Faculty Publications
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Item 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.Item 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.Item Effect of Wire Material on Productivity and Surface Integrity of WEDM-Processed Inconel 706 for Aircraft Application(Springer New York LLC barbara.b.bertram@gsk.com, 2016) Sharma, P.; Dupadu, D.; Narendranath, S.Inconel 706 is a recently developed superalloy for aircraft application, particularly in turbine disk which is among the most critical components in the gas turbine engines. Recently, wire electrical discharge machining (WEDM) attained success in machining of gas turbine components which require complex shape profiles with high precision. To achieve the feasibility in machining of these components, the research work has been conducted on Inconel 706 superalloy using WEDM process. And, the effect of different wire materials (i.e., hard brass wire, diffused wire, and zinc-coated wire) on WEDM performance characteristics such as cutting speed, surface topography, surface roughness, recast layer formation, residual stresses, and microstructural and metallurgical alterations have been investigated. Even though, zinc-coated wire exhibits improved productivity, hard brass wire was found to be beneficial in terms of improved surface quality of the machined parts. Additionally, lower tensile residual stresses were obtained with hard brass wire. However, diffused wire has a moderate effect on productivity and surface quality. Under high discharge energy, higher elemental changes were observed and also the white layer was detected. © 2016, ASM International.Item 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.Item Experimental Investigation on Effects of Wire Electro Discharge Machining of Ti50Ni45Co5 Shape Memory Alloys(Springer Netherlands rbk@louisiana.edu, 2018) Soni, H.; Narendranath, S.; Ramesh, M.R.TiNiCo shape memory alloy is most popular shape memory alloy for biomedical applications due to their outstanding properties such as shape memory effect, pseudoelasticity and transformation temperature. Machining of such kind of alloys is very difficult through conventional machining process is very difficult because they may affect their internal properties of these alloys. However conventional machining processes give poor surface quality during the machining hence non-conventional machining processes such as (wire electro discharge machining, water jet machining and electro discharge machining etc.) are more suitable for machining of such kind of alloy. From the literature it has been found that Wire electro discharge machining (WEDM) is more suitable non-conventional machining process for such kind of alloy. Present study exhibits the effects WEDM characteristics of Ti50Ni45Co5 shape memory alloy. L-9 orthogonal array has been created by using Taguchi as a design method for machining of selected alloy and machined surface characterization has been carried out at the optimized process parameters with respect to microstructures, surface topography, microhardness, XRD analysis and residual stresses. To find the optimum setting of the input process parameters a couple of optimization techniques are used, namely principal component analysis (PCA) and Gray relational analysis (GRA) technique. 125?s pulse on time (Ton), 35?s pulse off time (Toff) and 40V servo voltage (SV) were found as an optimal setting for the higher material removal rate (MRR) with better surface roughness (SR) in the present study. Moreover, characterization of the machined surface is performed with respect to microstructures, surface topography, microhardness analysis, XRD and residual stresses. Harder surface observed near the cutting edge and TiNio3 Tio2 and CuZn were noticed on the surface of machined component through XRD analysis. However, compressive residual stress has been noticed on the machined surface during WEDM process. © 2018, Springer Science+Business Media B.V., part of Springer Nature.Item 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.Item 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.Item Optimization and Prediction of Responses Using Artificial Neural Network and Adaptive Neuro-Fuzzy Interference System during Taper Profiling on Pyromet-680 Using Wire Electric Discharge Machining(Springer, 2023) Manoj, I.V.; Manjaiah, M.; Narendranath, S.In the present study, taper cutting is performed with the aid of a uniquely designed fixture. This is attempted to avoid the difficulties in tapering using wire electric discharge machining like wire break, dimensional error, guide wear, non-uniform flushing and low surface quality. An investigation of output parameters was made during taper machining using a fixture. The cutting rate (CR) and surface roughness (SR) were considered for response surface optimization (RSM) as they were important response parameters that indicate the quality of a machined component. It is observed that servo gap voltage and pulse act contrastingly on the output parameters. For achieving a trade-off of input parameters with output responses, RSM optimization is selected during taper profiling. There were 3-5% variations for both CR and SR when compared to experimental and RSM optimal values. The tapered profile slots of different angles like 0°, 15° and 30° were machined on Pyromet-680 using optimal machining parameters. The effect of different profiling parameters like wire distance between guides (WD), dwell time (DT), profile offset (PO) and cutting speed override (CO) on output responses like CR and SR was analyzed. Adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) models have been established for the prediction of the output responses. The validation is performed by experimentation, and the prediction errors ranged from 0 to 5% for both the responses CR and SR in ANFIS models. So ANFIS models proved to be the most efficient as there is an improvement of 45-50% in prediction compared to ANN models. © 2022, ASM International.