Machining Of Metal Matrix Composites Research Articles

An optimisation of the internal roller burnishing process for magnesium composites using Taguchi Multi objective optimization method

Machining Metal Matrix Composites with conventional metal removal causes particle debonding and crack propagation. This paper has given enhancing results for magnesium silicon carbide Metal Matrix Composite using an internal roller burnishing process. The optimal process parameters are obtained using a full factorial design and Taguchi Multi Response optimization. The optimized parameters include a spindle speed of 500 rpm, a feed rate of 0.5 mm/rev, and a stock allowance of 0.03 mm. The resulting surface characteristics comprise a surface roughness of 0.1555 µm, an out of roundness of 0.0595 mm, and a surface hardness of 66.9 HV. Scanning electron and atomic force microscope, images analyze the surface topology. Auto parts like transfer case and steering components can use burnished components.

Conventional Machining of Metal Matrix Composites towards Sustainable Manufacturing—Present Scenario and Future Prospects

Conventional Machining of Metal Matrix Composites towards Sustainable Manufacturing—Present Scenario and Future Prospects

A Review on the Machinability Enhancement of Metal Matrix Composites by Modern Machining Processes.

These days, metal matrix composites (MMCs) are being widely utilized in automotive and aerospace industries as prominent alternatives to traditional materials. Owing to their elevated strength-to-weight proportion, exceptional fracture toughness, and lightweight design, they can be used in a variety of applications. MMCs undergo extensive machining while making parts and components out of them. The machining of monolithic materials, such as metals and alloys, is a widely used and established process in different industries, such as the aerospace, bio-medical, and automotive sectors. Because of the properties of the metal matrix and the strong reinforcement, MMCs provide unique challenges. Modern machining processes have been found to be superior in overcoming challenges and achieving improved machinability of MMCs. An overview of MMC machining with modern methods is provided in this article. This article first outlines MMCs and addresses the need for and difficulties associated with their machining. Next, it reviews previous investigations on the machining of MMCs employing modern methods like electrical discharge machining, laser machining, abrasive machining, and hybrid machining. Productivity and surface integrity issues, including delamination and roughness, etc., are discussed. When presenting the review, the benefits and drawbacks of modern processes are also taken into account.

A Comprehensive Investigation into the Material Removal Capability of Powder Mixed Wire Electric Discharge Machining

The powder mixed electric discharge machining (PMEDM) has demonstrated promising results in the machining of difficult-to-cut materials including metal matrix composites (MMCs). Adding powder particles to the dielectric fluid used in electric discharge machining (EDM) improves material removal rate (MRR) and surface quality of the machined item. This study presents a thorough overview of research works on PMEDM for the machining of MMCs, concentrating on the impacts of different process parameters on the MRR and surface quality, such as powder concentration, pulse on-time, and Pulse off-time. The study also notes the process's obstacles and limits, as well as opportunities for further research.
 Previous research has shown that PMEDM can greatly increase the MRR and surface quality of machined MMCs when compared to regular EDM. The addition of powder particles to the dielectric fluid has been found to improve machining zone cleansing and cooling, decreasing tool wear and enhancing machining precision.

A comparative study on the machinability of Mg-based composites: Cemented carbide and cubic boron nitride tools performance

Machining of metal matrix composites (MMC) is a challenging process as they are difficult to cut and cutting tools get worn out in a short time. In this paper, the performance of two industrial carbide grades and a cubic boron nitride (CBN) tool are assessed when machining of AZ91/SiC composites. Mg-based composites with different volume fractions and particle sizes are machined at various cutting conditions to evaluate the tools wear resistance and finished surface. The surface of the worn-out tools and machined samples are analyzed by scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), and roughness tester. Results revealed that the tool wear increased for composites reinforced by smaller particles regardless of the tool type. Additionally, tool grade TH1000 resulted in longer tool life when machining of Mg-based composites compared to the CP500 grade so that at a cutting speed of 70 m/min and feed rate of 0.1 mm/rev, tool life improved nearly 250%. CBN tools showed the best performance when machining of Mg-based composites as tools became worn out after 255 s which is considerable compared to carbide tools. Also, the finished surface caused by cemented carbide CP500 indicated the worst quality.

Cutting fluid role in the machinability of AZ91/SiC composite: Tool wear and surface roughness

Metal matrix composites (MMC) introduced special features such as resistance to wear and high strength to weight ratio and these characteristics categorized them as difficult-to-cut materials in the field of machining. In the current paper, a novel study on the cutting fluid emulsion 5% role in the machinability of a magnesium-based metal matrix composite reinforced by silicon carbide (SiC) particles is presented. AZ91 magnesium alloy, with nominal composition Mg-9Al-1Zn, composites were made using stir casting method. Then, the composite samples were machined and the cutting parameters such as cutting speed, feed rate and side cutting edge angle were varied to assess their effects on the wear and surface roughness. To measure and analyze the wear, optical and scanning electron microscope (SEM) were used. Also, elemental analysis through energy-dispersive X-ray spectroscopy (EDS) was accomplished. Surface roughness of machined samples were measured by a profilometer and 3D surface topography. Results of SEM and EDS images indicated that SiC particles included in the composites act as grinders and remove the surface of tool even in a short time because of the severe abrasion. Additionally, surface of machined MMCs contains some defects such as cracks, broken SiC, and unwanted deformations. Using cutting fluid emulsion 5% enhanced the tool life as well as the surface quality remarkably for different cutting speeds, feed rates and cutting edge angles although finished surface of the samples were oxidized. Also, the cutting fluid considerably reduced the amount of adhered materials on the flank face.

Tool wear reduction in ultrasonic vibration-assisted turning of SiC-reinforced metal-matrix composite

In recent years, metal matrix composites (MMCs) have attracted the interest of various industrial sectors thanks to the benefits they offer in terms of lightness and mechanical properties compared to equivalent non-reinforced metallic alloys. Nevertheless, when machining MMCs, their heterogeneous structure, specifically characterized by the presence of hard particles within a much more ductile matrix, induces different thermal and mechanical loads when the cutting edge passes through the various composite constituents. This, in turn, may drastically reduce the cutting tool life as well as deteriorate the part surface integrity leading to poor in-service performances of the part. Nonconventional machining methods are usually employed to manufacture parts made of MMCs, nevertheless at the cost of scarce workpiece surface integrity and increased manufacturing burdens. To overcome the above-mentioned issues, ultrasonic vibration-assisted turning (UVAT) is proposed in this study as an efficient approach to machine MMCs. Turning trials with and without the application of ultrasonic vibration were carried out at varying cutting speeds, feed and volume of removed material. The tool wear mechanisms were identified and quantified. The surface finish and chip morphology were also analyzed as further machinability parameters for comparing the different machining approaches and assessing the advantages of UVAT. The obtained experimental results showed that the adoption of ultrasonic vibrations together with high feed can significantly increase the tool life, representing a suitable approach for efficiently machining MMCs.

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Machining of metal matrix composites (MMCs) has now become an essential task in shaping them to their final usable forms for various industrial applications. These machining operations may range from drilling of simple through holes to cutting and shaping of the composites into complex shapes. Determination of the optimal process parameters during their machining presents a combinatorial optimization problem, which may turn out to be more complex due to involvement of various material dependent parameters of the MMCs, like particle size, reinforcement percentage etc. The importance of optimization increases manifold due to conflicting settings of different process parameters for attaining the desired quality characteristics. In this paper, two nature-inspired optimization algorithms, i.e. multi-objective antlion optimization (MOALO) and multi-objective dragonfly algorithm (MODA) are applied for optimization of various process parameters during machining of MMCs. To mitigate uncertainties in global optimality of the predicted Pareto optimal fronts arising due to stochastic nature of the metaheuristics, an ensemble approach integrating MOALO and MODA techniques is proposed here. It is demonstrated with the help of two case studies that MOALO-MODA ensemble is far superior to its individual counterparts and thus, can be employed for development of robust and reliable Pareto optimal fronts.

Review on Removal Mechanism and Process Modeling in Machining of Metal Matrix Composites

Review on Removal Mechanism and Process Modeling in Machining of Metal Matrix Composites

The electrochemical degradation, wear behavior and machining of metal matrix composites based on 6xxx aluminum alloy with ceramic particulate reinforcements; a brief review

6xxx series aluminum alloy-based metal matrix composite materials are finding greater applicability in various fields like marine, aerospace and automobile industries. In fact, the diverse nature of the availability of ceramic particles and the hybrid combinations of the reinforcements make them versatile in superior properties as well as applications. More over these composites are latest additions to the novel materials developed in recent decades and hence the end products of these composites are reaching the markets in recent times after several years of optimization studies. There is a need to compose the material properties as a review document so that the research on the same domain will get accelerated. Hence it is appropriate to make a comprehensive study about 6xxx aluminum alloy-based metal matric composites in terms of its corrosion behavior in aggressive environments, wear behavior in engineering applications and feasibility of manufacturing the end products using the composite.

Cutting tool selection for machining metal matrix composites

Cutting tool selection for machining metal matrix composites

Investigation on the optimal machining of Mg-based composites considering surface roughness, tool life, cutting forces, and productivity

Machining of metal matrix composites (MMC) are being increasingly taken into consideration due to MMCs’ especial features like high strength to weight ratio, resistance to wear and creep. In this paper, effects of cutting parameters on the surface quality, tool life, and cutting force when machining of AZ91/SiC composites are analyzed to make the process optimized. To this end, a design of experiment based on the response surface methodology are done to consider variations of cutting parameters such as cutting speed, feed rate, and depth of cut. Challenges like particles pulled out and tool worn out in the machining process are evaluated. Subsequently, the results of cutting responses are analyzed and a multi-objective optimization is applied on the data to obtain the best surface quality, the highest production volume and the condition at which tool life is longest. The results showed although increasing the feed rate from 0.05 to 0.1 mm/rev leads to the tool life reduction about 70%, it enhances the productivity considerably about 100% for composites with volume fraction 5%. Moreover, at cutting speed 41.05 m/min and feed rate 0.07 mm/rev, machining process of AZ91/SiC-vol.5% becomes efficient.

Investigation of machinability of Ti–B-SiCp reinforced Cu hybrid composites in dry turning

MMCs (metal matrix composites) are widely used in many industrial applications thanks to their high specific strength. Nevertheless, this also poses a great challenge to their machinability due to rapid tool wear and poor surface finish caused by the added reinforcement particles. Improving the machinability of MMCs is of great importance as it will increase their performance and areas of applications. In this study, the machinability of Cu composites reinforced with Ti–B–SiC powder particles (0-2-4-6-8 wt.%) produced at different rates using powder metallurgy method was investigated. Cutting speed (Vc: 100–150 m/min) and feed rate (fn: 0.2–0.4 mm/rev) were used as cutting parameters. The effects of these parameters on surface roughness, flank wear, and cutting temperature were investigated. As a result of the turning experiments, it was observed that the surface roughness decreased with increasing reinforcement ratio, and thus the best surface roughness (Ra = 0.22 μm) was observed in the 8 wt.% reinforced sample. The cutting temperature and flank wear values increased as the reinforcement ratio increased. It was observed that cutting temperature at the chip–tool interface was the lowest (76 °C) in MMCs sample with 2 wt.% reinforcement. The lowest flank wear (0.93 mm) was also observed in the 2 wt.% reinforced sample. In addition, the chip morphologies of all samples produced at different ratios were investigated after the turning process.

Comparative study of machining quality for the Al–SiC–Gr hybrid metal matrix composite using ECM and ECSG

Hybrid metal matrix composites have superior strength to weight ratio as compared with conventional composites or superalloys. This characteristic makes them suitable for different advanced industries such as aerospace, automobile, and biomedical. Mechanical and thermal energy based processes have their own limitations to machine these composites due to superior mechanical properties and melting of reinforcement particles, respectively. Researchers are trying to machine metal matrix composites by the electrochemical process with the aim to achieve better machining quality, but low material removal rate and oxide layer formation on the machined surface has emerged as the main limitation. A hybrid variant of electro-chemical machining (ECM) and conventional grinding has capability to overcome these limitations. Keeping this in view, the experimental set-up of electro-chemical surface grinding (ECSG) has been developed with the aim to compare the machining characteristics of the hard-to-cut hybrid metal matrix composite Al–SiC–Gr with the ECM process. The machining performances have been compared on the basis of material removal rate, surface roughness, and microcrack width in the machined component. The influence of some important input process parameters on these performance characteristics have been analyzed scientifically. Experimental results show that the ECSG process improves the machining performance by reducing or eliminating the oxide layer from the machining zone due to suitable grinding effects. Material removal rate, surface roughness, and microcrack width were improved by 68%, 24%, and 40%, respectively, by using the ECSG process. The formation of the large size oxide layer with high crack width on the machined surface was observed at high voltage, high electrolyte concentration, and at low table speed.

Effect of Machining Parameters for Surface Finish and Material Removal Rate of Al-4032/SiC Composite During End Milling Using TGRA and ANN

The machining of metal matrix composites (MMCs) creates an extra challenge as compared to that of metals and alloys due to their hardness owing to the abrasive reinforcement particles. This paper presents the study on end milling of Al-4032/3% SiC composite considering the cutting speed (CS), feed rate (FR) and depth of cut (DOC) as the process parameters. Surface finish and material removal rate (MRR) have been taken as the response parameters. The Al-4032-based AMC has been prepared using stir casting process. Taguchi’s [Formula: see text] orthogonal array (OA) has been used for experimental trials. The optimum setting of the parameters has been obtained using TGRA. The resulting surface roughness (SR; [Formula: see text]) occurs in the range of 1.18–3.97[Formula: see text][Formula: see text]m, with the minimum value corresponding to the CS of 110[Formula: see text]m/min, FR of 0.05[Formula: see text]mm/tooth and DOC of 1.2[Formula: see text]mm. Bayesian regularization (BR), scaled conjugate gradient (SCG) and Levenberg–Marquardt (LM) algorithms have been employed for training, validating and testing the 3–[Formula: see text]–1 and 3–[Formula: see text]–2 ANN architectures ([Formula: see text]). Minimum root-mean-square error (RMSE) has been taken as the standard for evaluating the model. Neural network toolbox of MATLAB “R2019A” has been used for prediction of the response.

Optimization of machining parameters in drilling of LM6/B4C/Fly ash hybrid composites

Metal matrix composites (MMCs), innovative replacements for traditional materials, are currently achieving a growing trend in engineering and research for operations like aviation, nuclear power, and automotive. Machining of MMCs makes it challenging to get good dimensional accuracy, surface finish and lower tool wear. Drilling is a necessary and immensely useful tool for component assembly in the manufacturing sector. As a result, optimization of drilling process variables is unavoidable. The fundamental purpose of this study is to use the stir casting technique to manufacture LM6/B4C/Fly ash composites with 3, 6 and 9 wt.% of second phase materials. Taguchi's design of experiments strategy was used to drill with three levels of feed rate (F), spindle speed (S), drill material (D) and percentage of reinforcement (R) as input process parameters. Optimization of drilling variables for attaining lower surface roughness (SR) and burr height (BH) using single objective approach. The optimum process variable achieved for surface roughness is F1S3D3R2, i.e., 50 mm/min, 3000 rpm, TiN-coated drill bit and 6 wt.% of reinforcements (B4C and Fly-ash) and for burr height is F1S3D3R3, i.e., 50 mm/min, 3000 rpm, TiN-coated drill bit and 9 wt.% of reinforcements.

Parametric Optimization of Electric Discharge Machining of Metal Matrix Composites Using Analytic Hierarchy Process.

The present study reports on the method used to obtain the reliable outcomes for different responses in electric discharge machining (EDM) of metal matrix composites (MMCs). The analytic hierarchy process (AHP), a multiple criteria decision-making technique, was used to achieve the target outcomes. The process parameters were varied to evaluate their effect on the material erosion rate (MER), surface roughness (SR), and residual stresses (σ) following Taguchi’s experimental design. The process parameters, such as the electrode material (Cu, Gr, Cu-Gr), current, pulse duration, and dielectric medium, were selected for the analysis. The residual stresses induced due to the spark pulse temperature gradient between the electrode were of primary concern during machining. The optimum process parameters that affected the responses were selected using AHP to figure out the most suitable conditions for the machining of MMCs.

Optimum performance evaluation during machining of Al6061/cenosphere AMCs using TOPSIS and VIKOR based multi-criteria approach

Selection of optimal processing condition is an issue associate with multi-criteria decision making (MCDM) which can be influenced by several conflicting processing variables. The present study have been devoted to the implementation of TOPSIS algorithm in coordination with the VIKOR technique to yield an optimistic processing criteria while machining of metal matrix composites under electro-discharge machining process. A decision-making module has been developed for selection of optimum processing conditions under specified machining conditions. An experimental investigation was performed based on Taguchi’s orthogonal array on the newly prepared AA6061-cenosphere MMCs to analyze the sensitivity of EDM attributes to the process parameters such as peak current, pulse on time, the percentage of reinforcement, and flushing pressure. The weighing factors for the criteria were determined using AHP method. The results concluded that both the applied MCDM approaches, TOPSIS and VIKOR accrue the similar possible optimal solution having optimal value of pulse current 10 A, pulse on time 1010 µs, percentage of reinforcement as 2% and flushing pressure as 0.6 MPa.

Surface integrity in machining of AZ91/SiC composites

Use of metal matrix composites (MMC) is growing due to their high strength-to-weight ratio, resistance to wear, creep, etc. Machining of metal-matrix composites (MMC) faces many challenges, especially with regard to obtaining a finished surface with high quality. In this research, AZ91/SiC samples with different volume fractions are machined at different cutting conditions with respect to feed rate, cutting speed, and depth of cut. Surface integrity of the machined samples is analyzed by different methods such as tactile profilometer and 3D surface topography to investigate the SiC effects on the finished surface. Additionally, sample surfaces are evaluated by scanning electron microscope (SEM) and with energy-dispersive X-ray (EDS) to assess the surface defects formed around reinforcement materials. Results indicate SiC particles decline the surface quality and uniformity due to the formation of some defects such as micro cracks, holes, and undesired deformations when the cutting process. Also, subsurface SiC particles close to the machined surface are cracked after machining.

Optimisation of Drilling Parameters of Metal Matrix Composites using Genetic Algorithm in the Taguchi Method

This work presents the machining parameters optimization on machining metal matrix composites using genetic algorithm in the Taguchi method with the objectives of minimization of surface roughness, cutting force, maximization of metal removal rate, cutting power, specific cutting energy, cutting power and machining time. Experiments were conducted on aluminium silicon carbide Metal Matrix composite using TiN coated HSS twist drills. Optimal setting of parameters have been identified using Taguchi Technique and Genetic algorithm. Genetic algorithm is developed in ‘C’ language. The presented work gives a better results and it can be used for any machining parameter optimization in solving multiple response problems.