Faculty Publications

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Publications by NITK Faculty

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Author: search.filters.author.Herbert, M.A.Subject: search.filters.subject.Optimization

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    Influence of Process Variables on the Ultimate Tensile Strength of Friction Stir Welded AA6061 Matrix Composite
    (Springer Nature, 2021) Shettigar, A.; Prabhu B, S.R.; Herbert, M.A.; Rao, S.S.
    The present study is focused on the application of the friction stir welding process (FSW) to weld aluminium matrix composites (AMCs). Joints are formed by varying FSW process variables such as tool revolving speed (TRS), tool traverse speed (TTS) and the tool pin geometry (TPG). Influence of these parameters on the ultimate tensile strength (UTS) of the joints is investigated. Process variable optimization is done using Taguchi L18 orthogonal array design. Optimum process variables are determined and confirmed by confirmation tests based on the analysis of variance. © 2021, Springer Nature Singapore Pte Ltd.
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    Taguchi method of optimization of process variables for ultimate tensile strength of friction stir welded joint of Al-Ce-Si-Mg aluminium alloy plates
    (Elsevier Ltd, 2021) D’Souza, A.D.; Rao, S.S.; Herbert, M.A.
    A novel method of welding known as friction stir welding or FSW has found wide applications in metal joining industries now a days. There are various process input variables which affect the output quality characteristic or response of the weld joint produced. Speed of tool rotation, tool feed and tool pin contour are important input process variables and ultimate tensile stress (UTS) of the FSW joint is the output response considered in this research. The Taguchi method of Design of Experiments type optimization was used to find the level and contribution of each of these input process variables on output quality characteristic of the FSW butt joint produced on plates of Al-Ce-Si-Mg aluminium alloy material. Taguchi L9 orthogonal array type design was utilized to bring down the number of experiments from 27 to 9 for a 3 factor, 3 levels each, analysis. The results of Taguchi analysis indicated that the speed of tool rotation at 1200 rpm, tool feed at 15 mm/min and triangular shape pin tool gave the peak output UTS. The ANOVA tests demonstrated that the contribution percentage of the tool pin contour at 41%, speed of tool rotation at 29%, and tool feed at 22%, showing that the tool pin contour has maximum bearing on the output quality characteristics, i.e., UTS of the FSW joint. The optimum UTS predicted by the Taguchi analysis was 88.29 MPa, whereas the confirmation experiments gave a result of 80.54 MPa, which was well inside the confidence interval predicted by the Taguchi design. © 2021 Elsevier Ltd. All rights reserved.
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    Process parameter optimization for ultimate tensile strength of friction stir welded joint of Al-10Mg-8Ce-3.5Si aluminium alloy plates using Taguchi technique
    (Elsevier Ltd, 2022) D’Souza, A.D.; Rao, S.S.; Herbert, M.A.
    The Friction stir welding (FSW) process has become a popular method of joining metals, due to its clean and efficient nature of producing welds. The input process parameters: the tool rotation speed, tool feed and tool pin shape are the deciding parameters for an optimum output quality characteristic, the Ultimate tensile stress (UTS) of the weld joint. Here in this research, the Taguchi full factorial design technique is discussed for maximizing the UTS of the weld joint formed in Al-10Mg-8Ce-3.5Si aluminium alloy plates. The ANOVA of means and Signal to Noise ratios for UTS was used to assess the influence of each of the input process parameters on output UTS. The main effect plots of the ANOVA results demonstrated that, the tool rotation speed at level 2 or 1000 rpm, the tool feed at level 3 or 20 mm/min and tool pin shape at level 1 or triangular cross section, gave the optimum results for output UTS. The ANOVA for UTS also showed the percentage contribution of input process parameters; the shape of tool pin as 60.06%, the tool feed as 15.42% and shape of tool pin as 2.41%. The UTS value predicted by the Taguchi analysis was at 108.47 MPa which was in good agreement with the experimentally obtained value of 106.84 MPa. A nonlinear regression equation was developed by correlating the input process parameters, which could be used to predict the optimum UTS results. © 2022 Elsevier Ltd. All rights reserved.
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    Soft computing techniques during drilling of bi-directional carbon fiber reinforced composite
    (Elsevier Ltd, 2016) Shetty, N.; Herbert, M.A.; Shetty, R.; Shetty, D.S.; Vijay, G.S.
    Due to the intricacy of machining processes and inconsistency in material properties, analytical models are often unable to describe the mechanics of machining of carbon fiber reinforced polymer (CFRP) composites. Recently, soft computing techniques are used as alternate modeling and analyzing methods, which are usually robust and capable of yielding comprehensive, precise, and unswerving solutions. In this paper, drilling experiments as per the Taguchi L27 experimental layout are carried out on bi-directional carbon fiber reinforced polymer (BD CFRP) composite laminates using three types of drilling tools: high speed steel (HSS), uncoated solid carbide (USC) and titanium nitride coated SC (TiN-SC). The focus of this work is to determine the best drilling tool that produces good quality drilled holes in BD CFRP composite laminates. This paper proposes a novel prediction model 'genetic algorithm optimised multi-layer perceptron neural network' (GA-MLPNN) in which genetic algorithm (GA) is integrated with Multi-Layer Perceptron Neural Network. The performance capability of response surface methodology (RSM) and GA-MLPNN in prediction of thrust force is investigated. RSM is also used to evaluate the influence of process parameters (spindle speed, feed rate, point angle and drill diameter) on thrust force. GA is used to optimize the thrust force and its optimization performance is compared with that of RSM. It is observed that the GA-MLPNN is better predicting tool than the RSM model. The investigation in this paper demonstrates that TiN-SC is the best tool for drilling BD CFRP composite laminates as minimum thrust force is developed during its use. © 2016 Elsevier B.V. All rights reserved.
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    An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques
    (Springer, 2019) Karthik, M.C.; Malghan, R.L.; Shettigar, S.; Rao, S.S.; Herbert, M.A.
    The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition. © 2018, The Indian Institute of Metals - IIM.
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    Parameter investigation and optimization of friction stir welded AA6061/TiO2 composites through TLBO
    (Springer Science and Business Media Deutschland GmbH, 2022) Prabhu B, S.R.; Shettigar, A.; Herbert, M.A.; Rao, S.S.
    This paper explicates the joining of AA 6061/TiO2 composites by the friction stir welding (FSW) process. FSW experiments were conducted as per the three factors, three-level, central composite ivy– face-centered design method. Mathematical relationships between the FSW process parameters, namely tool geometry, welding speed, and tool rotational speed, and the output responses such as hardness, yield strength, and ultimate tensile strength were established using response surface methodology. Adequacies of established models were assessed through the analysis of variance method. Further, the paper elucidates the application of the teaching–learning-based optimization (TLBO) algorithm to identify the optimal values of input variables and to obtain an FSW joint with superior mechanical properties. The optimized experimental condition obtained from the TLBO yields an FSW joint with a UTS of 174 MPa, yield strength of 120 MPa, and hardness of 126HV. The study revealed that the result of the TLBO algorithm matched the findings of the FSW experiments. © 2021, The Author(s).