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Author: search.filters.author.Shettigar, A.K.Subject: search.filters.subject.Friction stir welding

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Now showing 1 - 9 of 9
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    Multi-objective Optimization of FSW Process Variables of Aluminium Matrix Composites Using Taguchi-Based Grey Relational Analysis
    (Springer Nature, 2019) Prabhu B, S.R.B.; Shettigar, A.K.; Herbert, M.A.; Rao, S.S.
    Successful joining of aluminium alloys using friction stir welding (FSW) opens a new window research in extending this technique to join aluminium matrix composites (AMCs). Current research is focused on optimization of process variables for multiple responses simultaneously. Experiments were performed using tool pin profile, rotational speed (RS) and welding speed (WS) as ideal process variables for multi-objective optimization in FSW of AMCs. Tensile strength, macro-hardness and elongation are considered as multi-response behaviour. Grey relational grade for the chosen multiple responses are obtained using grey analysis. Analysis of variance was utilized to understand the influence of process variables on the grey relational grade. Analysis reveals that RS and WS were the most influencing process variables on the output responses. Confirmation experiments were performed at optimized process variables to validate the present study. Predicted values were in good agreement with the experimental results. © 2019, Springer Nature Singapore Pte Ltd.
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    Influence of welding process parameters on microstructure and mechanical properties of friction stir welded aluminium matrix composite
    (Trans Tech Publications Ltd ttp@transtec.ch, 2017) Prabhu B, S.; Shettigar, A.K.; Karthik, K.; Rao, S.S.; Herbert, M.
    In this study, the effect of process parameters on microstructure and mechanical properties of friction stir welded aluminium matrix composites(AMC) have been explored. The results indicated that the recrystallized grain size at the bottom of the weld region is smaller than that at the top region due to difference in the heat transfer at the weld region. The joint strength of AMCs depends on proper selection of process parameters like tool rotational speed and welding speed. If process parameter values are beyond the optimal value, the joint strength decreases due to formation of defects. Maximum tensile strength is obtained for rotational speed of 1000 rpm and welding speed of 80mm/min. © 2017 Trans Tech Publications, Switzerland.
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    Application of neural network for the prediction of tensile properties of friction stir welded composites
    (Trans Tech Publications Ltd ttp@transtec.ch, 2017) Shettigar, A.K.; Prabhu B, S.; Malghan, R.; Rao, S.S.; Herbert, M.
    In this paper, an attempt has been made to apply the neural network (NN) techniques to predict the mechanical properties of friction stir welded composite materials. Nowadays, friction stri welding of composites are predominatally used in aerospace, automobile and shipbuilding applications. The welding process parameters like rotational speed, welding speed, tool pin profile and type of material play a foremost role in determining the weld strength of the base material. An error back propagation algorithm based model is developed to map the input and output relation of friction stir welded composite material. The proposed model is able to predict the joint strength with minimum error. © 2017 Trans Tech Publications, Switzerland.
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    Microstructural characterization and hardness evaluation of friction stir welded composite AA6061-4.5Cu-5SiC (Wt.%)
    (Defense Scientific Information and Documentation Centre, 2013) Shettigar, A.K.; Salian, G.; Herbert, M.A.; Rao, S.
    Recent developments in advanced materials research have led to the emergence of new materials having features like low density, high strength to weight ratio, excellent mechanical properties, heat and corrosion resistance. In friction stir welding (FSW), a non-consumable rotating welding tool is used to generate the frictional heat and plastic deformation of the material in the welding zone, which is in the solid state. The advantages of FSW as compared to the fusion welding are high joint strength, less defect weld, uniform distribution of grain structure in the weld zone and low power consumption. AA6061 with 4.5 % weight of copper and 5 % weight of SiC composite material has been prepared to conduct experiment and carry out characterization, evaluation of the mechanical properties. Micro-structural characterization of the weld zone is carried out by scanning electron microscope (SEM). Evaluation of hardness was also carried out across the weld zone. A successful method for FSW of AA6061-4.5(wt.%) Cu-5(wt.%) SiC has been developed. © 2013, DESIDOC.
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    Microstructure evolution and mechanical properties of friction stir welded AA6061/rutile composite
    (Institute of Physics Publishing helen.craven@iop.org, 2019) Prabhu B, S.R.; Shettigar, A.K.; Herbert, M.A.; Rao, S.S.
    Present study explores the Friction stir welding (FSW) of rutile reinforced AA6061matrix composite using various combination of tool traverse speeds (60, 75 and 90 mm min-1), rotational speeds (750, 1000 and 1250 rpm) and tool pin profiles (Threaded cylindrical and Square profiled pin). FSW process variables have significant impact in controlling the mechanical properties of the joint by limiting the welding defects. It has been inferred from the study that tool rotational speed and tool traverse speed majorly affects the microstructure, joint quality, hardness and joint strength. The weld area showed the presence of four distinct regions usually found in FSW of aluminium matrix composites. The weld region exhibited fine equiaxed grains and uniformly distributed tiny reinforced rutile particles. Tool having square profiled pin shows improved joint properties in comparison with tool having threaded cylindrical pin. © 2019 IOP Publishing Ltd.
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    Development of machine learning regression models for the prediction of tensile strength of friction stir processed AA8090/SiC surface composites
    (Institute of Physics, 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.; Vasudeva, T.V.
    Friction Stir Processing is a state-of-the-art technology for microstructure refinement, material property enhancement, and fabrication of surface composites. Machine learning approaches have garnered significant interest as prospective models for modeling various production systems. The present work aims to develop four machine learning models, namely linear regression, support vector regression, artificial neural network and extreme gradient boosting to predict the influence of FSP parameters such as tool rotational speed, tool traverse speed and groove width on ultimate tensile strength of friction stir processed AA8090/SiC surface composites. These models were developed through Python programming and the original dataset was divided into 80% for the training phase and 20% for the testing phase. The performance of the models was evaluated by root mean squared error, mean absolute error and R2. Based on the results and graphical visualization, it was observed that the XGBoost model outperformed other models with high accuracy in predicting UTS of AA8090/SiC surface composites. © 2024 The Author(s). Published by IOP Publishing Ltd.
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    Optimization of process parameters for friction stir processing (FSP) of AA8090/boron carbide surface composites
    (Springer Science and Business Media Deutschland GmbH, 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.
    Friction Stir Processing (FSP) is an innovative and promising technique for microstructure refinement, material property enhancement, and surface composite production. The current study describes the fabrication of AA8090/boron carbide surface composites (SCs) by FSP. Experimental studies were conducted by varying the FSP parameters, specifically the rotational speed (800–1400 rpm), traverse speed (25–75 mm/min), and groove width (1–1.8 mm). Ultimate Tensile Strength (UTS), Surface Roughness (SR), and Percentage Elongation (El) were used as response measures. Experiments were planned based on the central composite design (CCD) of Response Surface Methodology (RSM) and a mathematical relationship between the input parameters and UTS, SR and El, and were obtained by RSM. The model adequacy was tested using analysis of variance (ANOVA). The models enabled the examination of individual and interaction effects of input parameters on the UTS, SR, and El of the produced SCs. AA8090/boron carbide SC strength was optimal of 366 MPa at 800 rpm, 75 mm/min, and 1.8 mm and optimal 21.13% elongation at 1400 rpm, 25 mm/min, and 1 mm. A smoother surface with 0.82-μm roughness was optimal at 1400 rpm, 25 mm/min, and 1.2 mm. The present study uses the FSP method to synthesize near-net-shaped SCs without further machining by systematically selecting process parameters. The study shows that the increase in rotational speed during AA8090/boron carbide SC fabrication produces composites with a good surface finish, lower UTS, and good ductility. However, the increase in the other two parameters, namely, traverse speed and groove width, produces low ductile composites with rougher surfaces and higher strengths. Graphical abstract: (Figure presented.) © International Institute of Welding 2024.
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    Exploring welding parameter effects on friction stir weld joints in aluminum 8006 alloy using response surface methodology
    (MIM RESEARCH GROUP, 2025) Chandrakumar, C.; Sogalad, I.; Shettigar, A.K.; Korgal, A.; Nagaral, M.
    This study aims to develop mathematical models that can predict the characteristics related to mechanics, such as microhardness and impact resistance, of Aluminum that has been friction stir-welded 8006 alloy joints with 95% confidence. The four process parameters tool tilt angle, welding speed, tool pin shape, and rotating speed were systematically varied across three levels. Following a response surface and central composite design approach that is face-centered, the influence of different factors on the mechanical properties of aluminum 8006 alloy joints was assessed. The highest impact toughness of 58 joules was observed in joints specially prepared by a cylindrical threaded pin profile tool with a 1° tilt angle operating at 800 RPM and a feed rate of 20 mm/min and test was conducted at room temperature. Additionally, it was investigated how process factors affected impact toughness by ANOVA and the results revealed that the tool pin geometry is identified as the most significant process variable on impact toughness, contributing 52.52%, thereafter the tool tilt angles (15.53%), rotating speed (8.80%), and welding speeds (5.84%). The findings showed that, for impact toughness, the tool tilt angle and pin shape were more important than welding speed and tool rotation speed, but the tool pin profile and the welding speed showed governance over rotational speed and angle of tilt in case of hardness. The joints achieved a maximum hardness of 166 VHN at stir zone of the welded specimen made from a threadless taper pin tool for the speed of 1200 rpm, the tool was tilted at 2 degrees while welding at a speed of 40 mm/min. Finally, the effects of process parameters on the microstructure of friction stir welded Aluminum 8006 alloys were addressed and discussed. © 2025 MIM Research Group. All rights reserved.
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    Investigation of the effect of process parameters on the mechanical properties of friction stir additive manufactured (FSAM) AA8090 alloy
    (Elsevier B.V., 2025) D A P, P.; Shettigar, A.K.; Herbert, M.A.; Korgal, A.; Adiga, K.
    Friction Stir Additive Manufacturing (FSAM), an emerging technique, falls under the category of sheet lamination additive manufacturing. It employs a layer-by-layer fabrication where all the plates should be flat and of the same size. This process was developed to fabricate near-net-shaped components and refined microstructures. FSAM has been extensively used in the fabrication of aluminum alloys for aerospace applications. In this work, FSAM has been carried out for AA8090 aluminum alloy. AA8090 is the second-generation Al-Li alloy with 2.3 % Li, lightweight, 10 % lower density and 11 % higher modulus than the existing commercial 2014 and 2024 Al alloy. The experiments were carried out at rotational speed (1000 – 2000 rpm), traverse speed (45–55 mm/min) and 1° constant tilt angle. The macrostructure and microstructure analysis were carried out. This was followed by microhardness and tensile test analysis. The microhardness was carried out at nine points on each layer and tensile specimen was made according to ASTM E8 standard. The maximum reduction in grain size, which is 62 %, maximum hardness value 113 HV and maximum tensile value 346.8 MPa were observed at 2000 rpm. The size of the grains decreased from the top layer into the bottom layers. The maximum hardness for all the experiments was observed in the re-stir zone of the specimens. It was concluded that with increase in process parameters, better mechanical and microstructural properties can be achieved. The fractography analysis showed the presence of dimples and tear ridges indicating a ductile fracture. © © 2025. Published by Elsevier B.V.