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Abstract The creation of new alloys with improved qualities has become essential in modern industries for high-performance materials. This work’s main objective is to use vacuum arc melting (VAM) to synthesize two different high-entropy alloys (HEAs): AlCrFeNiCu and AlCrFeNiCo. The mechanical properties, phase composition, grain boundaries, and alloy composition of the HEAs were studied. The predominant crystal structure, the Body-Centred Cubic (BCC) phase was obtained for both alloys. Significantly, the Co-containing HEA showed a smaller particle size than the Cu-containing HEA, which led to a 14.21% increase in microhardness. It indicates that the Co-based HEA will likely perform better than the Cu-based HEA in applications prone to abrasion, and indentation, and requiring high hardness levels based on the observed microstructure and hardness parameters. According to wear surface morphology studies, main effects analysis and ANOVA show that increasing loads and sliding distances increase wear rate, whereas sliding velocity has less effect. The best wear rate-reducing parameters are 10 N, 0.5 m/s, and 500 m for Cu-containing HEAs, and the same can be predicted using regression analysis. The study categorizes the intricate worn surface structure by describing different surface properties and wear mechanisms, such as grooves, delamination, adhesive wear, and pitting.

Abstract The integrity of dissimilar Al-Ti welds during conventional friction stir welding (CFSW) is compromised by excessive material mixing, leading to thick intermetallic layers. Underwater friction stir welding (UWFSW) mitigates these effects by inhibiting material mixing due to lower thermal conditions. Scanning electron microscopy revealed substantial Ti particles, appearing as blocks and strips, within the stir zone during CFSW. Static recrystallization, driven by exothermic reactions between Ti blocks and the Al matrix, resulted in over 93% recrystallized grains along stir zone, 10.7% higher than in UWFSW. In contrast, UWFSW resulted in a finer dispersion of Ti particles with reduced density due to lower frictional heat. The average grain size at the Ti interface of CFSW was 1.0 μm, compared to 2.6 μm in UWFSW. The inhomogeneous distribution of Ti particles in CFSW led to uneven dislocation distribution and increased stress concentrations, while finer Ti particles in UWFSW promoted a uniform grain structure, enhancing joint strength to 267 MPa, 13.4% higher than CFSW. Additionally, the γ-fibre and basal fibre texture in UWFSW increased joint ductility. The study highlights UWFSW’s effectiveness in joining dissimilar metals, offering significant advantages for industries such as aerospace and automotive.

Ti-6Al-4 V is an extensively used and highly versatile titanium alloy. It is renowned for its lightweight-to-strength ratio, excellent biocompatibility, and corrosion resistance. The pursuit of advanced materials with enhanced mechanical strength, and wear resistance has led to the exploration of high entropy alloys (HEA) as particle reinforcements. This study combines Ti-6Al-4 V with AlCoCrFeNi HEA at different weight compositions (0 %, 2 %, 4 %, 6 %, 8 %) to create novel composites with tailored properties. The composites were subjected to density, microhardness, tensile, and pin-on-disc tests to evaluate mechanical and tribological properties. Microstructural analysis revealed that microwave sintering has enhanced densification and resulted in uniform dispersion of HEA particles within the Ti-6Al-4 V matrix. The XRD and EBSD analysis revealed the presence of BCC structure in the composite. 8 wt%-AlCoCrFeNi/Ti-6Al-4 V sample exhibited an impressive 81.66 % increase in microhardness and 21.23 % in yield strength, compared to the base sample. Furthermore, noteworthy reductions of 45 % in wear rate and 40 % in coefficient of friction (COF) when subjected to tribological analysis. The worn surface revealed the presence of oxide layer formation at elevated sliding velocity and distance which resulted in reduced wear rate.

Abstract Surfaces are commonly enhanced with wear-resistant coatings to improve their resistance to abrasion, erosion, and other forms of wear. These coatings play a crucial role in extending the lifespan and improving the performance of materials and components exposed to challenging conditions. The objective of the current study is to deposit thermally sprayed 3-layer TiC–12Co–10ZrO2/NiCoCrAlMo functionally graded coatings on SS410 substrates using atmospheric plasma spray. The results revealed that by employing appropriate ceramic proportions, the microhardness of graded coatings increased to 990.4 HV, which is approximately 3.21 times higher than that of the substrate. Furthermore, the tribological properties of graded coating exhibited superior resistance compared to the substrate, where process settings were varied. Specifically, graded coating samples subjected to the applied load, sliding distance, and sliding velocity showed improved wear resistance of 78.51%, 68.42%, and 76.66% respectively in extreme conditions compared with uncoated samples. The characterization of the worn surface revealed a sequential occurrence of wear mechanisms: abrasive, adhesive, and delamination. The formation of TiO2 and Cr2O3 tribo-oxide film protects the surface against the wear mechanism and is applicable in extreme wear environments.

Current advancements in technology enables the enhancement and refinement of alloys to address the demands of expanding industrial applications. High Entropy Alloys (HEAs) are a developing class of alloys displaying unique and advanced mechanical, tribological, thermal stability, and corrosion properties. HEAs have unpredictable structures and compositions displaying enhanced performance and characteristics. Unique microstructures can be achieved through multi-principal elements and HEAs usually outperform conventionally made alloys. Lightweight HEAs (LWHEAs) are a category of HEAs with alloy density less than 6 g/cm3 and are potentially applicable in the automobile and aerospace industries. The superior characteristics make LWHEAs an extremely interesting space for research. Recent research has focused on effective manufacturing methods for processing alloys, coatings, and surface modifications. The current work discusses a comprehensive review of fabrication processes, mechanical, tribological, and corrosion behavior of LWHEAs. The review also highlights the future scope of research and directions for designing LWHEAs. The results of the article provide crucial information to researchers and pioneers exploring LWHEAs.

Abstract The present work demonstrates the development of SiC/TiS2/AlSi12Cu hybrid functionally graded composite using centrifugal casting and examines its microstructural, mechanical, and tribological properties. A gradient distribution of reinforcement particles was observed with the outer region being particle-rich. EBSD analysis confirms microstructural refinement owing to titanium’s grain refining properties and the formation of θ-Al2Cu intermetallic phase. The outer layer of the composite attained a maximum hardness and tensile strength of 93 HB and 202 MPa respectively, which was increased by 7.5% and 8.2%, 20.4% and 13.8%, 22.5% and 44.5% in middle, inner, and as-received alloy respectively. Tribological properties were assessed via dry sliding pin-on-disk tribometer with various process parameters such as load (10–40 N), velocity (1–4 m/s) and distance (500–2000 m), optimized using response surface methodology. The higher wear resistance was attained by the optimized process parameters of 16 N load, 1.6 m/s velocity, and 804 m distance. Results indicated increased material loss with higher load, sliding distance, and velocity, but with enhanced wear resistance in the outer zone. Worn surface analysis revealed deeper grooves, delamination, particle pull-out, and wear tracks under severe conditions. The study emphasizes the composite’s potential for high wear applications, linking its microstructural features to its superior wear behavior.

High-entropy alloys (HEAs) are a category of material with exceptional mechanical, thermal, and chemical properties, making them suitable for a wide range of applications in industries such as aerospace, automotive, and energy storage. The wear rate is a crucial property in determining the reliability and performance of HEAs. It is crucial to accurately predict wear rates when optimizing material for selection and design. This study uses Machine Learning (ML) techniques to create predictive models for wear rate prediction in HEAs. Five regression models, including Linear Regression (LR), Support Vector Regression (SVR), Bayesian Ridge Regression (BRR), Multilayer Perceptron (MLP), and Huber Regression (HR) are built and evaluated. These models are built using a dataset featuring elemental compositions, applied load, sliding distance, sliding velocity, and wear rates of HEAs. The results show that the MLP regressor outperforms other algorithms in terms of accuracy and model fit when predicting wear rates. For phase prediction of non-existing HEAs, Recurrent Neural Networks (RNNs) and Extreme Gradient Boosting (XGBoost) models are employed. Using the output from these phase predictions as input variables, the wear rate of these non-existing HEAs is predicted at different conditions. The prediction provides a large dataset with phase and wear prediction of non-existing HEAs, which can be experimentally designed later for specific applications. The present study highlights the potential of ML techniques in developing materials science and engineering by allowing the design of HEAs with tailored properties for specific applications.

Hydrogen is a clean energy carrier and has potential applications in energy storage, power generation, and transportation. This study explores the efficient and safe storage of hydrogen, particularly through solid-state methods using high entropy alloys (HEAs). HEAs have garnered attention for their versatility in tailoring properties for hydrogen storage. The integration of Machine Learning (ML) in designing HEAs offers an expedited approach, analyzing datasets and predicting material properties to enhance storage capacity, kinetics, and stability. Despite significant progress, the study acknowledges certain research limitations, particularly its relatively narrow focus on applying ML to HEAs for hydrogen storage. One of the biggest challenges with HEAs is their complexity, which.necessitates larger datasets to develop accurate predictive models. Collecting and analyzing existing HEA data for hydrogen storage using ML techniques is the main objective. Using algorithms like support vector regression (SVR), K-nearest (KNN), and random forest (RF), hydrogen-to-metal ratio (H/M) and valence electron configuration (VEC) are accurately predicted. The study proposes alloys with potential for HEA formation, identifying 741 with quaternary and 631 with quinary HEAs. These compositions are newly proposed and do not yet exist. Out of these, 774 HEAs are identified as potential candidates for hydrogen storage applications. Applying ML techniques, the selection process is more efficient, reducing the dependency on time-consuming experiments and making it easier to discover promising candidates.

The High Entropy Alloy (HEA) coatings exhibit diverse properties contingent upon their composition and microstructure, addressing current industrial requirements. Machine Learning (ML) regression emerges as a proficient solution for predicting the properties of HEA coatings, offering a significant reduction in experimental work. The ML regressions including Support Vector Regression (SVR), Gaussian Process Regression (GPR), Ridge Regression (RR), and Polynomial Regression (PR), are effectively employed to predict Young's modulus of HEA coated Stainless Steel (SS) through a significant database. The statistical responses of the developed regression models are analyzed through evaluation indices of Coefficient of determination (R2), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Among the regression models, the 2-degree PR model stands alone with a high prediction accuracy of R2-0.95, MAE-16.12, and RMSE-21.53. The 2-degree PR model demonstrates a significant correlation between the predicted and experimental Young's modulus, contributing to the accurate prediction of unknown Young's modulus of the HEA-coated SS. The prediction of Young's modulus by the PR model is more reliable, as proved by an error percentile of ±4.76 %, compared to the experimental values of Young's modulus.

High Entropy Alloys (HEAs) are currently a subject of significant research interest in the fields of materials science and engineering. They are rapidly evolving due to their exceptional properties, and there is considerable focus on expanding their application potential by developing HEA coatings on various substrate materials. This area of study holds promise for advancing technology and innovation in diverse industries. In this study, a novel equiatomic AlBeSiTiV Light Weight HEA was synthesized via mechanical alloying and was sprayed on the substrate SS316 by the thermal spray process. The microstructural characterization revealed that synthesized HEA had a major FCC phase and the average coating thickness was observed to be 150 μm. The average microhardness was measured to be 975 ± 13 HV for the coating which was five times than the substrate. The coated samples' wear resistance was found out using a pin-on-disc apparatus by varying the wear process parameters and Taguchi's L27 Orthogonal Array was used to interpret the parametric influence on wear rate. ANOVA and regression analysis revealed applied load to be the most significant factor followed by distance and velocity. The major wear mechanisms observed were adhesion abrasion and oxidation, and the formation of tribolayer was observed at higher velocity and distance.

Abstract The ability to endure extreme corrosion in challenging environments is reduced in stainless steel. This can be addressed by appropriate surface modification techniques to redefine the surface with the required properties. The characteristics of the atmospheric plasma sprayed AlCoCrFeNi High Entropy Alloy (HEA) on SS316l are presented in this study. The coating characterisation revealed uniform coating with homogeneous deposition of gas-atomized AlCoCrFeNi HEA spanning for 150 µm. The coated substrates were further annealed for 2 h at 400 °C, 550 °C, 700 °C and 850 °C and the annealing at 550 °C offered enhanced microstructure. Annealing the coated sample at 550 °C offered a 46% improvement in microhardness against the uncoated sample post-annealing. The electrochemical corrosion tests showcased improved corrosion resistance after annealing through the formation of a protective oxide layer and the influence of HEA. Hot corrosion tests at 900 °C resulted in 10.1%, 8.49%, and 10.36% improved corrosion resistance for the coated sample annealed at 550 °C than the coated sample pre annealing and 44.09%, 44.25%, and 42.09% than the uncoated sample pre annealing under three salt mixtures respectively. The microstructural analysis examines various corrosion modes and verifies the presence and formation of protective oxide layers.

Abstract Surface modification by suitable technique aids in improving the characteristics of material to resist severe wear in demanding environments and challenging applications. The present study aims to analyse the tribological performance of Stainless Steel (SS304) reinforced with CoCrCuFeTi High Entropy Alloy (HEA) through friction stir processing and compares the results with annealed specimens. The CoCrCuFeTi HEA was ball milled and revealed irregular fragment particles with Body Centred Cubic (BCC) phase. The processed samples exhibited excellent refinement in grains with uniform HEA reinforcement distribution. The grains were observed to be in nano level post-annealing promoting exceptional microhardness. The pin-on-disc wear test was conducted by varying load (10-40N), sliding velocity (0.5–3.5 m/s) and sliding distance (500–2000 m) and the respective worn surface was analysed. The processed sample with HEA after annealing offered 29.8%, 57.4% and 58.49% improved wear resistance at the minimum level of load, sliding velocity and sliding distance than the processed base samples. The worn morphology revealed delamination, abrasion, adhesion and oxide layer formation to be the predominant wear mechanisms.

Ceramic coatings are necessary for steel as they offer resistance to corrosion, high-temperature degradation, and abrasion, thereby enhancing the wear characteristics of steel structures. Evaluating the wear rate of Ceramic-Coated (CC) steels is crucial for enhancing the reliability and longevity of steel components. Various factors such as microstructural features and operating conditions complicate the wear analysis of CC steel. To overcome this obstacle, the present study employs several Machine Learning (ML) models such as Elastic Net Regressor (ENR), Robust Regressor (RR), Extreme Gradient Boosting Regressors (XGBoost), and Bagging Regressor (BR), to predict the wear rate of CC steel. Pearson Correlation Coefficient (PCC) revealed that the hardness of the coating greatly affects the wear rate. Among various ML regressor models, the BR model exhibited the optimum performance with the R2 of 0.93 with ENR, RR, and XGBoost exhibiting lower R2 values of 0.79, 0.84, and 0.89 respectively. Eventually, the BR model is used to predict the wear rate of TiN and Al2O3-coated steel, and the experimental results of the same are compared. The comparison of results revealed an error percentage of ± 7.78% between the experimental and predicted wear rate.

Titanium alloys are widely used in various industrial applications due to their excellent properties. Due to its excellent heat conductivity and stability, graphene (Gn) can help Ti components last longer and experience less wear. In the current study, Ti6Al6V2Sn (Ti662) with various wt.% Gn was produced. The composite samples were subjected to metallurgical characterization to analyze the influence of Gn addition in the microstructure and phases formed. The properties such as microhardness and wear resistance were analyzed for all the samples. Variations in the load, sliding velocity, and distance were made during the wear test, and the effects of these factors on the wear rate and morphology of the worn surface were examined. Mechanical property analysis revealed that Ti662 + 0.5Gn exhibited the highest microhardness of 514.32HV, which was 1.45 times that of the matrix material. The sample with 0.5Gn exhibited increased wear resistance, the order of wear resistance observed was Ti662 + 0.5Gn > Ti662 + 0.75Gn > Ti662+1Gn > Ti662 + 0.25Gn > Ti662. The wear rate was reduced by 44.15 % at 40 N, 42.07 % and 52.02 % at 1.5 m/s and 2000 m for Ti662 + 0.5Gn composite. Worn surface morphology revealed that at elevated loads, abrasive and delamination wear was observed while at elevated velocity and distance, the formation of mechanically mixed layer (MML) was observed.

The performance loss in industrial equipment due to friction and wear is one of the critical concerns among researchers. This drives the need to develop lubrication fluids that reduce friction to provide extended performance. The global sustainability movement drives the research towards novel bio-based oils to aid in lubrication. This study analyses the dispersion stability, tribological behaviour and antiwear properties of zinc oxide (ZnO), titanium dioxide (TiO2) and molybdenum di sulphide (MoS2) nanoparticles as an additive in hazelnut and sunflower oils. The viscosity index and flash point of the prepared nano lubricants were analyzed. The tribological test conducted on four ball tester resulted in a 12.6% and 35.8% reduction in coefficient of friction (COF) for 0.5% ZnO in hazelnut oil and 1% MoS2 in sunflower oil. The corresponding wear scar images were analysed. The extreme pressure (EP) test resulted that 1% MoS2 in sunflower oil exhibiting improved performance as it sustained a 1800N load. The kinematic viscosity of the 0.5% ZnO in hazelnut oil and 1% MoS2 in sunflower oil had an improvement against others. Therefore, infusion of nano additives in bio-oils offers enhanced tribological properties foreseeing sustainability in applications.

The equimolar High Entropy Alloy (HEA) is incorporated on the surface of SS410 steel to enhance the mechanical properties for the current industrial scenario. The objective of the present work is to make a first attempt at surface modification of SS410 steel with gas atomization synthesized AlCrCoFeNi HEA powder through Friction Stir Processing (FSP). The microhardness and ultimate tensile strength of the FSP-HEA sample are increased by 41.3 % and 39.1 % respectively due to the high degree of refined grains with 2.84 μm and evenly distributed HEA particles. The wear rate of FSP-HEA samples is optimized by response surface methodology with process parameters including applied load, sliding distance, and sliding velocity. The most influential factor and regression model are derived from experimental results that predict the wear rate by the analysis of variance technique. The worn surface of FSP-HEA samples is evaluated by morphological analysis with corresponding induced wear mechanisms. The minimum wear rate is achieved by optimum process parameters along with higher hardness through particle-stimulated nucleation mechanism, Hall-Petch relation, and dynamic recrystallization. The grain refinement, barrier effect, and grain growth hindrance of HEA particles lead to enhancement in the strength of processed HEA samples.

Carbon fiber reinforced polymer (CFRP) has been in high demand over the last few decades, especially in the aircraft manufacturing industry, due to their superior properties. However, drilling of CFRP materials is more complicated than common metal due to their exceptional anisotropic and non-homogenous features. This unique microstructure often leads to drilling-induced defects such as delamination, thermal damage and burr formation which compromises the structural integrity. Therefore, a good understanding of this composite material is required to realize its full potential. This review paper summarizes the knowledge available in literature on drilling of CFRP and their outcomes are compared comprehensively in a simple way. It covers key aspects such as drilling mechanism, cutting parameters and tool geometries for conventional drilling. Also, drilling-induced damages and potential solutions for those problems are addressed and covered in this paper

Aluminium hybrid functionally graded metal matrix composites (FGMMCs), meet growing demands for supreme tribo-mechanical performance in automotive and aviation industry. This research experimentally compares the influence of carbide ceramics (B4C, SiC, TiC) as reinforcements, in improving reciprocating tribology performance and mechanical strength of A333 hybrid composites against alloy. Hollow cylindrical samples of A333/6 wt%B4C/4 wt%TiC and A333/6 wt%B4C/4 wt%SiC hybrid FGMMCs were developed using horizontal centrifugal casting. Metallography analysis on both composites revealed increasing ceramic gradient distribution towards outer composite wall. Particle rich zone of A333/B4C/SiC hybrid FGMMC showed maximum micro-hardness (198.9 HV) and tensile strength (267.9 MPa). Elemental mapping confirmed effective distribution of ceramics and detected elemental composition of both composites. Particle rich layer of A333/B4C/SiC hybrid FGMMC exhibited improved wear resistance in comparison with all three layers of A333/B4C/TiC hybrid FGMMC and alloy. Third-body abrasion and tribo-chemical wear were the predominant mechanisms revealed for both composites during worn surface analysis.

This study comparatively investigates the rotational dry sliding wear behaviour of hybrid ceramic reinforced AA6082/3wt.%Boron Nitride (BN)/4wt.%Boron Carbide (B4C) stir cast composite against its alloy by varying weight percentage (2, 4 and 6 wt.%) of Corn Cob Ash. Maximum hardness (70.7 BHN) and impact strength (32 J) was identified at 4 wt.%. The input parameters were applied load (15, 25 and 35 N), sliding distance (750, 1250, and 1750 m) and sliding velocity (1, 2 and 3 m/s), whereas specific wear rate was the response parameter designed based on Taguchi's L27 array. The percentage contribution of each influential input factor towards the performance characteristics of the developed composites were defined using Analysis of Variance. Optimum wear rate was obtained at 15 N load, 750 m sliding distance and 1 m/s sliding velocity combination. Signal to Noise ratio identified applied load as most influential followed by sliding distance and sliding velocity.

In this analysis, a computational study is conducted to examine the two-dimensional flow of an incompressible MHD SWCNT-blood nanofluid, saturated mass and porous medium .In addition to viscous dissipation, thermal radiation is taken into consideration. We developed the mathematical model and useful boundary intensity approximations to diminish the structure of partial differential equations based on the fluid for blood-based SWCNT underflow assumptions. Converted the partial differential equations by applying corresponding transformations to arrive at ODE’s. The above results are solved numerically by the Runge-Kutta 4th order technique. Noticed that there is desirable conformity when interpolated with the numerical one. The effects exhibited the velocity of SWCNT-blood nanofluid enhanced for defined standards of the viscosity parameter. Rise in temperature when various parameters like Prandtl number, Eckert number, and slip parameter are applied on SWCNT-blood. The impact of fluid flow on blood-based SWCNT is discussed graphically, and our results are tabulated along with illustrations. The design concepts, such as the Nusselt quantity and the local skin friction, conform to the analytical approach. Velocity reductions with an increase in CNT’s volume fraction, whereas enhancement in the blood temperature, is noted, which is directed to the rise in the heat mass transfer rates.

The effect of the water pressure, traverse speed, and abrasive feed rate on the circularity, cylindricity, kerf taper, and surface roughness of holes produced by abrasive waterjet machining (AWJM) of a carbon-fibre-reinforced polymer (CFRP) composite was investigated in the current study. It was found that the circularity deviation decreased as the water pressure was increased. Cylindricity was affected by all three parameters, although the abrasive feed rate caused the largest deviations as it increased. The surface roughness was affected by all three, but a clear connection was not able to be concluded. The kerf taper ratio reduced with an increase in water pressure, while it increased with an increase in the abrasive feed rate and an increase in the traverse speed. To obtain optimum results, the water pressure should be increased, the traverse speed should be decreased, and the abrasive feed rate can remain constant but is recommended to be slightly reduced.

This paper discusses on improving the mechanical and tribological characteristics of homogeneous and functionally graded A359 aluminium alloy processed through gravity and centrifugal casting respectively, through T6 heat treatment. Microstructural observation confirmed uniform and gradient structure for homogeneous and functionally graded casts respectively. Maximum micro-hardness values were observed at 10 hours aging time followed by a significant drop due to over aging. After T6 treatment, 38 and 40 % improvement in micro-hardness, 11 and 13.4 % improvement in tensile strength was observed on comparing as-cast homogeneous and functionally graded material respectively. Wear evaluation was performed for all the regions of as-cast and heat treated functionally graded material and homogeneous casts by varying load (15-35 N) and sliding distance (500-1500 m). Maximum wear resistance was observed for heat treated functionally graded material (outer) under the effect of sliding distance. Wear analysis revealed predominant delamination wear mechanism on worn surfaces.

The present work focusses on improving the mechanical and tribological properties of Al-5Si-3Cu alloy and Ni-coated TiC reinforced composite fabricated through liquid metallurgy route, through T6 heat treatment. Good interfacial bonding was developed between the matrix and coated reinforcement on microstructural investigation. There was an improvement in hardness for heat-treated alloy and composite by 34.5% and 14.7% respectively. Tensile strength for heat-treated alloy and composite was enhanced by 25.9% and 30.6% respectively. Pin on disc dry sliding wear test was carried out for Ni-coated TiC heat-treated composite for varying loads (10, 20, 30N), distances (500, 1000, 1500m) and velocities (1, 2, 3m/s) by using Taguchi's L27 Orthogonal Array. It was concluded that load had the highest influence on wear rate (71.88%), whereas the effects of sliding distance (8.23%) and velocity (3.45%) were nominal. Wear analysis revealed that, wear rate increased with an increase in load and sliding velocity and decreased with increasing sliding distance. Defects like delamination, grooving, and protrusions were observed on the worn surface. Thus, this kind of Ni-coated TiC reinforced composites can be used in camshafts, bearings and bushes for better wear resistance.

The functional grade composite Cu-11Ni-4Si/10wt.%TiC along with Cu-11Ni-4Si alloy was stir cast, followed by horizontal-centrifuge cast technique. Cast sample was prepared at a dimension Fout100 x Fin85 x 100 mm. A comparative analysis for non-lubricated slide tribology at inner wall zone (1-5 mm), middle wall zone (5-10 mm) and outer wall zone (10-14 mm) of composites and alloy, was performed utilizing pin-on-disc tribometer. Observed a proportional raise in wear and friction with rise in applied loads and slid distances. For alloy and composite, a slight decline in wear was seen at medium velocity; showing a gradual deduction in friction with rise in slid velocity, while alloy wear showed a linear growth. Rate of increase in wear response with respect to change in distance was less prominent, compared to its response with load. Worn surfaces analysis of composite using Scanning Electron Microscope showed the presence of Mechanically Mixed Layers, which reduced friction at higher slid velocities resulting in lower wear. The phase formations and presence of oxides were confirmed by X-ray diffraction (XRD) and Energy dispersive spectrometers (EDS) results respectively.

Pure copper was coated with Tungsten Carbide-Cobalt (WC12%-Co) using Detonation- Gun technique. A coating thickness of 541 µm was obtained and the hardness of WC-Co coated copper surface was 5.2 times greater than the hardness of uncoated surface. The wear properties of coated copper were investigated using pin-on-disc tribometer, where the WC-Co coated copper exhibited higher wear resistance than uncoated copper. Dry sliding wear properties of WC-Co was analysed using Response Surface Methodology by considering the parameters load (10, 20, 30 N), sliding velocity (0.75, 1.5, 2.25 ms-1) and sliding distance (750, 1250, 1750 m). The results indicated an increase in the wear rate with increasing load and velocity, whereas the increase in the distance showed minimal increase in wear rate. The worn surfaces were analysed using Scanning Electron Microscopy to understand the wear mechanism. The result from the presented experiment may find its application in clutch selector fork of automobile transmission and bearings.

A comparative study was drawn for evaluating mechanical and tribological properties between as-cast, heat treated (HT) Functionally Graded (FG) A359/10 wt% B4C and homogenous A359/6 wt% B4C composites (wt% equivalent to FGM outer zone, determined by chemical dissolution method) processed through horizontal centrifugal and gravity casting techniques respectively. Metallographic analysis confirmed decreasing gradation of reinforcement particles from outer to inner layers for as-cast FG composite, whereas even distribution of reinforcement was observed throughout for homogenous composite. Formation of fine alpha-spheroidized eutectic silicon was observed in HT composite. Comparative analysis carried out for mechanical properties of as-cast to HT composite confirmed an improvement of 37.9 % for outer layer of FG composite and 32.6 % for homogeneous composite in micro-hardness, while an improvement of 24.1 % for outer layer FG composite and 5.6 % for homogeneous composite was observed for tensile strength. Reciprocating wear analysis confirmed superior resistance to wear for outer zone of HT FG composite, with an increasing trend for wear rate and friction co-efficient under the effect of load and sliding distance. A decreasing trend was observed for wear rate and friction co-efficient as weight percentage of reinforcement increased. Worn morphological analysis confirmed predominant delamination wear mechanism for homogenous composites, whereas a combination of abrasive, adhesive and delamination wear was observed for FG composite. Keywords: Functionally graded composite, Homogeneous composite, Heat treatment, Reciprocating wear.

This paper presents the optimization of cutting parameters for MRR, tool wear and surface roughness characteristics in machining of ADC12 alloy. Milling experiments were performed on CNC Milling machine using uncoated carbide inserts. The objective is to minimize the surface roughness, tool wear and maximize the MRR. Process parameters that included speed (1000, 2000, 3000) rpm, feed (0.05, 0.075, 0.1) m/min and Depth of Cut (DOC) of (0.5, 1.0, 1.5) mm were varied for three levels to determine the test cases with the help of Taguchi’s Orthogonal Array (L9), following which, surface roughness, MRR and tool wear was calculated. MRR and tool wear showed similar trends where the responses increase with speed, feed and DOC, whereas the surface roughness tends to increase with feed but lowers on increasing the speed and DOC. Minimum surface roughness and tool wear obtained was 0.25 µm and 0.001 mm respectively, whereas maximum MRR obtained was 0.1144 mm3/min. Speed had major influence on MRR and tool wear whereas, feed had highest impact on surface roughness. ANOVA results also depicted the same rankings. Regression analysis was performed to estimate the surface roughness, MRR and tool wear which was further validated using confirmation tests.

The tribological performance of functionally graded composites (FGCs) under abrasive and reciprocating test conditions are reviewed, from the numerous studies performed over the last three decades. FGCs produced differing wear analysis trends under varying process conditions and parameters. A general framework identifying the process parameters as well as assessing the wear performance through wear modes and mechanisms is presented. The tribo-system material loss is reduced by optimizing the process parameters independently, for specific engineering applications depending on the industrial demands. Moreover, the different challenges faced during wear analysis were discussed and their prospects in various scientific and technological fields are addressed.

Productivity and cost-effectiveness are essential components of any long-term manufacturing system. While quantity and quality are linked to productivity, the economy focuses on energy-efficient processes that produce a high output-to-input ratio. Hard-to-cut materials have always been difficult to machine because of more significant tool wear and power losses. Inconel 625 is a hard material used in aerospace and underwater applications and is milled using biolubricants with nanoparticles. Palm oil is considered a biolubricant, and titanium dioxide (TiO2) and copper oxide (CuO) are selected as nanoparticles. When the combination of biolubricants and nanoparticles is added to the workpiece’s surface, it enhanced some properties while machining. Experiments involving four factors with four levels were carried out using the Taguchi design of experiments (DoE). The feed, depth of cut, speed, and coolant with nanoparticle additives were all factors. The responses were surface roughness, spindle vibration along X, Y, and Z axes, and material removal rate. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to alter the multiresponse optimization problem to a single-response optimization problem. The S/N of TOPSIS closeness coefficients was calculated, and the optimal machining conditions were determined. Surface roughness, material removal rate, and spindle vibration were reduced by 3.10%, 6.14%, 7.54% (Vx), and 6.78% (Vz), respectively, due to the TOPSIS optimization.

This research aims to fabricate Cu-10Sn-5Ni /10wt%TiC functionally graded composite (Øout100 X Øin70 X 100 mm) through horizontal centrifuge cast technique and to study its tribo-mechanical characteristics. Microstructural observation revealed higher percentile of reinforcement particles at inner wall zone compared to middle and outer zones. Vicker’s micro hardness tests revealed proportional increase of hardness along the radial wall towards inner periphery. Inner (7-15 mm) zone had higher tensile strength (291 MPa) compared to outer (1-7 mm) zone (236 MPa). Non-lubricated tribology experiments were performed at inner, middle and outer region of composite using pin-on-disc tribometer under a wide range of loads, sliding distances and sliding velocities. From the wear experiment results, it was observed that inner region had minimal wear due to rich particle presence. Scanning Electron Microscopy on worn specimen at low and high wear parametric conditions exhibited features like delamination, ploughing, micro cutting, particle pull-out, plastic deformation with flaky wear debris and thin film formation.

Fabrication of Aluminum LM13/MoS2/TiO2 hybrid metal matrix composite via stir casting technique was carried out to analyze the wear characteristics at an elevated temperature of 150° C using pin on disc tribometer. The parameters namely load, sliding velocity and sliding distance were varied for five levels as per the run order generated from Response Surface Methodology. From experiments, it was observed that the wear rate decreased with reduced sliding velocity initially due to mechanically mixed layer formation and then increasess. Also the results showed a reduction in wear rate with low loading and sliding distance conditions. Minimum wear rate was observed at a load of (11N), sliding velocity (1m/s) and sliding distance (848m) which was the ideal condition. Results concluded that the load applied was the significant factor over rate of wear leading to the occurrence of deep grooves along with delamination at higher loads. At minimal loads, appearance of shallow grooves in the sliding direction was observed.Major Applications of AMMC include the manufacturing of piston liners in automobiles and bearings, gears for aircraft engines which are often subjected to high friction and temperatures.

Functional grade composites Cu–10Sn–5Ni reinforced with 10 wt%SiC and 10 wt%Al2O3, respectively, and their alloy was developed through horizontal centrifuge cast technique. Sample composites and alloy were cast at cylindrical dimensions of Φout100 × Φin70 × 100 mm. They were later subjected to tribology analysis during non-lubricated sliding. Anti-wear performance variations at inner (0–8 mm) and outer (8–15 mm) wall thicknesses of both composites and alloy were experimented using pin-on-disc tribo-tester. Experimentation with increasingly varied parameters like load and slid distance showed a rising trend of wear and friction. This was observed while comparing between the least (10 N, 500 m) and highest (60 N, 3000 m) varied parameter; for both alloy and composites. Also, a proportional decline in coefficient of friction with increase in slid velocity was exhibited for both composites; whereas alloy showed a linear rise. Worn specimen analysis using scanning electron microscopy on both composites revealed Mechanically Mixed Layer formation at both zones. This caused reduction in friction coefficient at high velocity (6 m/s). Keywords: Centrifuge casting, Functional graded materials, Adhesive wear, Scanning electron microscopy

The objective was to study the wear behaviour of titanium nitride deposited onto 6061 aluminium alloy by DC magnetron sputtering technique. The coating on the aluminium substrate was characterized using optical microscopy, scanning electron microscopy and energy dispersive spectroscopy analysis. The hardness of the uncoated and coated aluminium specimens was tested using Vickers hardness tester and the results revealed that coated specimens had 26 % improvement compared to uncoated samples. The dry sliding wear behaviour of the titanium nitride coated aluminium specimens was investigated using pin on disc tribometer by response surface methodology. Five level central composite design was utilized and experiments were conducted by varying the wear process parameters such as load, velocity and sliding distance within the range 15 to 45 N, 1.5 to 4.5 m/s and 500 to 1500 m respectively. Wear test results revealed that increase in load increases the wear rate and increase in velocity and sliding distance decreases the wear rate. The developed model was validated through the comparison of experimental and model values which yields an error within 3 % confirms that the model was adequate. Scanning electron microscope was utilized to analyze the worn surfaces to study the wear mechanisms.

The aim of the present research is to determine the abrasive wear behavior of functionally graded Al LM21/10wt.% Ni coated SiC composite fabricated by centrifugal casting route. The centrifugal cast hollow cylindrical part has the dimensions of Øout150 mm x Øin135 mm x 160 mm. Ni was coated over SiC reinforcement particles by electroless coating process and the presence of Ni content on reinforcement particles were confirmed by Energy Dispersive Spectroscopy analysis (EDS). Abrasive wear test was conducted as per Taguchi’s L27 orthogonal array design. The parameters selected for wear experiments were: load (29, 34 and 41 N), rotational speed (100, 150 and 200 rpm) and radial distance (1, 6 and 11 mm) from outer periphery. The wear characteristics of the composite were analyzed using signal-to-noise and analysis of variance. Results showed that the radial distance had major impact on the wear rate (40.59 %), followed by the applied load (29.7 %) and rotational speed (14.85 %). The regression equation was developed and validated with confirmatory experiments and the error was found to be less than 10 %. Scanning Electron Microscope (SEM) analysis was done on the worn specimens and observed lesser wear rate at the radial distance of 1 mm.

The aim of this research is to fabricate functionally graded aluminium composite reinforced with 15 wt% alumina using centrifugal casting technique with dimensions of Øout160 x Øin145 x 150 mm and to investigate its threebody abrasive wear behavior. Hardness tests and microstructural examinations were performed at distances of 2, 8 and 14 mm from outer diameter. Based on hardness test results, wear tests were carried out at a distance of 2 mm from outer diameter and a total of 16 experiments were conducted as per Taguchi’s Design of Experiments. The parameters varied were load applied on the specimen (29, 34, 41 and 53 N), sliding speed at the surface of the specimen (75, 100, 125 and 150 rpm) and time of operation (3, 5, 7 and 9 mins) and their influence on the wear rate was analyzed using Analysis of Variance and Signal-to-Noise ratio. The most dominating parameter was found out to be the load applied and subsequently a regression equation was generated. Finally, the worn surfaces were analyzed using Scanning Electron Microscope. The images obtained were used to explain the wear mechanisms and it was found out that increased load caused severe ploughing action on the surface. This indicates that the load applied on the component fabricated with this material is the major factor in determining is life.

The aim of the work is to fabricate functionally graded aluminium (Al-Si6Cu)/ nickel coated SiC metal matrix composite using centrifugal casting route. SiC particles (53-80 µm) were coated with nickel using electroless coating technique to enhance the wettability with aluminium matrix. Several attempts were made to coat nickel on SiC by varying the process temperature (65 °C, 75 °C, and 85 °C) to obtain a uniform coating. Silicon particles coated with nickel were characterised using EDS enabled Field Emission Scanning Electron Microscope and it was found that the maximum nickel coating on SiC occurred at a process temperature of 75°C. This nickel coated SiC particles were used as the reinforcement for the manufacture of functionally graded metal matrix composite and a cast specimen of dimensions 150×90×15 mm was obtained. To ensure the graded properties in the fabricated composites, microstructure (at a distance of 1, 7 and 14 mm) and hardness (at a distance of 1, 3, 7, 10 and 14 mm) from outer periphery taken in the radial direction was analysed using Zeiss Axiovert metallurgical microscope and Vickers micro hardness tester respectively. The microstructure reveals presence of more SiC particles at the outer periphery compared to inner periphery and the hardness test shows that the hardness also decreased from outer periphery (90 HV) to inner periphery (78 HV).Tensile strength of specimen from outer zone (1-7mm) and inner zone (8-14 mm) of casting was also tested and found out a value of 153.3 Mpa and 123.3 Mpa for the outer zone and inner zone respectively. An important observation made was that the outer periphery of casting was particle rich and the inner periphery was particle deficient because of centrifugal force and variation in density between aluminium matrix and reinforcement. Functionally graded Al/SiC metal matrix composite could be extensively used in automotive industry especially in the manufacture of liners and brake drums.

Aluminium alloy reinforced with zirconia (10 wt%) was fabricated using stir casting technique and specimens with diameter 20 mm and 100 mm length were obtained. The adhesive wear test was done on the fabricated specimens using a pin-on-disc tribometer. Taguchi’s method was used for designing the number of experiments and L27 orthogonal array was developed for analysis of wear rate. Optimisation of parameters like applied load (15 N, 25 N, 35 N), sliding distance (500 m, 1250 m, 2000 m) and sliding velocity (1.5 m/s, 2.5 m/s, 3.5 m/s) was done using Signal-to-Noise ratio analysis and Analysis of Variance. “Smaller the better” criteria was considered as objective model to analyse the wear resistance of the composite. Results revealed that applied load (73.83%) has major influence on wear behaviour followed by sliding distance (10.08%) and sliding velocity (8.25%). Scanning Electron Microscope analysis was done on the worn surfaces of the composite specimens and severe delamination was observed at high load condition.

Functionally graded aluminium (Al-Si5Cu3) metal matrix composite reinforced with 10 wt-percent of boron carbide particles having average size of 33 µm was synthesized through horizontal centrifugal casting method. The specimen of length 150 mm and outer diameter of 154 mm with the thickness of 20 mm was produced under the centrifuging speed of 1000 rpm. Composite specimens were prepared as per ASTM standards from the casting and subjected to microstructural evaluation, hardness testing and three body abrasion wear test. The microstructural observation was done on the surfaces at the distance of 1, 2.5, 10 and 15 mm from the outer periphery of the casting and the result shows that larger amount of particles observed at distance of 2.5 mm and very less particles observed at the distance of 15 mm. The hardness test was conducted on the different surfaces in the radial direction from the outer periphery and found decrease in hardness from 2.5 to 15 mm. The abrasion wear test was conducted using dry abrasion tester for various loads of 28, 40 and 52 N at different distances from the outer periphery of the casting and the results revealed that wear rate gradually increases when moving towards the inner periphery and also with the increasing load. Therefore higher wear resistance was observed at the outer periphery and the lower wear resistance was obtained at the inner periphery. This property makes them suitable for using in wear applications such as in cylinder liners.

Aluminium alloy (LM25) reinforced with silicon nitride was fabricated by liquid metallurgy route. The fabricated composite was investigated for dry sliding wear behaviour by conducting experiments using pin-on-disc tribometer. Set of experiments were planned using Taguchi’s technique and data analysis was carried out using L27 orthogonal array. Analysis of Variance (ANOVA) technique was used to determine the significance of parameter with respect to wear rate. Signal-to-Noise ratio was employed to detect the most and least influential parameter as well as their level of influence. ‘Smaller the wear’ characteristic was chosen for the analysis of dry sliding wear. Results implied that, the load has the primary effect on the wear succeeded by the effect of sliding velocity and sliding distance. Scanning Electronic Microscopic studies were carried out on worn surfaces to understand the wear mechanism.Tribological results indicated that LM25 aluminium alloy could be better utilized as a material for piston, rotor and bearings for long life in low speed applications.

LM25 aluminium alloy reinforced with 15 wt% SiO2 metal matrix composite was fabricated by liquid metallurgy technique. Microstructure of the fabricated composite specimen was observed using inverted metallurgical microscope and result showed uniform distribution of reinforcement particles in the matrix. The dry sliding wear behaviour of LM25/SiO2 composite was analyzed by conducting experiments using pin-on-disc tribometer. Taguchi’s method was used for designing the number of experiments and L16 orthogonal array was developed for wear analysis. Optimization of parameters like applied load (10 N, 20 N, 30 N, 40 N), sliding velocity (0.5 m/s, 1 m/s, 1.5 m/s, 2 m/s) and sliding distance (500 m, 1000 m, 1500 m, 2000 m) was done using Signal-to-Noise ratio analysis and Analysis of Variance. ‘smaller-the-better’ characteristic was chosen to analyze the dry sliding wear behaviour. Results found that load (69.17 %) had the highest impact on wear rate followed by sliding velocity (18.04 %) and sliding distance (1.5 %). The regression equation was developed and it was validated with confirmatory experiment. Scanning Electron Microscope analysis was done to observe the mechanism of the worn out composite specimen and found more delamination at the load of 40 N.

Functionally graded aluminium/zirconia metal matrix composite was fabricated using stir casting technique followed by horizontal centrifugal casting process and a hollow cylindrical functionally graded composite (150 x 150 x 16 mm) was obtained with centrifuging speed of 1200 rpm. The microstructural evaluation and hardness test was carried out on the outer and inner surface of the functionally graded composite at a distance of 1 and 13 mm from the outer periphery. In Response Surface Methodology, Central Composite Design was applied for designing the experiments and sliding wear test was conducted as per the design using a pin-on-disc tribometer for varying ranges of load, velocity and sliding distance. The model was constructed and its adequacy was checked with confirmation experiments and Analysis of Variance. The microstructural examination and hardness test revealed that the outer surface of FGM had higher hardness due to the presence of particle rich region and the inner surface had lesser hardness since it was a particle depleted region. The wear results showed that wear rate increased upon increase of load and decreased with increase in both velocity and sliding distance. Scanning Electron Microscopy analysis was done on the worn specimens to observe the wear mechanism. It was noted that wear transitioned from mild to severe on increase of load and the outer surface of FGM was found to have greater wear resistance at all conditions.

The main aim of this study was to determine the adhesive wear characteristics of heat treated LM 25/AlB2 metal matrix composites fabricated using liquid metallurgy route. The composite samples were solutionized at 525 °C and then water quenched. Aging was done at different temperatures (160 °C, 175 °C, 200 °C and 250 °C) for different aging time (4 hrs, 6 hrs, and 8 hrs). Brinell hardness tester was used to evaluate the hardness of all aged samples and maximum hardness (82 HRB) was observed in the sample aged for 6 hours at 250°C . Those heat treated specimens were taken for further experimentation on wear characteristics. Pin-on-disc tribometer was used to analyse the dry sliding wear characteristics and the experiments were conducted based on Taguchi’s L16 orthogonal array by varying the process parameters of load (10 N, 20 N, 30 N and 40 N), sliding distance (400 m, 800 m, 1200 m and 1600 m) and sliding velocity (1 m/s, 2 m/s, 3 m/s and 4 m/s) for four levels. The dependence of wear rate on various parameters was found out using ANOVA and S/N ratio. The experimental result shows that sliding velocity (56.6 %) influences more on wear rate followed by load (23.09 %) and sliding distance (6.02 %). The regression equation was developed and the confirmatory result shows less error. The worn surfaces were analysed using Scanning Electron Microscope and severe delamination at the sliding velocity of 1m/s was found.

Functionally graded LM13 aluminium/10wt% TiS2 composite was fabricated by centrifugal casting method and hollow cylindrical part has the dimension of 150x150x20 mm was obtained. The microstructural evaluation and vicker’s micro-hardness test was carried out on the surfaces at the distance of 1, 6, 12 and 18 mm from the outer surface of functionally graded composites. The microstructural investigation reveals that the TiS2 reinforcement particles concentrated more on the outer periphery and less at the inner periphery of the composite. The hardness of the composite surface increases at the particle rich region of outer periphery and decreases towards inner region. The dry sliding wear experiments were conducted on the composite specimens as per plan of Taguchi’s L16 orthogonal array design. The parameters considered were load, sliding velocity, sliding distance and distance from outer periphery of the composite, varied for four levels. Signal- to- Noise ratio and Analysis of Variance were carried out and the significance test revealed that distance from outer periphery had major impact (43.11 %) followed by sliding distance (31.19 %), load (16.59 %), and sliding velocity (7.33 %). Adequacy of model was predicted through regression equation and the error was found to be less than 8 %. The scanning electron microscope analysis carried out for the worn-out surfaces showed maximum wear resistance of the functionally graded composite at outer periphery.

Aluminium alloy reinforced with boron carbide (10 wt.%) was fabricated using stir casting method followed by centrifugal casting and the cylindrical specimen with dimension 150 x 150 x 15 mm was obtained. The composite specimens were heat treated at various aging temperatures and aging time for property improvement. Solution treatment was done at 525 ℃ for 5 hrs. Taguchi’s method was used for designing the plan of experiments and L27 orthogonal array was formulated for the analysis of data. The wear test was conducted on the outer periphery of centrifugally cast Functionally Graded composites using pin-on-disc tribometer. Optimization of parameters such as applied load (10 N, 20 N, 30 N), agingtemperature (150 ℃, 175 ℃, 200 ℃) and aging time (2 hrs, 6 hrs, 10 hrs) was done using Signal-to-Noise ratio. “Smaller-the-better” criterion was used for analyzing the results. Results ended up with a conclusion that aging time (92.19 %) had major influence on tribological behavior followed by aging temperature (5.36 %) and applied load (1.95 %). Scanning Electron Microscope (SEM) analysis was performed to understand the wear mechanism in heat treated specimens.

Aluminium/alumina/graphite hybrid metal matrix composites manufactured using stir casting technique was subjected to machining studies to predict tool condition during machining. Fresh tool as well as tools with specific amount of wear deliberately created prior to machining experiments was used. Vibration signals were acquired using an accelerometer for each tool condition. These signals were then processed to extract statistical and histogram features to predict the tool condition during machining. Two classifiers namely, Random Forest and Classification and Regression Tree (CART) were used to classify the tool condition. Results showed that histogram features with Random Forest classifier yielded maximum efficiency in predicting the tool condition. This machine learning approach enables the prediction of tool failure in advance, thereby minimizing the unexpected breakdown of tool and machine.

The present paper labels the wear behaviour of the manufactured LM 13 aluminium/B4C metal matrix composites synthesized by means of liquid metallurgy technique. The B4C particles with size 33 µm diversified for the range of 0, 4, 8 and 12 wt-% were incorporated in the composite. The wear behaviour of the composites was studied as per L16 orthogonal array using pin-on-disc tribometer for various sliding conditions by varying the parameters such as load, velocity, sliding distance and wt-% of the reinforcement. Smaller-the-better characteristic was selected as the objective of the developed model and the optimum level of each parameter was detected. The influence of the parameters on the wear rate was known through analysis of variance. Regression model was developed and checked for adequacy using confirmation experiments. Scanning electron microscope analysis was done to study the worn morphologies of composite surface. The experimental results disclose that load was the major influencing parameter on the wear behaviour followed by wt-% of reinforcement, velocity and sliding distance. The worn-out surface interprets that rise in load yields a transition in the wear mechanism. The confirmatory results evident that Taguchi’s design as efficient statistical model by supporting the regression results with less error.

This paper involves the optimisation of the process parameters for the aluminium/alumina/graphite hybrid metal matrix composite to obtain the least wear rate during dry sliding process. The tribological properties of the composite have been studied and discussed. Experiments were carried out using pin-on-disc tribometer by varying the parameters such as load, velocity, distance & the alumina composition of the composite and the wear rate for each input configuration was calculated. Using this empirical data, the regression equation was obtained using Artificial Neural Networks and this function was then optimised using Genetic Algorithm. The least wear rate was obtained for the composite with an alumina composition of 5 wt%.

This paper involves the multi-objective optimization of process parameters of AlSi10Mg/9 wt% alumina/3 wt% graphite in Electrical Discharge Machining for obtaining minimum surface roughness, minimum tool wear rate and maximum material removal rate. The important machining parameters were selected as peak current, flushing pressure and pulse-on time. Experiments were conducted by selecting different operating levels for the three parameters according to Taguchi’s Design of Experiments. The multi-objective optimization was performed using Grey Relation Analysis to determine the optimal solution. The Grey Relation Grade values were then analysed using Analysis of Variance to determine the most contributing input parameter. On analysis it was found that peak current, flushing pressure and pulse-on time had an influence of 61.36%, 17.81% and 8.09% respectively on the optimal solution.

This paper involves the optimization of input process parameters in Electric Discharge Machining of Aluminium hybrid Metal Matrix Composite. Aluminium AlSi10Mg alloy reinforced with 9 %wt. alumina and 3 %wt. graphite particles fabricated through liquid metallurgy route was used for machining. Experiments were conducted in an Electric Discharge Machine and the influence of input process parameters such as Peak current, Pulse-on time and Flushing pressure during machining of aluminium composite was studied. The objective was to obtain a minimum surface roughness with minimum tool wear rate and maximum material removal rate. Multi-objective optimization of the input process parameters was performed by employing Artificial Neural Network and Genetic Algorithm hybrid optimization technique. The results obtained provide a pareto-optimal solution set that offers a set of non-dominated solutions that can be used in a practical situation by a decision maker.