Faculty Publications

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Author: search.filters.author.Narendranath, S.Subject: search.filters.subject.Wire electric discharge machining

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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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    Wire electric discharge machining characteristics of titanium nickel shape memory alloy
    (Nonferrous Metals Society of China B12 Fuxing Road Beijing 100814, 2014) Manjaiah, M.; Narendranath, S.; Basavarajappa, S.; Gaitonde, V.N.
    TiNi shape memory alloys (SMAs) have been normally used as the competent elements in large part of the industries due to outstanding properties, such as super elasticity and shape memory effects. However, traditional machining of SMAs is quite complex due to these properties. Hence, the wire electric discharge machining (WEDM) characteristics of TiNi SMA was studied. The experiments were planned as per L27 orthogonal array to minimize the experiments, each experiment was performed under different conditions of pulse duration, pulse off time, servo voltage, flushing pressure and wire speed. A multi-response optimization method using Taguchi design with utility concept has been proposed for simultaneous optimization. The analysis of means (ANOM) and analysis of variance (ANOVA) on signal to noise (S/N) ratio were performed for determining the optimal parameter levels. Taguchi analysis reveals that a combination of 1 ?s pulse duration, 3.8 ?s pulse off time, 40 V servo voltage, 1.8×105 Pa flushing pressure and 8 m/min wire speed is beneficial for simultaneously maximizing the material removal rate (MRR) and minimizing the surface roughness. The optimization results of WEDM of TiNi SMA also indicate that pulse duration significantly affects the material removal rate and surface roughness. The discharged craters, micro cracks and recast layer were observed on the machined surface at large pulse duration.
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    Effect of electrode material in wire electro discharge machining characteristics of Ti50Ni50-xCux shape memory alloy
    (Elsevier Inc. usjcs@elsevier.com, 2015) Manjaiah, M.; Narendranath, S.; Basavarajappa, S.; Gaitonde, V.N.
    Abstract TiNiCu alloy belongs to new class of shape memory alloy (SMA), which exhibits superior properties like shape memory effect, super elasticity and reversible martensitic transformation phase and thus find broad applications in actuators, micro tools and stents in biomedical components. Even though, SMA demonstrates outstanding property profile, traditional machining of SMAs is fairly complex and hence non-traditional machining like wire electric discharge machining (WEDM) has been performed. Hence, there is a need to investigate the WEDM performance characteristics of shape memory alloys due to excellent property profile and potential applications. In the present investigation, various machining characteristics like material removal rate (MRR), surface roughness, surface topography and metallographic changes have been studied and the influence of wire material on TiNiCu alloy machining characteristics has also been evaluated through ANOVA. Ti50Ni50-xCux=10, 20 was prepared by vacuum arc melting process. The proposed alloy as-cast material exhibits austenite property (B2 phase) and having higher hardness when compared to TiNi alloy. The investigation on WEDM of Ti50Ni50-xCux alloy reveals that the machining parameters such as servo voltage, pulse on time and pulse off time are the most significant parameters affecting MRR as well as surface roughness using both brass and zinc coated brass wires. However, machining with zinc coated brass wire yields reduced surface roughness and better MRR and also produces less surface defects on the machined surface of Ti50Ni50-xCux alloys. © 2015 Elsevier Inc. All rights reserved.
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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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    Variation and artificial neural network prediction of profile areas during slant type taper profiling of triangle at different machining parameters on Hastelloy X by wire electric discharge machining
    (SAGE Publications Ltd, 2020) Manoj, I.V.; Narendranath, S.
    In the present research work, an in-house developed fixture is used to achieve taper profiles which avoids the disadvantages in convention tapering operation in wire electric discharge machining like wire bend, inaccuracies in taper, insufficient flushing, guide wear etc. A simple triangular profile was machined at 0°, 15° and 30° slant/taper angles. These taper profile areas are investigated for various machining parameters like wire guide distance, corner dwell time, wire offset and cutting speed override. It is observed that as the wire guide distance and cutting speed override increases, the profile area decreases. Whereas in case of wire offset, as offset increases the profile areas also increase. The corner dwell time parameter do not effect on the profile area. The taper profile areas measured highest at 30° followed by 15° and 0° slant angles. This is due to the workpiece placed at different angles during machining with the aid of fixture to obtain taper profile. The taper angle represents the angularity of slant triangular profiles. As the slant angle increases the variation in taper error also increases due to higher wire vibration. An artificial neural network model is developed for the prediction of these areas at a different slant angle. The model is validated experimentally where the errors in prediction ranged from 1% to 9%. In conclusion, it can be noticed that the machining parameters and slant angle influence on profiles irrespective of their dimensions. © IMechE 2020.
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    Slant type taper profiling and prediction of profiling speed for a circular profile during in wire electric discharge machining using Hastelloy-X
    (SAGE Publications Ltd, 2021) Manoj, I.V.; Narendranath, S.
    Hastelloy-X a nickel-based alloy used in nozzles, flame holders, turbine blades, turbocharges, jet engine tailpipes, afterburner components etc. having complex tapering profiles. Wire electric discharge machining proves to be the most beneficial machining technique as it provides required accuracy for the components. In the present research, a slant type taper fixture is employed for achieving taper angles as convention tapering have many hindrances like wire bend, angular inaccuracy, guide wear, insufficient flushing and wire breakage etc. and machining a simple circular profile on Hastelloy-X. The behaviour of different output parameters like profiling speed, surface roughness, profile areas, microhardness and recast layer were investigated for various input parameters for machined taper components at 0°, 15° and 30°. The cutting speed override parameter influenced most on the profiling speed and surface roughness. The wire offset parameter was found to be the most significant factor in the case of circular profile areas that were machined. The variation of different output parameters to profiling/cutting speed and taper angle was also highlighted. It is found the recast layer decreased which indicated lesser thermal degradation at higher taper angles at different profiling parameters. This is also validated by the microhardness where the machined surface hardness of taper angular profiles was found to be greater than the 0° profiles. The artificial neural networks and adaptive neuro-fuzzy interference system were used for the prediction of profiling speed. The adaptive neuro-fuzzy interference system was found better in prediction as the percentage error varies between 0–5 per cent. In conclusion, the profiling speed influences both on the accuracy and surface of machined taper circular profiles. © IMechE 2021.
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    Wire Electric Discharge Machining at Different Slant Angles during Slant Type Taper Profiling of Microfer 4722 Superalloy
    (Springer, 2022) Manoj, I.V.; Narendranath, S.
    Wire electric discharge machining (WEDM) is nonconventional machining that provides machining solutions irrespective of the material hardness. In the present study, a simple profile was machined on Microfer 4722 at different slant angles using to know the effect of machining parameters. A unique method of obtaining taper components was employed by slant type taper fixture to avoid the disadvantages of the conventional method. The profiling speed, profile roughness, profiling error (Corner error), recast layer thickness, micro-hardness, microstructural and metallurgical changes of the machined component were investigated. As the taper of the component increases the profile roughness, corner error increases although profiling speed decreases. It is observed that recast layer thickness decreases as the taper of the component increases. A contrasting phenomenon is observed in the case of hardness at the WEDM surface. The metallurgical changes like the addition of Cu, Zn and O in the nickel-based alloy after machining from WEDM at different slant angles are highlighted. It is observed that residual stress decreased as the slant angles increased from 0° to 30° during slant type profiling. © 2021, ASM International.
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    A study on the influence of WEDM parameters on surface roughness, kerf width, and corrosion behavior of AZ31B Mg alloy
    (Elsevier Ltd, 2022) Chaitanya, V.H.; Sekar, P.; Narendranath, S.; Balaji, V.
    Wire electric discharge machining (WEDM) is a nontraditional machining process where the material is removed by the spark erosion technique. This technique is used to machine AZ31B, a biodegradable Magnesium alloy. In the present work impact of WEDM input parameters, namely pulse on time (Ton), pulse off time (Toff), servo voltage (SV), and wire feed (WF) on response characteristics is studied. The response characteristics considered are kerf width (KW), surface roughness (SR), and corrosion rate (CR). L9 orthogonal array by Taguchi's is employed as the design of experimentation. Taguchi's analysis implied that TON is the most influencing input parameter on the response characteristics. At a relatively lower TON setting (105 μs), comparatively lesser kerf width (335.894 μm), lower surface roughness (3.069 μm), and lower corrosion rate (0.95 mm/year) are exhibited by the machined specimens. From the main effects plots using signal-to-noise ratios, it is understood that the values of response characteristics increased with an increase in TON value. It is due to the increase in discharge at the more pulse on time duration. It is also understood that a surface with relatively better surface finish exhibited better corrosion resistance. With the help of regression equations, the relation between response characteristics and input parameters is built. © 2022 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
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    Artificial neural network-based prediction assessment of wire electric discharge machining parameters for smart manufacturing
    (De Gruyter Open Ltd, 2023) Manoj, I.V.; Narendranath, S.; Mashinini, P.M.; Soni, H.; Rab, S.; Ahmad, S.; Hayat, A.
    Artificial intelligence (AI), robotics, cybersecurity, the Industrial Internet of Things, and blockchain are some of the technologies and solutions that are combined to produce "smart manufacturing,"which is used to optimize manufacturing processes by creating and/or accepting data. In manufacturing, spark erosion technique such as wire electric discharge machining (WEDM) is a process that machines different hard-to-cut alloys. It is regarded as the solution for cutting intricate parts and materials that are resistant to conventional machining techniques or are required by design. In the present study, holes of different radii, i.e. 1, 3, and 5 mm, have been cut on Nickelvac-HX. Tapering in WEDM is a delicate process to avoid disadvantages such as wire break, wire bend, wire friction, guide wear, and insufficient flushing. Taper angles viz. 0°, 15°, and 30° were obtained from a unique fixture to get holes at different angles. The study also shows the influence of taper angles on the part geometry and area of the holes. Next, the artificial neural network (ANN) technique is implemented for the parametric result prediction. The findings were in good agreement with the experimental data, supporting the viability of the ANN approach for the evaluation of the manufacturing process. The findings in this research provide as a reference to the potential of AI-based assessment in smart manufacturing processes and as a design tool in many manufacturing-related fields. © 2023 the author(s), published by De Gruyter.
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    Optimization of wire-EDM process parameters for Ni–Ti-Hf shape memory alloy through particle swarm optimization and CNN-based SEM-image classification
    (Elsevier B.V., 2023) M, R.V.; Balaji, V.; Narendranath, S.
    Shape memory alloys (SMAs) have the unique ability to regain their shape under specified conditions, making them extremely useful for a wide range of applications. However, non-traditional machining techniques could be more effective for high-temperature SMAs as they provide better shape recovery properties than conventional methods, necessitating this study's unconventional wire electric discharge machining procedure. The surface morphology of Ni–Ti-Hf-based alloys was examined using scanning electron microscopy. A convolutional neural network model was used to categorize SEM images based on the material removal rate, utilizing the pixel intensity histogram of the processed images. The study discovered that the material remelted as the discharge energy increased, leaving lumps and globules on the surface. The size of debris lumps, pores, and globules increased with increasing Ra values. Moreover, widening the inter-electrode gap by expanding the servo-voltage facilitated efficiently removing debris from the machined site. The TOPSIS method for particle swarm optimization was employed to find the optimal solutions, yielding TON = (124.239, 116.228), TOFF = (54.532, 40.781), Servo voltage = (36.216, 43.766), and Wire-Feed = (2.157, 8). These results were validated through experimentation, with minimal error percentages of 2.01%, 2.046% (MRR), and 3.86%, 1.611% (Ra) for both sets of input parameters, respectively. © 2023