Faculty Publications
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Item Novel application of graphite-talc hybrid nanoparticle enriched cutting fluid in turning operation(Elsevier Ltd, 2021) Singh, V.; Sharma, A.K.; Sahu, R.K.; Katiyar, J.K.In this study, the influence of hybrid nanocutting fluid (both graphite and talc nanoparticles dispersed in a base fluid) in turning of Titanium alloy grade 5. The hybrid nanocutting fluid was developed by the blending of graphite and talc nanoparticles in a constant volumetric proportion (50:50) in pure coconut oil as a base fluid. The prepared hybrid nanocutting fluid has been investigated for its tribological behaviour using a pin-on-disc machine. The Gray relational analysis (GRA) is applied as a conservative approach in the optimization of process variables of Titanium alloy with multiple performance characteristics. The turning performance of the hybrid nanocutting fluid is compared with that of pure coconut oil in terms of cutting force and surface roughness. From the Gray relational grade analysis, it is obtained that the feed rate has a larger influence on responses as compared to cutting speed and nanoparticle concentration as well. By the application of hybrid nanocutting fluid, it is obtained a significant reduction in cutting force and surface roughness compared to pure coconut oil by 21.19 % and 18.9 %, respectively. © 2020 The Society of Manufacturing EngineersItem Artificial Intelligence System Approach for Optimization of Drilling Parameters of Glass-Carbon Fiber/Polymer Composites(Springer Science and Business Media B.V., 2021) Upputuri, U.H.; Vijaya Sai, N.V.; Sahu, R.K.In recent times, the study on machining characteristics of combined (hybrid) fiber polymer composites has drawn a remarkable research attention because of its emerging industrial applications. The present study focuses on the drilling of hybrid glass-carbon fiber reinforced (GCFR) epoxy composites fabricated using hand layup technique. The machining characteristics were considered in the drilling of GCFR composites which include thrust force, torque, delamination factor and surface roughness. The influence of the drilling process parameters such as spindle speed, drill diameter and feed rate on the characteristics are studied. To avoid the confounding effect of the individual optimized characteristics, an artificial intelligence system i.e. fuzzy inference system approach is adopted. The fuzzy inference system transformed all the performance characteristics of drilled hybrid composites into a multi response performance index (MPI) and optimized the MPI at the common factor level setting. The optimal combination of process parameters for minimum thrust force, torque, delamination factor and surface roughness found to be: speed 3000 RPM, drill diameter 5 mm and the feed rate 50 mm/min. The analysis of variance results show that drill diameter is the most significant parameter followed by feed rate and speed. Further, a theoretical model was proposed for the estimation of MPI and found that an average absolute error of 14.8% with respect to the experimental MPI data is obtained. © 2020, Springer Nature B.V.Item Multi-response optimization and effect of tool rotation on micromachining of PMMA using an in-house developed µ-ECDM system(Elsevier Ltd, 2022) Bhargav, K.V.J.; Balaji, P.S.; Sahu, R.K.; Katiyar, J.K.Poly-methyl methacrylate (PMMA) is a lightweight and transparent thermoplastic material which is commonly used as an alternative for high-cost and resilient glass. PMMA has potential applications in the fields of microfluidics because of its high strength, low weight, optical transparency, and biocompatibility. Therefore, in this study, in-depth experimentation was carried out to generate microchannels on PMMA using an in-house developed micro Electrochemical Discharge Machining (µ-ECDM) system. The µ-ECDM process parameters used for the experimentation include voltage (V), electrolyte concentration (wt%), and duty factor (DF) (%). Experiments were designed at three levels of process parameters for the parametric study. The microchannels were machined on a 2.5 mm thick PMMA workpiece using a titanium tool of diameter 0.7 mm. The optical microscope images, along with SEM images, are used to characterize the machined channels. The machining characteristics such as material removal rate (MRR), tool wear rate (TWR), channel width, surface roughness (SR), and depth of the channel were studied using the process parameters. Individual response optimization is carried out using S/N ratios, but confounding of factors at different factor level settings is observed for each response. Therefore, to overcome this problem, multi-response optimization using the JAYA algorithm coupled with the multi-attributed decision-making (MADM) R-method has been adopted for maximizing MRR and depth of the channel and minimizing TWR, channel width, and surface roughness at single factor level settings. The optimal process parameters are obtained by multi-response optimization are 51 V, 24 wt%, and 55% DF, and the MRR, TWR, channel width, surface roughness, and depth of the channel are found to be 21.5 µg/min, 5.5 µg/min and 804.33 µm, 5.2412 µm, and 238.22 µm, respectively that are in close pact with the predicted observations. Further, the optimal machining parameters have been used along with tool rotation (in RPM) to observe the effect on machining features. The findings show that with increment in tool rotation rate improved the MRR, TWR, and depth of the channel decreased the channel width and surface roughness. © 2022 CIRPItem Generation of microchannels on PMMA using an in-house fabricated μ-ECDM system(Walter de Gruyter GmbH, 2023) Bhargav, K.V.J.; Balaji, P.S.; Sahu, R.K.Electrochemical corona discharge micromachining (μ-ECDM) is a newly advented, advanced hybrid machining process capable of machining non-conducting and conducting materials. In this article, Polymethyl methacrylate (PMMA), a non-conducting material, often used in microfluidic applications, is machined to generate microchannels. The process parameters chosen for machining are voltage, duty factor, and concentration. The process parameters are chosen at three levels, and their effect on machining characteristics such as material removal rate and surface roughness are detailed in this paper. Optimization is carried out for individual response using the signal to noise ratio optimization technique for maximizing material removal rate and minimizing surface roughness. © 2023 Walter de Gruyter GmbH, Berlin/Boston.Item Isolation of microcrystalline cellulose from Musa paradisiaca (banana) plant leaves: physicochemical, thermal, morphological, and mechanical characterization for lightweight polymer composite applications(Springer Science and Business Media B.V., 2024) Indra Reddy, M.I.; Sethuramalingam, P.; Sahu, R.K.Natural cellulose owing to its remarkable microstructural and physiochemical behaviour, and its eco-friendliness have attracted significant interest among the researchers. Therefore, in this work, microcrystalline cellulose (MCC) is extracted from the Musa paradisiaca plant leaf (MPPL) debris which is accumulated in large quantity and treated as waste material. The purified micro-cellulose is obtained by subjecting the MPPL raw material to alkali treatment followed by acid hydrolysis, bleaching and slow pyrolysis. From the FT-IR spectra of the cleaned cellulose, it is observed that its amorphous phase is eliminated. The crystallinity index is found to be 87.42% and this value is attributed to the sodium chlorite bleaching. The particle size analyzer results show that the micro-cellulose found to have a bimodal distribution with an average size of 35.97 μm and standard deviation 16.53. It is evident from SEM that the microcrystalline cellulose is of semi-spherical in shape and found to be aggregated with uneven distribution. Further, TGA analysis is carried out in this work and the results show that the microcrystalline cellulose can exhibit high heat resistance up to 297 °C. Surface roughness values (Ra) for MPPL MCC is 58.41 μm. The properties are well suited for futuristic polymer composite applications such as filler addition in biofilm for packaging industries and coating material in pharma industries. © The Polymer Society, Taipei 2024.Item Machining Parameter Optimization of Wire Electrical Discharge Machining for Ni50.3Ti29.7Hf20 Alloy Using TOPSIS and Grey Wolf Optimization Technique(Springer, 2025) Bhaskar, M.; Balaji, V.; Narendranath, S.; Sahu, R.K.Ni50.3Ti29.7Hf20 is an alloy with shape memory characteristics that can withstand high temperatures. It possesses remarkable strength, hardness, and exceptional corrosion resistance. SMAs are well-suited for various applications, including automotive sensors, automobiles, aerospace technologies, robotics, actuators, and MEMS devices. However, its unique properties make it difficult to machine using conventional methods. Wire EDM is an unconventional machining process suited for difficult-to-machine materials like Ni-Ti-Hf alloy, providing high accuracy and precision and minimizing the risk of material damage. This paper focuses on the optimization of machining parameters, namely Discharge time (PON), Pause time (POFF), Gap voltage (GV), and Wire travel speed (WS) during WEDM of Ni-Ti-Hf shape memory alloy utilizing the TOPSIS and GWO techniques. The aim is to obtain optimal machining parameters for improving the machined Ni-Ti-Hf alloy’s material removal rate (MRR) and surface roughness (Ra). The optimal machining parameters from GWO were PON = 123.8 µs, POFF = 50 µs, WS = 2, and GV = 25. The predicted values of material removal rate and surface roughness are 4.22 mm3/min and 3.62 µm, respectively. The experimental verification demonstrates the proposed optimization approach's effectiveness, as the predicted values correlate strongly with the actual values. © ASM International 2023.