Faculty Publications
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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 Micromachining of borosilicate glass using an electrolyte-sonicated-µ-ECDM system(Taylor and Francis Ltd., 2023) Bhargav, K.V.J.; Balaji, P.S.; Sahu, R.K.Glass has become an integral part of today’s world. This is because of its wide range of applications owing to its various potential properties. Though it has enormous applications, processing or machining glass is a challenging task. The present study focuses on the generation of microholes on borosilicate glass (thickness: 1000 µm) using an in-house developed in-situ electrolyte-sonicated (ES)-micro electrochemical discharge machining (µ-ECDM), i.e. ES-µ-ECDM system. The experiments revealed that the sonication of electrolytes had increased the electrolyte flushing, which enables the basic µ-ECDM process to push its limits and machine the materials beyond 300 µm (hydrodynamic regime). The process parameters selected for the experimentation are voltage, concentration, and duty factor with sonication of electrolyte at 36 kHz frequency throughout the experiments. Material removal rate (MRR) and overcut (OC) are identified as the machining characteristics in this study. To acquire enhanced machining characteristics, the process parameters are further optimized using the MOJAYA algorithm in conjunction with the R-method which is a multi-attribute decision-making method (MADM). The detailed experimentation revealed that using electrolyte sonication through-holes was achieved at a higher level of parameter settings. © 2022 Taylor & Francis.Item Micromachining of Al7075 alloy using an in-situ ultrasonicated µ-ECDM system(Taylor and Francis Ltd., 2023) Bhargav, K.V.J.; Pyla, K.R.; Balaji, P.S.; Sahu, R.K.Al7075 is a lightweight metal alloy essentially used in various engineering sectors possessing applications in aerospace, military, missile, etc. Miniaturized machining operations have placed a great deal of pressure on the conventional machining capabilities of Al7075 alloys as they possess certain challenges due to their ductile and unique adhesive nature, which must be overcome. The present study focuses on generating through-holes on Al7075 alloy using an electrolyte ultrasonication-assisted µ-ECDM system. The FCC-RSM factorial-based design is chosen at three levels to carry out experimentation with process characteristics voltage (V), concentration (wt%), and duty factor (%DF). The material removal rate (MRR), top hole overcut (TOC), bottom hole overcut (BOC), and circularity (CIR) are the machining responses. JAYA algorithm, a multi-objective optimization is performed, and optimal process parameters are obtained using the R method. Further, RSM based desirability approach is also used to obtain optimal process parameters and compared them with results obtained from R-method and found to be relatively close. © 2023 Taylor & Francis.Item 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 Influence of Process Parameters and its Optimization on Wear Behavior of an Exceptional Aegle Marmelos Polymer/Aluminum Composite(Springer, 2024) Veeranaath, V.; Sahu, R.K.; Priya, I.M.The present paper is focused on the indigenous production of a unique and low-cost Aegle Marmelos natural polymer (AMNP) powder via chemical synthesis and its reinforcement in the aluminum matrix via powder metallurgy. The wear behavior of Aegle Marmelos natural polymer-reinforced (AMNPR) aluminum composites is studied. The effect of control parameters like reinforcement (wt.%) and different sliding parameters on the wear characteristics is discussed. The SEM studies revealed that severe damage due to adhesive wear, delamination, and formation of oxide zones is observed at reinforcement concentrations of 10 wt.% and 15 wt.%. The optical profilometry study also revealed that the roughness of the worn-out samples was maximum at 10 wt.% reinforcement. Further, the process parameters with each characteristic are optimized individually and the optimal parameters are different. To avoid this confounding effect, TOPSIS coupled with CRITIC method is adopted to convert all characteristics into a closeness coefficient (Ci) and optimize at a common parameter level setting. The optimal combination of process parameters for minimum wear characteristics is as follows: reinforcement concentration: 20 wt.%, sliding load: 25 N, sliding speed: 200 rpm, and sliding duration: 4 min. The confirmation test results were validated and showed an improvement of the closeness coefficient by 0.0116. In this study, a statistical multi-regression model is also developed for predicting the closeness coefficient of the developed composites under different parametric conditions. The predicted values obtained from the regression model agreed well with the experimental values, with a mean absolute error of 5.478%. © ASM International 2024.Item Optimization of measured mechanical characteristics of selective microwave hybrid heating processed Inconel 625/ SS 304 weldments using multi-objective JAYA algorithm coupled with multi-attributes decision making R-method(Elsevier B.V., 2025) Singha, B.; Kamble, D.L.; Sahu, R.K.; Narendranath, S.; Badiger, R.I.This work focuses on the joining of Inconel-625/SS-304 using selective microwave hybrid heating (SMHH) technique. Input power, filler powder particle size, separator, and susceptor size are considered for experimentation according to the Definitive Screening Design. The multi-objectives measured are UTS, FS, and microhardness. XRD results show the intermetallic/secondary phases, and FESEM micrographs show the metallurgical bonding occurs between base metal and filler. The joint and interface region had an average microhardness of 204 ± 10 HV and 342 ± 18 HV, respectively. The UTS and FS of the weldments measured to 550 MPa and 805 MPa. MOJAYA technique is utilized for multi-objective optimization, and R-method determined the optimal process parameters. The optimal process parameters found to 2.2 kW, 25 ?m powder, 120 grit and 0.804 mm separator. The confirmation test reveals UTS ? 566 MPa, FS ? 903 MPa, and microhardness ? 365 HV, which closely matched with predicted observations. © 2024 Elsevier Ltd