Browsing by Author "Patil, S."

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A study on solubility of bismuth cations in nickel cobalt ferrite nanoparticles and their influence on dielectric and magnetic properties
(Elsevier Ltd, 2023) Patil, S.; Meti, S.; Kanavi, P.S.; Bhajantri, R.F.; Anandalli, M.; Mondal, R.; Karmakar, S.; Muhiuddin, M.; Rahman, M.R.; Kumar, B.C.; Hegde, B.G.
In this work, a low temperature (∼600 °C) solution combustion technique is employed for the synthesis of Ni0.5Co0.5BixFe2-xO4 (NCBFO, where x = 0.0, 0.05, 0.1, 0.15, & 0.2) nanoparticles with crystallite size variation of 17–22 nm. The X-ray diffraction (XRD) technique is used to confirm the formation of cubic spinel phase of Bi3+ doped (for x ≤ 0.05 samples) nickel–cobalt ferrite (NCFO) nanoparticles. The increase in bismuth substitution (x > 0.05) results in the formation of the Bi2O3 along with the NCFO structure, which results in the reduction of binding energy and is confirmed by the XRD and X-ray photoelectron spectroscopy (XPS) techniques. From the Raman spectra, the change in the intensities of the peaks is observed due to the variation of Bi3+ in NCFO matrix. Due to increasing cation concentration and electronegativity, the FTIR absorption band shifts toward the lower wave numbers. Dielectric measurements were carried out to examine the charge transport behavior and electric conduction mechanism. The FESEM images shows the non-magnetic bismuth atoms are diffused into the NCFO nanoparticles. From the vibrating sample magnetometer (VSM) analysis, it is observed that saturation magnetization, remanent magnetization, coercivity and squareness ratio are found to be maximum for x = 0.15 NCBFO sample. The high coercivity (Hc = 916.8 Oe) for the x = 0.15 sample indicates the hard ferromagnetic behaviour of the samples. © 2023 Elsevier B.V.
Analysis of the Effect of Friction Stir Welding Parameters on Characteristics of AA6061 Composites using Response Surface Methodology
(Springer, 2021) Patil, S.; Dupadu, D.; Narendranath, N.
Response surface methodology (RSM) is used for mathematical modeling of friction stir welding parameters for joining AA6061 composite material. Characteristics of joints were examined through response characteristics such as ultimate tensile strength (UTS) and microhardness (HV) using RSM. Microstructure examination was carried out using optical microscopy, scanning electron microscopy and electron backscattered diffraction, and results exhibit variation in the grain size diameter. Specifically, lower nugget exhibits fine grains with maximum hardness compared to middle nugget and upper nugget. Analysis of variance (ANOVA) results indicate good match between actual values and predicted values with R2 of 0.91 and 0.96, respectively, for UTS and HV, and better joint efficiency of 90% is obtained. © 2021, The Indian Institute of Metals - IIM.
Applications of geospatial analysis and analytical hierarchy process to identify the groundwater recharge potential zones and suitable recharge structures in the Ajani-Jhiri watershed of north Maharashtra, India
(Elsevier B.V., 2022) Sahu, U.; Wagh, V.; Mukate, S.; Kadam, A.; Patil, S.
The present study undertakes the integration of hydrogeological, geospatial and multi-criteria decision analysis (MCDA) techniques to identify groundwater recharge potential zones and suitable recharge structures in parts of the Ajani-Jhiri watershed of the Tapi river basin, north Maharashtra, India. Hydrogeological thematic layers include drainage density, lineament density, geology, geomorphology, land use/landcover, soil and slope, which are the demarcating factors in identification of potential recharge sites of the watershed. An analytical hierarchy process model based on MCDA methodologies was adapted to determine the overall weightage distribution for individual layers for weighted overlay to be executed in GIS environment. Groundwater recharges potential zones are divided into high, moderate, and low classes. Results showed that only 272.72 km2 (38.02%) area has high recharge potential, while 316.94 km2 (44.07%) has moderate groundwater recharge potential. The low groundwater potential recharge zone (129.35 km2; 17.98%) is located in the southern part of the watershed, which is mountainous terrain. Locations of new recharge structures, including six stream bunds, five check dams and two percolation tanks are recommended to meet the regional domestic and agricultural needs. The water bodies in the region are partially silted with loose materials, hence three desiltation tanks proposed. © 2022 Elsevier B.V.
Characterization and Evaluation of Joint Properties of FSWed AA6061/SiC/FA Hybrid AMCs Using Different Tool Pin Profiles
(Springer, 2020) Patil, S.; Narendranath, S.; Dupadu, D.
This work reports the characterization of AA6061/SiC/FA hybrid composites joined using friction stir welding (FSW). FSW was conducted by employing various tool pin profiles such as straight cylindrical (SC), tapered conical, straight square (SS) and cylindrical threaded. Microstructure and mechanical characteristics of joints were investigated using these tool pin profiles. Microstructure study of the weld joints was carried out through scanning electron microscopy and electron backscattered diffraction (EBSD) analysis. The results show equiaxed distribution of grains in the nugget zone. EBSD analysis indicates that the average grain size reduces to 3 µm after FSW with the presence of high-angle grain boundaries. Higher joint efficiency (85%) is obtained for joints obtained using SS tool pin compared to their counterparts, and SC tool yields minimum joint efficiency (77%). Overall 8% enhancement of the joint efficiency is achieved using SS tool pin profile. © 2020, The Indian Institute of Metals - IIM.
Effect of FSW on microstructure and hardness of AA6061/SiC/fly ash MMCs
(Elsevier Ltd, 2018) Patil, S.; Narendranath, S.; Dupadu, D.
In this study 6 mm thick plates of aluminum matrix composites (AMCs) composed of AA6061/SiC (10 Wt. %) /fly ash (7.5 Wt. %) were butt welded using friction stir welding (FSW. Microstructural characterization of weld joints was conducted by using optical microscopy (OM) and scanning electron microscopy (SEM). The microstructure of the weld revealed the presence of four different zones like nugget zone (NZ), thermo mechanically affected zone (TMAZ), heat affected zone (HAZ) and base metal (BM). Nugget zone reveals homogenous distribution of fly ash and SiC particles. Rotating effect of FSW tool results in breaking of some array of grains present in the parent AMCs. Needle like phases present in the parent AMCs eliminated successfully by the incorporation of fly ash particles. Higher hardness is observed in the nugget zone compared to other zones. Â© 2018 Elsevier Ltd. All rights reserved.
Effect of traverse speed on joint characteristics of FSWed HAMCs
(Elsevier Ltd, 2020) Patil, S.; Narendranath, S.; Dupadu, D.
The present work describes the evolution of microstructure and enhancement of mechanical properties of friction stir welded AA6061/SiC/FA Hybrid AMCs (HAMCs). Various joints were produced using different traverse speed from 30 mm/min to 80 mm/min. Microstructural analysis was carried out using Optical microscopy and scanning electron microscopy. Mechanical characteristics such as ultimate tensile strength (UTS) and microhardness (Hv) were studied. Sound quality joints were obtained by FSW without any defects. Results showed that the microstructure zones are divided in to nugget zone, thermomechanically affected zone, heat affected zone and base material zone. Uniform and fine grain formation took place at traverse speed of 60 mm/min indicating sufficient amount of heat input at this speed. Accordingly maximum joint efficiency of 90% is obtained at this traverse speed. Â© 2020 Elsevier Ltd. All rights reserved.
Efficient Traffic Signboard Recognition System Using Convolutional Networks
(Springer, 2020) Mothukuri, S.K.P.; Tejas, R.; Patil, S.; Darshan, V.; Koolagudi, S.G.
In this paper, a smart automatic traffic sign recognition system is proposed. This signboard recognition system plays a vital role in the automated driving system of transport vehicles. The model is built based on convolutional neural network. The German Traffic Sign Detection Benchmark (GTSDB), a standard open-source segmented image dataset with forty-three different signboard classes is considered for experimentation. Implementation of the system is highly focused on processing speed and classification accuracy. These aspects are concentrated, such that the built model is suitable for real-time automated driving systems. Similar experiments are carried in comparison with the pre-trained convolution models. The performance of the proposed model is better in the aspects of fast responsive time. Â© Springer Nature Singapore Pte Ltd. 2020.
High Temperature Corrosion Behavior of High Velocity Oxy Fuel Sprayed NiCrMoFeCoAl-30%SiO2 and NiCrMoFeCoAl-30%Cr2O3 Composite Coatings on ASTM SA213-T22 Steel in a Coal-fired Boiler Environment
(Materials and Energy Research Center, 2022) Patil, V.G.; Somasundaram, B.; Kandaiah, S.; Ramesh, M.R.; Patil, S.
High-velocity oxy fuel (HVOF) sprayed coatings can improve the corrosion resistance of bare ASTM SA213-T22 boiler steel. In this report, we have investigated the NiCrMoFeCoAl-30%SiO2 and NiCrMoFeCoAl-30%Cr2O3 composite coatings were deposited on bare ASTM SA213-T22 boiler steel for corrosion protection. High-temperature corrosion studies were conducted in a molten salt (Na2SO4-60%V2O5) environment at 700ºC under thermo-cyclic conditions. The as-sprayed composite coatings are characterized for microstructure and mechanical properties. The thermo-gravimetric method was utilized to understand the kinetics of corrosion. Characterization of the corrosion products was examined by using scanning electron microscope (SEM)/ Energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD) techniques. The obtained results suggest both the composite coatings are favorable to corrosion resistance over the bare ASTM SA213-T22 boiler steel. The NiCrMoFeCoAl-30%Cr2O3 composite coating was concluded to present a superior corrosion resistance in the high-temperature corrosion environment because of the uniform distribution of the composite coating matrix and the development of protective protection Cr2O3 in the scale. The molten salt heat-treated chromium oxide containing coating shows good corrosion stability than the silica composite. This could be attributed to the high temperature assisted formation metal chromates, chromites and oxide layers. © 2022 Materials and Energy Research Center. All rights reserved.
Influence of news on individual confidence bias in stock markets
(2016) Mukund, Y.R.; Naresh, V.; Patil, S.; Chandrasekaran, K.; Vijaya, Kumar, V.; Gnanamurthy, R.K.
The Phenomenon of stock markets is a complex one and is something which, has attracted researchers and statisticians for a long time. Complex statistics have long dominated this field where the prediction models are usually stochastic. The advent of machine learning gave us a new way of looking at the problem. Much work has been done in analyzing the stock market to predict the stock index of a particular or-ganization. However, most of the work done is based on the previous stock data and other statistical parameters. Our work, uses data such as the online news articles about a particular company and aims to help a trader conclude the market sentiment towards that company through sentiment analysis. The online raw data is obtained through crawling and is indexed, weighted and subject to sentiment analysis to output the final sentiment of the market. It is found that the Naive-Bayesian Classifier is the more suitable op-tion among the Decision Tree and Random Forests for the task of sentiment analysis. The Final Sentiment Factor ar-rived at, is found to reect the real time market sentiment quite accurately. It is also shown that the sentiment factor can be used as an input to a more complex analysis model. This new model, performs better than the existing models.
Influence of news on individual confidence bias in stock markets
(Association for Computing Machinery acmhelp@acm.org, 2016) Mukund, Y.R.; Naresh, V.; Patil, S.; Chandrasekaran, K.; Vijaya, V.; Gnanamurthy, R.K.
The Phenomenon of stock markets is a complex one and is something which, has attracted researchers and statisticians for a long time. Complex statistics have long dominated this field where the prediction models are usually stochastic. The advent of machine learning gave us a new way of looking at the problem. Much work has been done in analyzing the stock market to predict the stock index of a particular or-ganization. However, most of the work done is based on the previous stock data and other statistical parameters. Our work, uses data such as the online news articles about a particular company and aims to help a trader conclude the market sentiment towards that company through sentiment analysis. The online raw data is obtained through crawling and is indexed, weighted and subject to sentiment analysis to output the final sentiment of the market. It is found that the Naive-Bayesian Classifier is the more suitable op-tion among the Decision Tree and Random Forests for the task of sentiment analysis. The Final Sentiment Factor ar-rived at, is found to reect the real time market sentiment quite accurately. It is also shown that the sentiment factor can be used as an input to a more complex analysis model. This new model, performs better than the existing models.
Investigation of structural, thermal, magnetic, and dielectric properties of Yb+3 doped nickel cobalt ferrite nanomaterial for electro-magnetic applications
(Springer, 2024) Patil, S.; Meti, S.; Anandalli, M.; Badiger, H.; Bhajantri, R.F.; Pratheek, L.; Muhiuddin, M.; Rahman, M.R.; Hegde, B.G.
Herein, we report the synthesis of ytterbium (Yb) (with concentration x = 0.01, 0.015, 0.02, 0.025 and 0.03) doped in to nickel cobalt ferrite (NCYFO: YbxNi0.5Co0.5Fe2-xO4) nanoparticles at temperature 500 °C with phase pure spinel using solution combustion technique. The phase purity and effect of doping on NCYFO complex oxide on structural, thermal, magnetic and dielectric properties have been determined by various characterization techniques. The FTIR data reveal that strong metal oxide linkages can be observed in the tetrahedral and octahedral sites at wavenumbers 460 to 410 cm−1 and 595 to 540 cm−1. The X-ray diffraction (XRD) studies confirmed the spinel structure. The crystallite sizes and lattice parameters were estimated to be in the range of 31 to 22 nm and 8.32 to 8.35 Å, respectively. The X-ray photoelectron spectroscopy (XPS) study confirmed that the increase in Yb concentration results in accumulation of Yb in the grain boundaries of NCYFO in the form of Yb2O3. The thermal stability of nanoparticles were investigated using TGA/DSC method. Transmission Electron microscopy (TEM) studies and Field emission scanning electron microscopy (FESEM) used to study the particle size distribution and elemental composition within the nanomaterial. In addition, the dielectric properties, such as, dielectric constant and dielectric loss were investigated for all the NCYFO nanomaterial. The saturation magnetization of the NCYFO is determined using vibrating sample magnetometer (VSM) analysis and is maximum for x = 0.03 (Ms = 97.56 emu/g) sample. The high magnetic behaviour and better dielectric properties of the NCYFO nanomaterials are suitable for electro-magnetic applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
LCSNet: Lightweight Caries Segmentation Network for the segmentation of dental caries using smartphone photographs
(Elsevier B.V., 2025) Radha, R.C.; Raghavendra, B.S.; Hota, R.K.; Vijayalakshmi, K.R.; Patil, S.; Narasimhadhan, A.V.
Dental caries is one of the major dental issues that is common among many individuals. It leads to tooth loss and affects the tooth root, creating a need to automatically detect dental caries to reduce treatment costs and prevent its consequences. The Lightweight Caries Segmentation Network (LCSNet) proposed in this study detects the location of dental caries by applying pixel-wise segmentation to dental photographs taken with various Android phones. LCSNet utilizes a Dual Multiscale Residual (DMR) block in both the encoder and decoder, adapts transfer learning through a pre-trained InceptionV3 model at the bottleneck layer, and incorporates a Squeeze and Excitation block in the skip connection, effectively extracting spatial information even from images where 95 % of the background and only 5 % represent the area of interest. A new dataset was developed by gathering oral photographs of dental caries from two hospitals, with advanced augmentation techniques applied. The LCSNet architecture demonstrated an accuracy of 97.36 %, precision of 73.1 %, recall of 70.2 %, an F1-Score of 71.14 %, and an Intersection-over-Union (IoU) of 56.8 %. Expert dentists confirmed that the LCSNet model proposed in this in vivo study accurately segments the position and texture of dental caries. Both qualitative and quantitative performance analyses, along with comparative analyses of efficiency and computational requirements, were conducted with other deep learning models. The proposed model outperforms existing deep learning models and shows significant potential for integration into a smartphone application-based oral disease detection system, potentially replacing some conventional clinically adapted methods. © 2025 The Authors.
Micro-Architectural support for High Availability of NoC-based MP-SoC
(Institute of Electrical and Electronics Engineers Inc., 2019) Singh, R.; Ranga, S.V.; Patil, S.; Krishna, M.; Mehta, M.; Anoop, M.N.; Nandy, S.K.; Haldar, C.; Narayan, R.; Neumann, F.; Baufreton, P.
In this paper, we focus on increasing the availability of Multi-Processor System on Chip (MP-SoC) for executing user applications, even when some components of the system are faulty. A Network-on-Chip (NoC) provides high bandwidth communication substrate for the multitude of components/modules in such MP-SoCs. Health of such MP-SoC, and hence its availability, is largely dependent on the health of the NoC. We consider an NoC comprising a bidirectional toroidal mesh interconnection of routers. We use a distributed built-in-self-test to identify faulty communication links. We use information so obtained to determine healthy subsystems that can be made available for executing user applications. This feature is key for enhancing availability of MP-SoCs. We realize this feature as a micro-architectural enhancement in MP-SoC that incurs an insignificant hardware overhead of less than 2%. Latency incurred for analyzing availability of MP-SoC is also insignificant. We functionally validate our proposal by emulating the system on a FPGA device and demonstrate increase in availability of the MP-SoC. Â© 2019 IEEE.
Microstructure, Hardness and Tensile Properties of Friction Stir Welded Aluminum Matrix Composite Reinforced with SiC and Fly Ash
(Springer editorial@springerplus.com, 2019) Patil, S.; Narendranath, S.; Dupadu, D.
In the present work, aluminum alloy 6061/SiC/fly ash aluminum matrix composites were welded successfully using friction stir welding process. Microstructure of weld joints was examined using optical microscope and scanning electron microscope. Mechanical properties namely, microhardness and ultimate tensile strength of the joints were studied. The results were correlated to microstructural changes caused by friction stir welding process. Microstructure in the stirred zone exhibits the uniform distribution of SiC and fly ash particles. Especially fine grains were formed on the advancing side than on the retreating side, due to the different variation between tool direction and welding direction. Higher hardness value is observed on the advancing side (132 Hv) than on the retreating side (124 Hv). Transverse tensile test of weld sample exhibits higher joint efficiency of 85.06% with respect to ultimate tensile strength. Fracture study reveals ductile mode of failure. Weld joints got fractured in heat affected zone on the retreating side, which indicates the weakest part of the weld joint. Based on thermodynamic analysis, the optimum heat input was found to be 756 J mm?1, resulting in higher strength of weld joints due to uniform distribution of reinforcement particles in the nugget zone. © 2018, Springer Nature B.V.
Multi head attention based deep learning framework for waxberry fruit object segmentation from high resolution remote sensing images
(Nature Research, 2025) Vaghela, R.; Sravya, N.; Lal, S.; Sarda, J.; Thakkar, A.; Patil, S.
In some Asian countries, waxberries are special fruit that demand substantial labour for harvesting each season. To ease this burden, automated fruit-picking equipment has seen extensive development over the past decade. However, accurately segmenting waxberries in orchards remains challenging due to complex environments with overlapping fruits, foliage occlusions, and variable lighting conditions. Most existing segmentation methods are optimized for controlled environments with steady lighting and unobstructed views of the fruit, which limits their effectiveness in real-world scenarios. This paper introduces a fully convolutional neural network namely Multi-Attention Waxberry Network (MAWNet) which effectively addresses challenges such as occlusions, overlapping fruits and variable lighting conditions. The MAWNet is a UNet based architecture and it consist of enhanced residual block, transformer block, Atrous Spatial Pyramid Pooling (ASPP) block and introduced Multiple Dilation Convolutional (MDC) Block. The experimental results validate that the proposed MAWNet model surpasses several State-of-the-Art (SOTA) architectures, in terms of performance with achieving a remarkable accuracy of 99.63%, an Intersection over Union (IoU) of 96.77%, and a Dice coefficient of 98.34%. © The Author(s) 2025.
Praseodymium doped ceria as electrolyte material for IT-SOFC applications
(Elsevier Ltd, 2018) Shajahan, I.; Ahn, J.; Nair, P.; Medisetti, S.; Patil, S.; Niveditha, V.; Uday Bhaskar Babu, G.; Prasad Dasari, H.P.; Lee, J.-H.
Praseodymium-doped ceria (PDC, Ce0.9Pr0.1O2) electrolyte material for intermediate temperature solid oxide fuel cells (IT-SOFCs) has been successfully synthesised by EDTA-citrate method. From X-Ray diffraction (XRD), fluorite structure along with a crystallite size of 5.4 nm is obtained for PDC nanopowder calcined at 350 °C/24 h. Raman spectroscopy confirmed the structure, presence of oxygen vacancies with the manifestation of the main peak at 457 cm?1 and with a secondary peak at 550 cm?1. From Transmission Electron Microscopy (TEM) analysis, the average particle size is around 7–10 nm and selected area electron diffraction (SAED) patterns further confirmed the fluorite structure of PDC nanopowder. The PDC nanopowder displayed a BET surface area of 65 m2/g with a primary particle size of ?13 nm (calculated from BET surface area). Dilatometer studies revealed a multi-step shrinkage behaviour with the multiple peaks at 522, 1171 and 1461 °C which may be originated due to the presence of multiple size hard agglomerates. The PDC electrolyte pellet sintered at 1500 °C displayed an ionic conductivity of 1.213E-03 S cm?1 along with an activation energy of 1.28eV. Instead of a single fluorite structure, XRD of sintered PDC pellet showed multiple structures (Fluorite structure (CeO2) and cubic structure (PrO2). © 2018 Elsevier B.V.
Process parameter optimization for FSW of AA6061/SiC/fly ash AMCs using Taguchi technique
(ICE Publishing subscriptions@icepublishing.com, 2018) Patil, S.; Narendranath, S.; Dupadu, D.
In this research work, aluminum matrix composite (AMC) plates were welded using friction stir welding (FSW). AMCs contain AA6061 as a base metal with silicon carbide (SiC) and fly ash particles as reinforcements. The FSW process parameters considered in this work were tool rotational speed (revolutions/minute), tool traverse speed (millimeters/minute) and tool tilt angle (degrees). The Taguchi L9 orthogonal array was considered for optimizing the process parameters. Tensile strength and hardness were the two output responses obtained by analyzing joint efficiency and signal/noise ratio. An analysis of variance (Anova) study was conducted to identify the percentage contribution of each process parameter to the output responses. The Anova study concluded that among the three process parameters, tool rotational speed was the most dominant parameter in deciding the tensile strength and hardness of the FSW joints, followed by traverse speed and tool tilt angle. At the end, the results were validated by conducting additional experiments. © 2018 ICE Publishing: All rights reserved.
Saltwater corrosion behaviour of equal channel angular pressed AZ80/91 Mg alloys
(Elsevier Ltd, 2021) Hebbale, A.M.; Naik, G.M.; Badiger, R.I.; Bellubbi, S.; Patil, S.; Narendranath, S.
In this study, AZ80/91 Mg alloys were used to comprehend the electrochemical corrosion behaviour of coarse-grained and fine-grained Mg alloys in different concentration of NaCl solution as well as in the marine environment. The inadequate studies of the corrosion response of ECAPed AZ80 and AZ91 Mg alloy in a different environment were noticed. Accordingly, the current research presents and compares the corrosion behaviour of AZ80/91 Mg alloys in 2.5 wt% NaCl, 3.5 wt% NaCl solution and Natural Sea Water. Influence of corrosion media on coarse and fine-grained AZ80/91 Mg alloys was discussed in the results and discussion section. Corrosion attack of AZ80/91 Mg alloys under the above environment, increased with increase in chloride ion concentration and decreased with the ECAP passes. Â© 2021 Elsevier Ltd. All rights reserved.
Studies on microstructure and mechanical characteristics of as cast AA6061/SiC/fly ash hybrid AMCs produced by stir casting
(Elsevier Ltd, 2020) Patil, S.; Narendranath, S.; Dupadu, D.
Fly ash has been receiving the extensive concentration as a strong reinforcing element for Aluminum Matrix Composites (AMCs) to strengthen the properties and cut the price of manufacturing. AA6061 reinforced with various weight percentages of fly ash particulates and a constant weight percentage of SiC were prepared by stir casting technique as it is one of the simplest and cost-effective method for producing AMCs. Wettability of SiC and Fly ash particles with the aluminum was enhanced by fly ash itself. The microstructure, hardness and tensile properties of manufactured AMCs were analyzed. Optical Microscopy (OM) and Scanning Electron Microscopy (SEM) discovered a harmonized dispersion of SiC and fly ash particles with superior bonding with the matrix material. The inclusion of fly ash particles in to aluminum matrix enhanced the microhardness and Ultimate Tensile Strength (UTS) of the AMCs. Â© 2019 Elsevier Ltd. All rights reserved.
Study on microstructure and tensile properties of fly ash AMCs welded by FSW
(American Institute of Physics Inc. subs@aip.org, 2018) Patil, S.; Narendranath, S.; Dupadu, D.
Aluminum matrix composite (AMCs) constitute a new class of light weight and high strength materials which have widespread applications in almost all engineering sectors. But the cost of AMCs is the only barrier to increase their applications still. Hence there is a huge demand for the composites containing low cost reinforcement with less weight, keeping this in mind, in the present work, Friction stir welding (FSW) of AA6061/SiC/fly ash was carried out successfully. Microstructural study on the welded specimens was performed using optical microscopy (OM) and scanning electron microscopy (SEM). Results indicate that fly ash particles were uniformly distributed in the weld nugget area because of the stirring action of the FSW tool also promoted the grain refinement of the matrix material with complete elimination of clusters present in matrix material which resulting in sound welds without any defects for AA6061/SiC/fly ash composites. 82% of joint efficiency is obtained for selected AMCs. Transverse tensile test results showed that all welds fractured in HAZ. Â© 2018 Author(s).