear velocity of wire, and electric conductivity of the dielectric fluid decreases the material removal rate and surface roughness.

     

The parameters evaluation and optimization of polycrystalline diamond micro-electrodischarge machining assisted by electrode tool vibration

The objective of this research is to evaluate and optimize machining parameter of tool electrode vibration on micro-electric discharge machining of polycrystalline diamond. The machining parameters evaluated are charge voltage, capacitance, and vibration of the tool electrode. An orthogonal array, signal-to-noise ratio, and analysis of variance are employed to analyze the effect of these machining parameters. The results show that by application of vibration on tool electrode in machining of polycrystalline diamond, it has significant effect up to 66.48% in increasing material removal rate without increasing surface roughness and tool electrode wear. Using Taguchi method for design of experiment, other significant effects on surface quality and tool electrode wear are also investigated. The results also show that surface roughness is mostly affected by the amount of capacitance (52.24%), and the tool electrode wear is also affected by the amount of capacitance (92.82%).     

Multiple process parameter optimization of wire electrical discharge machining on Inconel 825 using Taguchi grey relational analysis

In this paper, an effective approach, Taguchi grey relational analysis, has been applied to experimental results of wire cut electrical discharge machining (WEDM) on Inconel 825 with consideration of multiple response measures. The approach combines the orthogonal array design of experiment with grey relational analysis. The main objective of this study is to obtain improved material removal rate, surface roughness, and spark gap. Grey relational theory is adopted to determine the best process parameters that optimize the response measures. The experiment has been done by using Taguchi’s orthogonal array L36 (2¹?×?3⁷). Each experiment was conducted under different conditions of input parameters. The response table and the grey relational grade for each level of the machining parameters have been established. From 36 experiments, the best combination of parameters was found. The experimental results confirm that the proposed method in this study effectively improves the machining performance of WEDM process.     

Automated surface finishing of plastic injection mold steel with spherical grinding and ball burnishing processes

This study investigates the possibilities of automated spherical grinding and ball burnishing surface finishing processes in a freeform surface plastic injection mold steel PDS5 on a CNC machining center. The design and manufacture of a grinding tool holder has been accomplished in this study. The optimal surface grinding parameters were determined using Taguchi’s orthogonal array method for plastic injection molding steel PDS5 on a machining center. The optimal surface grinding parameters for the plastic injection mold steel PDS5 were the combination of an abrasive material of PA Al₂O₃, a grinding speed of 18000 rpm, a grinding depth of 20 μm, and a feed of 50 mm/min. The surface roughness R_a of the specimen can be improved from about 1.60 μm to 0.35 μm by using the optimal parameters for surface grinding. Surface roughness R_a can be further improved from about 0.343 μm to 0.06 μm by using the ball burnishing process with the optimal burnishing parameters. Applying the optimal surface grinding and burnishing parameters sequentially to a fine-milled freeform surface mold insert, the surface roughness R_a of freeform surface region on the tested part can be improved from about 2.15 μm to 0.07 μm.     

Experimental study of lapping and electropolishing of tungsten carbides

Lapping and electropolishing (EP) experiments for tungsten carbide blocks were executed. The effectiveness of the lapping experiment is evaluated in terms of the material removal rate, the surface roughness, and wear of the workpiece. The material removal rate describes the thickness removal of the workpiece under a fixed surface area. Wear describes a microscopic study of the wear track. The results show that the material removal and surface roughness increase as the grain size of the abrasive increases. Four main wear mechanisms -- abrasive wear, fracture, adhesive wear and scratch -- are observed during the lapping of tungsten carbide using silicon carbide abrasive. In the electropolishing experiment, four different machining characteristics -- sub-electropolishing, crack, electropolishing, and pitting -- can be analyzed as the applied current is increased. Although material removal is close to Faraday’s law during electropolishing, it disagrees with Faraday’s law after 400 s of sub-electropolishing.     

Precision machining of an aluminum alloy piston reinforced with a cast iron insert

Bimetallic pistons consisting of aluminum alloy reinforced with a cast iron (CI) insert are used to reduce the weight and improve the wear resistance of pistons. A major problem with machining such bimetallic pistons is producing the desired shape with minimal cutting forces and without damaging the bonding registry. The objective of this paper is to determine the optimal cutting parameters (cutting speed, feed, and depth of cut) for turning bimetallic pistons. When machining, we wish to obtain optimal values of the cutting forces and a better surface integrity while maintaining the required surface finish. Experiments were conducted following Taguchi’s parameter design approach using a cubic boron nitride tool for the machining. The results indicate that the process parameters affected the mean and variance of the cutting force at the Al-CI interface of the piston. The Al-CI interface was examined using an ultrasonic piston bond tester after machining to assure the bond quality. The surface roughness of the components was measured with a surface roughness tester. A mathematical model was developed using the Systat 12.0 software package to establish the relationship between the input quantities (speed, feed, and depth of cut) and the output data (cutting force). The output data of the mathematical model were compared with the experimental results. The results from the Taguchi robust design concept were compared with the results obtained from a nonconventional Genetic Algorithm optimization technique.     

Surface quality evaluation in ultrasonic drilling through the Taguchi technique

Ultrasonic drilling of commercially pure titanium and titanium alloy (Ti-6Al-4v) was investigated in this study. During the experiments, process parameters such as work piece, grit size, slurry concentration, power rating and tools were changed to explore their effect on the surface roughness. Taguchi’s technique was applied to obtain an optimal setting of ultrasonic drilling (USD) process parameters. Average surface roughness (Ra) was measured by using the Optical Profiling System. Two-dimensional and three-dimensional contour plots were obtained from the profiling system to quantify and visualize the surface roughness. From the experimental results and further analysis, it is concluded that the effect of slurry concentration and grit size have a significant effect on surface roughness more than other parameters. In addition, the surface roughness is apparently similar in two and three dimensions as visualized from contour plots. Ultrasonic drilling is established as a material removal process with good surface quality.     

Empirical modeling and optimization of wire electrical discharge machining

Wire electrical discharge machining is a widely used process in manufacturing industries to machine complex profiles. The performance of any machining process is based on choosing the right combination of input parameters. Metal removal rate and surface roughness are the most important output parameters, which decide the performance of a machining process. The selection of optimal parameters in wire electrical discharge machining is difficult as it is a complex process and involves a large number of variables. The present work models the metal removal rate and the surface roughness in terms of the input variables using the response surface methodology and, consequently, the developed mathematical models are utilized for optimization. Since the influences of machining parameters on the metal removal rate and the surface roughness are opposite, the problem is formulated as a multiobjective optimization problem. Non-dominated sorting genetic algorithm is then applied to obtain the Pareto-optimal set of solutions.     

Single and multiobjective optimization of Inconel 718 nickel-based superalloy in the wire electrical discharge machining

Inconel 718 is widely used in high-temperature environments, high-performance aircraft, and hypersonic missile weapon systems; however, it is very difficult to machine using conventional techniques. This study employed an L9 Taguchi orthogonal array for the analysis of wire electrical discharge machining parameters when used for the machining of Inconel 718. Our aim was to determine the optimal combination of parameters to minimize surface roughness while maximizing the material removal rate. The Taguchi method is widely applied in mechanical engineering with the aim of identifying the optimal combination of processing parameters as they pertain to single quality characteristics. Unfortunately, Taguchi analysis often leads to contradictory results when seeking to rectify multiple objectives. To resolve this issue, this study implemented gray relational analysis in conjunction with Taguchi method to obtain the optimal combination of parameters to deal specifically with multiple quality objectives. For the dual objectives of surface roughness and material removal rate, the optimal combination of parameters derived using gray relational analysis resulted in a mean surface roughness of 2.75 μm. In L9 orthogonal array experiments, run 1 produced the best gray relational grade with mean surface roughness of 2.80 μm, representing an improvement of 1.8%. The material removal rate achieved after the application of gray relational analysis was 0.00190 g/s, whereas the L9 experiment achieved a material removal rate of 0.00123 g/s, representing an improvement of 54.5%.