Faculty Publications

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Author: search.filters.author.Narendranath, S.Subject: search.filters.subject.Response surface methodology

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    Parametric Analysis and Response Surface Optimization of Surface Roughness and Cutting Rate in the Machining Using WEDM
    (Springer Science and Business Media Deutschland GmbH, 2022) Manoj, I.V.; Narendranath, S.
    Nickelvac HX is an amalgamation of nickel, chromium, iron, molybdenum etc. As nickel-based alloys have high-temperature strength they can be used in many applications like afterburners, blades of turbines, turbocharges, submarines parts etc. Wire electric discharge machining a non-contact spark machining was found to be the most precise machining process. Among the WEDM parameters, different process parameters like servo voltage, pulse on time, cutting speed override and pulse off time were employed for the examination. It was noticed that both response characteristics increased with the increase in cutting speed override and pulse on-time. In the case of servo voltage and pulse off time, as it was increased the cutting rate and surface roughness diminished. The effects of cutting rate on surface roughness and microhardness were analyzed. The response surface optimization was employed for optimizing surface roughness and cutting rate as it controls product quality. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Experimental investigations on performance characteristics in wire electro discharge machining of Ti50Ni42.4Cu7.6 shape memory alloy
    (2013) Narendranath, S.; Manjaiah, M.; Basavarajappa, S.; Gaitonde, V.N.
    This article investigates the effect of pulse on time, peak current and pulse off time on wire electro discharge machining characteristics of Ti 50Ni42.4Cu7.6 shape memory alloy. A Ti 50Ni42.4Cu7.6 alloy was prepared by conventional tungsten arc melting. The machining experiments were performed as per Box-Behnken design on computer control wire electro discharge machining machine using molybdenum wire electrode. The relationships between the process parameters (pulse on time, peak current and pulse off time) and wire electro discharge machining responses (surface roughness and material removal rate) have been established using response surface methodology-based quadratic models. The analysis of variance has been employed to test the significance of the developed second-order mathematical models. The parametric analysis-based results reveal that low peak current with prolonged pulse on duration leads to reduced surface roughness. However, combination of low peak current with low pulse on time is beneficial for achieving better material removal rate for machining of shape memory alloy. © IMechE 2013.
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    Influence of process parameters on material removal rate and surface roughness in WED-machining of Ti50Ni40Cu10 shape memory alloy
    (Inderscience Publishers, 2016) Manjaiah, M.; Narendranath, S.; Basavarajappa, S.; Gaitonde, V.N.
    Among the shape memory alloys (SMAs), TiNi SMAs have been typically used as the functional elements in the larger part of the industries due to exceptional properties like super elasticity and shape memory effect. However, traditional machining of these alloys is fairly complex due to these properties. The non-traditional machining process like electric discharge machining (EDM) exhibits outstanding capability in machining of these alloys. The poor selection of machining parameters may cause increased roughness of workpiece and lesser material removal rate. Hence, an effort has been made in the present work to explore the effects of three process parameters, such as pulse on time, pulse off time and servo voltage in wire electric discharge machining (WEDM) of Ti50Ni40Cu10 shape memory alloy (SMA) using zinc coated brass wire electrode on material removal rate and surface roughness using response surface methodology (RSM)-based mathematical models. The experiments were planned as per central composite design (CCD). The investigations revealed that pulse on time and servo voltage have predominant effects in maximising material removal rate and minimising surface roughness. The best combination of the process parameters for multi-response optimisation was obtained through desirability function. ©2016 Inderscience Enterprises Ltd.
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    Dry Sliding Wear Behavior of Super Duplex Stainless Steel AISI 2507: A Statistical Approach
    (De Gruyter Open Ltd peter.golla@degruyter.com, 2016) Davanageri, M.; Narendranath, S.; Kadoli, R.
    The dry sliding wear behavior of heat-treated super duplex stainless steel AISI 2507 was examined by taking pin-on-disc type of wear-test rig. Independent parameters, namely applied load, sliding distance, and sliding speed, influence mainly the wear rate of super duplex stainless steel. The said material was heat treated to a temperature of 850°C for 1 hour followed by water quenching. The heat treatment was carried out to precipitate the secondary sigma phase formation. Experiments were conducted to study the influence of independent parameters set at three factor levels using the L27 orthogonal array of the Taguchi experimental design on the wear rate. Statistical significance of both individual and combined factor effects was determined for specific wear rate. Surface plots were drawn to explain the behavior of independent variables on the measured wear rate. Statistically, the models were validated using the analysis of variance test. Multiple non-linear regression equations were derived for wear rate expressed as non-linear functions of independent variables. Further, the prediction accuracy of the developed regression equation was tested with the actual experiments. The independent parameters responsible for the desired minimum wear rate were determined by using the desirability function approach. The worn-out surface characteristics obtained for the minimum wear rate was examined using the scanning electron microscope. The desired smooth surface was obtained for the determined optimal condition by desirability function approach. © 2016 M. Davanageri et al., published by De Gruyter Open 2016.
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    ANN and RSM modeling methods for predicting material removal rate and surface roughness during WEDM of Ti50Ni40Co10 shape memory alloy
    (AMSE Press 16 Avenue Grauge Blanche Tassin-la-Demi-Lune 69160, 2017) Soni, H.; Narendranath, S.; Ramesh, M.R.
    Present study exhibits the comparison between experimental and predicted values. Where response surface method (RSM) and artificial neural network (ANN) were used as predictor for the prediction of wire electro discharge machining (WEDM) responses such as the material removal rate (MRR) and surface roughness (SR) during the machining of Ti50Ni40Co10 shape memory alloy. It has been noticed from the literature survey that pulse on time and servo voltage are most important process parameters for the machining of TiNiCo shape memory alloy, hence there are five levels of these process parameters were chosen for the present study. For the present study selected alloy has been developed through vacuum arc melting and L-25 orthogonal array has been created by using Taguchi design of experiment (DOE) for experimental plan. During the present study ANN predicted values have been found to very close to experimental values compare to RSM predicted values, hence it can be say that ANN predictor gives more accurate values compare to RSM predicted values. © 2017 AMSE Press. All rights reserved.
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    Modeling and Optimization of Wear Rate of AISI 2507 Super Duplex Stainless Steel
    (Springer Netherlands rbk@louisiana.edu, 2019) Davanageri, M.B.; Narendranath, S.; Kadoli, R.
    The present work attempts to study the parameters influencing wear, namely, applied load, heat-treated temperature, sliding velocity, and sliding distance using statistical Design of Experiments (DOE) and Response Surface Methodology (RSM). The wear behavior of super duplex stainless steel was evaluated under dry sliding conditions. A three-level Central Composite Design (CCD) based non-linear model was used to establish input-output relationship based on the collected experimental input-output data. Surface plots were used to study the influence of applied load, heat-treated temperature, sliding distance, and sliding velocity on the wear rate of super duplex stainless steel. The wear rate was observed to vary nearly non-linearly with applied load and linearly with the rest of the input parameters. Analysis of Variance (ANOVA) was conducted to test the statistical adequacy of the non-linear model developed. Applied load and heat-treated temperature were found to have a more positive contribution towards the wear rate than other parameters. Although the sliding velocity had a negligible effect, its interaction with applied load and heat-treated temperature had a significant impact on the wear rate. The regression equation developed was tested for its prediction precision with the help of 20 test cases. Further, attempts were also made to determine the optimum combination of input parameters that minimize the wear rate using the Desirability Function Approach (DFA). The objective of minimizing the wear rate was met with the highest desirability value of 1. Confirmation experiments were conducted for the determined optimal set of input parameters of 20 test cases resulting in an average absolute percent deviation in prediction of 6.34% and 5.58%. © 2018, Springer Science+Business Media B.V., part of Springer Nature.
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    Selection of optimal process parameters in sustainable diamond burnishing of 17-4 PH stainless steel
    (Springer Verlag service@springer.de, 2019) Sachin, B.; Narendranath, S.; Dupadu, D.
    Secondary finishing operations are the primary requirement of the manufacturing industries to achieve dimensional tolerance of the components. Burnishing is essentially a surface finishing operation usually performed after machining to achieve superfinishing. Diamond burnishing is one of the finest finishing technologies which has been conducted on any surface to attain mirror surface finish. The present work focuses on the development of a correlation model between the process parameters and the output responses while burnishing of 17-4 precipitation hardenable stainless steel using response surface methodology. A novel diamond burnishing tool has been used to analyze the influence of process parameters on output responses in the MQL environment. The control factors considered for the present study include burnishing speed, burnishing feed and burnishing force, and the corresponding output responses considered were surface roughness and surface hardness. The influence of process parameters on output responses has been determined by analysis of variance. Optimization was performed by a multi-objective genetic algorithm. The proposed methodology has been validated by performing experiments at the optimal process parameters, and the achieved results indicate the effectiveness of the diamond burnishing process. © 2019, The Brazilian Society of Mechanical Sciences and Engineering.