Optimizing machining parameters of wire-EDM process to cut Al7075/SiCp composites using an integrated statistical approach

Metal matrix composites (MMCs) as advanced materials, while producing the components with high dimensional accuracy and intricate shapes, are more complex and cost effective for machining than conventional alloys. It is due to the presence of discontinuously distributed hard ceramic with the MMCs and involvement of a large number of machining control variables. However, determination of optimal machining conditions helps the process engineer to make the process efficient and effective. In the present investigation a novel hybrid multi-response optimization approach is proposed to derive the economic machining conditions for MMCs. This hybrid approach integrates the concepts of grey relational analysis (GRA), principal component analysis (PCA) and Taguchi method (TM) to derive the optimal machining conditions. The machining experiments are planned to machine Al7075/SiCp MMCs using wire-electrical discharge machining (WEDM) process. SiC particulate size and its weight percentage are explicitly considered here as the process variables along with the WEDM input variables. The derived optimal process responses are confirmed by the experimental validation tests and the results showed satisfactory. The practical possibility of the derived optimal machining conditions is also analyzed and presented using scanning electron microscope examinations. According to the growing industrial need of making high performance, low cost components, this investigation provide a simple and sequential approach to enhance the WEDM performance while machining MMCs.     

Experimental investigation and optimization of machining parameters in drilling of fly ash-filled carbon fiber reinforced composites

Particle-filled polymer composites have become attractive because of their wide applications and low cost. Carbon fiber reinforced polymer (CFRP) is well known as a difficult-to-cut material, which has very strong physical and mechanical characteristics. Machining of carbon fiber reinforced composites is essential to have functional upshots, out of which drilling is the key operation needed for fabrication. In this paper Taguchi L₂₇ experimental design is coupled with grey relational analysis (GRA) to optimize the multiple performance characteristics in the drilling of fly ash-filled carbon fiber reinforced composites. Experiments were conducted on a vertical machining center, and Taguchi L₂₇ experimental design was chosen for the experiments. The drilling parameters, namely spindle speed, feed rate, drill diameter and wt% of fly ash, have been optimized based on the multiple performance characteristics including thrust force, surface roughness, and delamination. The GRA with multiple performance characteristics indicates that the wt% of fly ash and drill diameter are the most significant factors that affect the performance. Experimental results have shown that the performance in the drilling process can be improved effectively by using this approach.     

Machining parameters optimization for satisfying the multiple objectives in machining of MMCs

The metal matrix composites (MMCs) have gained acceptance in an extensive range of applications owing to their high strength to mass ratio. Machining of such complex MMCs is often challenging. It is essential to optimize the controllable machining parameters to simultaneously attain manifold objectives. In the current work, response surface design is created for experiments, and Genetic algorithm (GA) combined with Principal Components Analysis (PCA) coupled Grey Relational Analysis (GRA) is employed to improve the straight turning process of MMCs. The procedure is demonstrated by machining aluminum-based MMC with 25% SiC particulates. The procedure aims at identifying optimal combination of machining parameters to obtain high surface quality at lower cutting force without increasing the specific power consumption. PCA is helpful in providing the individual uncorrelated quality characteristics called as quality indices that do not have any influence on other responses. Individual quality indices have been utilized to obtain the grey relational grade through GRA. GRA has been used to alter manifold quality indices into singular column of grey relational grade as a means to change the manifold objective problem into a sole objective problem. Then, GA has been used to get the optimal parameters combination. The novelty present in this work is the avoidance of correlation existing among the quality characteristics and combining of the GRA and GA. This is an endeavor to augment the performance and accuracy of GA to solve the optimization problem associated with the turning operation.     

Influence of drilling process parameters on hybrid vinyl ester composite

In the modern world, the use of hybrid composite becomes unavoidable. They have their unique and tailor-made properties which makes them suitable for many engineering and industrial applications. But the restriction on the use of composites arises during machining of these composites. Unlike conventional materials, machining of composites is a tedious process due to their anisotropic nature. In the current research work, the prepared high strength hybrid composite is subjected to one of the important machining process say drilling and the process parameters are optimized for the multiple output characteristics namely delamination, torque and thrust force. Taguchi technique aided with grey relational analysis is used for optimization purpose. From the experimental outcome, it is clear that the machining characteristics can be improved at optimum machining conditions. And it is also found that the diameter of the drill has the major effect on the output characteristics.     

Multi-response optimization of the electrical discharge machining of insulating zirconia

In this study, electrical discharge machining has been used to machine insulating zirconia via the assisting electrode method. The process parameter optimization was investigated by combining the Taguchi method with grey relational analysis. The application of Taguchi–grey relational analysis is proven to effectively improve the performance of electrical discharge machining in drilling insulating zirconia. The results of this analysis indicate that the final optimal process parameters are a peak current of 8 A, a pulse duration of 16?µs, a duty cycle of 0.5, and a flushing pressure of 6?MPa. Additionally, the material removal rate, electrode wear rate, and hole taper ratio increase by 39%, 1.5%, and 1.3%, respectively, which improves the grey relational grade by 6.8%. The electrical resistance test confirms that the conductivity of the conductive layer obtained using the final optimal process parameters is better than that of the conductive layer obtained using the initial optimal process parameters. Energy spectrum analysis reveals that the conductive layer is composed of C, Cu, Zn, Zr, and O. Analysis of variance shows that the most significant component of the multi-responses is the peak current, with a 51.4% contribution.     

Investigation of multiple process parameters in abrasive water jet machining of tiles

This paper discusses the optimization of an abrasive water jet machining process with multiple characteristics, using the Taguchi orthogonal array and grey relational analysis (GRA). The machining process variables, such as mesh size, nozzle diameter, abrasive flow rate, water pressure, stand-off distance, and feed rate, were optimized with respect to multiple performance characteristics, namely, the surface roughness and the kerf angle. Experiments were performed using an L₁₈ orthogonal array, and the optimum machining process variables were determined, using GRA. Analysis of variance was used to identify the most significant factor in the machining performance. A confirmatory test was performed to verify the improvement of the performance characteristics. The microstructure of the machined surfaces was also examined by scanning electron microscopy and atomic force microscopy. The results showed that the surface roughness and kerf angle were minimized under optimal machining conditions.     

Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics

This article addresses an approach based on the Taguchi method with grey relational analysis for optimizing turning operations with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. Optimal cutting parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. Tool life, cutting force, and surface roughness are important characteristics in turning. Using these characteristics, the cutting parameters, including cutting speed, feed rate, and depth of cut are optimized in the study. Experimental results have been improved through this approach.     

Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool

The present investigation focuses on the multiple performance machining characteristics of GFRP composites produced through filament winding. Grey relational analysis was used for the optimization of the machining parameters on machining GFRP composites using carbide (K10) tool. According to the Taguchi quality concept, a L27, 3-level orthogonal array was chosen for the experiments. The machining parameters namely work piece fiber orientation, cutting speed, feed rate, depth of cut and machining time have been optimized based on the multiple performance characteristics including material removal rate, tool wear, surface roughness and specific cutting pressure. Experimental results have shown that machining performance in the composite machining process can be improved effectively by using this approach.     

Optimization of Plasma Arc Welding Parameters by Using the Taguchi Method with the Grey Relational Analysis

The optimal parameters process of plasma arc welding (PAW) by the Taguchi method with Grey relational analysis is studied. The Grey relational grade is used to find optimal PAW parameters with multiple response performance characteristics. The welding parameters (welding current, welding speed, plasma gas flow rate, and torch stand-off) are optimized with consideration of the multiple response performance characteristics (the penetration of root, the weld groove width, and the weld pool undercut). As a result, the improvement percentage of the Grey relational grade with the multiple performance characteristics is 31.8%. It is shown that the multiple response performance characteristics are greatly improved through this study.     

Analysis of tribological behaviour of aluminum-titanium carbide-basalt metal matrix composite

In the recent years, particulate reinforced aluminum based matrix composites are playing an important role in automobile and aerospace applications due to their enhanced properties. In this work, an attempt has been made to optimize the tribological behaviour of aluminum 7075 matrix reinforced with titanium carbide (3 percent weight) and basalt particles (2 percent weight) using Taguchi based grey relational analysis. Composites are fabricated according to american society for testing materials standard using stir casting method dry sliding wear tests were carried out using pin on disc apparatus as per Taguchi's L9 orthogonal array. Grey relational analysis was used to obtain the optimum process parameters for multiple quality characteristics such as wear rate and coefficient of friction. Then significant contribution of wear parameters was determined by analysis of variance. A confirmatory test was carried out to validate the test result. Finally, the micro structural investigation on the worn surfaces was performed by scanning electron microscope.     

Experimental investigations into triplex hybrid process of GA-RDECDM during subtractive processing of MMC’s

The use of Al-6063 SiCp metal matrix composites (MMCs) in electronic packaging applications, heat sinks for printed circuit boards and for microwave housings necessitates certain degree of machining operations to meet the specifications of the product. The various conventional and non-conventional machining processes had been used to machine the MMCs. But all such processes have their limitations in providing the desired outcomes. Therefore, the present research endeavor, a new process variant of ECDM for the machining of Al-6063 SiCp MMCs. The developed grinding assisted rotary disk electrochemical discharge machining (GA-RDECDM) process integrates the concept of triplex hybridization. In GA-RDECDM, an abrasive coated rotary disk was used as a tool electrode. The abrasive coated disk provides micro gaps between the tool electrode and work material surface and thereby it results in thin and stable gas film formation. The breakdown of thin and stable gas films produce high frequency, low intensity discharges and consequently improves the machining performance. The additional abrasion action imparted by rotating disk ensures the continuation of ECDM process. The influence of various process parameters including applied voltage, pulse on time, electrolyte concentration and the disk rotation rate on width over cut (WOC) and depth were experimentally investigated. Multi criteria optimization using desirability approach predicts the parametric combination of applied voltage of 99V, pulse on time of 3 ms, electrolyte concentration of 17%wt./vol. and disk rotation rate of 30 rpm as the optimum setting for fabrication of slits on the MMCs. The underlying process mechanism is also investigated and presented with appropriate illustrations. The major contribution of the present research work is the development of a novel method for the fabrication of the slits on MMCs.     

The characteristics of transparent conducting Al-doped zinc oxide thin films deposited on polymer substrates

Al-doped zinc oxide (AZO) transparent, conductive thin films were deposited on inexpensive polyethylene terephthalate substrates, using radio frequency (rf) magnetron sputtering, with an AZO ceramic target (the Al₂O₃ content is approximately 2 wt%). This paper presents an effective method for the optimization of the parameters for the deposition process for AZO thin films with multiple performance characteristics, using the Taguchi method, combined with grey relational analysis. Using the Taguchi quality design concept, an L₉ orthogonal array was chosen for the experiments. The effects of various process parameters (rf power, substrate-to-target distance, substrate temperature and deposition time) on the electrical, structural, morphological and optical properties of AZO films were investigated. In the confirmation runs, using grey relational analysis, the electrical resistivity of the AZO films was found to have decreased from 5.0?×?10^?3 to 1.6?×?10^?3?Ω-cm and the optical transmittance was found to have increased from 74.39 to 79.40%. The results demonstrate that the Taguchi method combined with grey relational analysis is an economical way to obtain the multiple performance characteristics of AZO films with the fewest experimental data. Additionally, by applying an Al buffer layer, of thickness 10?nm, the results show that the electrical resistivity was 3.1?×?10^?4?Ω-cm and the average optical transmittance, in the visible part of the spectrum, was approximately 79.12%.     

Optimization of Process Parameters to Improve Form and Orientation Tolerances in EDM of MoSi2-SiC Composites

In this research, an investigation and experimental work were carried out on electric discharge machining (EDM) of intermetallic base MoSi₂-SiC ceramic composite with copper electrode. It is extremely difficult to machine MoSi₂-SiC composite using conventional machining techniques. However, it can be easily machined by executing spark EDM parameters to induce the correct optimum result. These composites find their application in high-temperature environments, viz. fuel turbo pump rotors, inlet nozzles, combustion chambers, injectors, nozzle throats, and nozzle extensions. The sparking parameters, namely current (I), pulse on time (T_on), pulse off time (T_off), spark gap (SG), and dielectric pressure (DP), were investigated by L₁₈ orthogonal array. The optimal process parameters were determined by the grey relational grade (GRG) obtained through the grey relational analysis (GRA) for multiple performance characteristics, viz. material removal rate (MRR), electrode wear rate (EWR), circularity (CIR), cylindricity (CYL), and perpendicularity (PER). The significant process parameters were obtained by analysis of variance (ANOVA) based on GRG, which showed current, pulse on time, and DP. The results were finally established using a confirmatory experiment, which showed the spark eroding process could effectively be improved.     

A Power Spectrum Analysis of Surface Generation in Ultraprecision Machining of Al/SiC Metal Matrix Composites

Metal matrix composites (MMCs) are well known to be difficult-to-machine materials in ultraprecision machining. To have a better insight into the physical mechanisms involved in the cutting process, a power spectrum analysis is proposed to study the surface generation in ultraprecision machining of aluminiumsilicon carbide MMCs. The results indicate that the power spectrum of a surface roughness profile is correlated well to different process parameters and mechanisms of surface generation. The findings help to formulate the optimum cutting strategy for machining the MMCs.     

Optimization of dry sliding wear behaviour of industrial wastes reinforced aluminium based metal matrix composites

Marble dust and basalt powder are industrial waste generated during the machining of marble stone and basalt rock. This paper presents an approach for the optimization of dry sliding wear parameters of aluminium 7075 reinforced with marble dust and basalt powder hybrid metal matrix composite using Taguchi based grey relational analysis. In this work, the composite is fabricated by stir casting technique and the wear parameters namely load, sliding velocity and sliding distance are optimized with consideration of multi responses such as wear rate and coefficient of friction. Experiments are conducted as per Taguchi's L9 orthogonal array. A grey relational analysis is carried out and grey relational grade is obtained. Based on the grey relational grade, optimum level of wear parameters has been identified by analysis of variance. The test results are validated by conducting the confirmation test. Experimental results have shown that the sliding velocity is the most effective factor among the control parameters on dry sliding wear, followed by the sliding distance and load. Finally, the micro structural investigations on the worn surfaces are performed by scanning electron microscope.     

Wire electrical discharge machining characteristics of AA6061/cenosphere as-cast aluminum matrix composites

Machining of metal matrix composites (MMCs) reinforced with low-density waste byproduct particulates using nonconventional processes is relatively new in the field of material science. However, more attention has been paid for investigations on nontraditional machining of such MMCs currently as the conventional machining may generate additional complexity. This study investigates the wire electro-discharge machining behavior of compo-casted cenosphere-reinforced AA6061 alloys. Cu₆₀Zn₄₀-coated copper wire was used as electrode material. The investigation demonstrates that melting and vaporization are the dominant machining mechanisms. The weight fraction of cenosphere was observed to be the most substantial process variables affecting the cutting rate, on-time, and the wire speed of tool were the next in the order of importance. The presence of nonconductive cenosphere particles along with thermal degradation of the aluminum matrix composites leads to degrading processed machined surface quality. The issues related to wire breakage and poor quality of the machined surface, surface finish, and dimensional accuracy are described in detail.     

Machinability evaluation of Al–4%Cu–7.5%SiC metal matrix composite by Taguchi–Grey relational analysis and NSGA-II

Machinability evaluation of Al–4%Cu–7.5%SiC metal matrix composite (MMC) prepared by powder metallurgy (P/M) process is presented. Specimens are prepared with 99.85% pure aluminum added with 4% copper and 7.5% silicon carbide particles by volume fraction. Scanning electron microscope image shows even distribution of particles in Al-MMC. Turning operation is performed by varying machining parameters and experiments are designed using Taguchi’s Design of Experiments (DoE), an L₉ Orthogonal Array (OA) is chosen. A hybrid Taguchi–Grey relational approach is used to determine the optimum parameters over measured responses flank wear, roughness, and material removed. Analysis of Variance (ANOVA) result shows that the depth of cut is the influential parameter that contributes toward output responses. A metaheuristic evolutionary algorithm nondominated sorting genetic algorithm (NSGA-II) is applied to optimize the machining parameters for minimizing wear and maximizing metal removal. Experiments with optimum conditions show a better improvement in the output conditions.     

Effect of Heat Treatment on the Drilling Performance of Aluminium/SiC MMC

The extremely abrasive reinforcing phases present in metal matrix composites (MMCs) are known to dominate their machining behaviour. Consequently, the properties of the matrix material are often ignored. The work reported here investigated the influence of matrix microstructure on the drilling performance of a 2618 aluminium alloy reinforced with 18% silicon carbide particles. The drills used were 8 mm diameter, titanium nitride coated K10 carbide with through-tool cooling. The workpiece material was drilled in four heat treatment conditions: as-extruded, solution treated and solution treated and aged for 12 and 20 hours. Drilling performance was assessed by measuring the wear on the drills, cutting forces, surface finish and the condition of the worn cutting edges. The results indicated that softer as-extruded and solution treated materials produced less wear and lower cutting forces than the harder aged materials. However, the height of the burrs produced during drilling were found to be greater with the softer materials and the quality of the drilled surface was also inferior. Examination of the worn cutting edges indicated that the wear mechanism was primarily one of abrasion although some attrition and edge chipping was also observed. It was concluded that when drilling these materials, the heat treatment condition of the matrix exerts a significant influence on machinability.     

Fabrication and Machining of Metal Matrix Composites: A Review

Intrinsically smart, metal matrix composites (MMCs) are lightweight and high-performance materials having ever expanding industrial applications. The structural and the functional properties of these materials can be altered as per the industrial demands. The process technologies indulged in fabrication and machining of these materials attract the researchers and industrial community. Hybrid electric discharge machining is a promising and the most reliable nonconventional machining process for MMCs. It exhibits higher competence for machining complex shapes with greater accuracy. This paper presents an up-to-date review of progress and benefits of different routes for fabrication and machining of composites. It reports certain practical analysis and research findings including various issues on fabrication and machining of MMCs. It is concluded that polycrystalline tools and diamond-coated tools are best suitable for various conventional machining operations. High speed, small depth of cut and low feed rate are a key to better finish. In addition, hybrid electrical discharge machining has proved to be an active research area in critical as well as nonconventional machining since last few years. This paper incorporates year-wise research work done in fabrication, conventional machining, nonconventional machining, and hybrid machining of MMCs. Conclusions and future scope are addressed in the last section of the paper.     

Optimization of Dynamic Multi-Response Problems Using Grey Multiple Attribute Decision Making

While many of the previous Taguchi method applications dealt with a state system problem, dynamic multi-response problems have received only limited attention. This study presents a practical and systematic procedure to resolve dynamic multi-response problems based on Taguchi's parameter design. The quality loss function is initially applied to assess the quality performance for each response. The technique for order preference by similarity to the ideal solution (TOPSIS), associated with the multiple attribute decision-making (MADM) method, is then incorporated into the Grey relational model of the Grey system theory. The integrated Grey relational grade (IGRG) relative closeness to the ideal solution is determined as a multi-response performance index for determining the optimal parameter setting. The proposed procedure can not only efficiently determine the optimal parameter setting, but also reduce the conflicts when determining the optimal parameter setting for the multi-response problems. Experimental results obtained from the biological reduction of an ethyl acetoacetate process demonstrate the effectiveness of the proposed procedure.