Faculty Publications
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Publications by NITK Faculty
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Item Prediction of surface finish and optimization of machining parameters in turning(2012) Prasad, D.; Krishna, P.; Rao, S.S.Surface roughness plays a crucial role in the functional capacity of machined parts. In this work, experiments were carried out on a conventional lathe for different cutting parameters namely feed, spindle speed, depth of cut and tool nose radius according to Taguchi Design of Experiments. Radial acceleration readings were taken with an accelerometer. Optimum cutting parameters and their level of significance were found using Taguchi analysis (ANOVA). Regression analysis was carried out to identify whether the experimental roughness values have fitness characteristic with the process parameters. Recurrence Plots (RP) were obtained using the sensor signals which determine surface roughness qualitatively and Recurrence Quantification Analysis (RQA) technique was used to quantify the RP obtained. Surface finish was predicted using a feed forward back propagation neural network with RQA parameters, cutting parameters and acceleration data as inputs to the network. The validity and reliability of the methods were verified experimentally. © (2012) Trans Tech Publications.Item Effect of Lateral Vibrations during Directional solidification on Mechanical Properties of Al-18%wt Si Alloys(Elsevier Ltd, 2018) Ramesh Babu, N.; Ramesh, M.R.; Kiran Aithal, S.; Kotresh, K.Experimental Investigation on the effect of mold vibration on the mechanical properties of Al-18%WtSi have been carried out using Taguchi Technique, as the molten metal at 750°C is poured in to the insulated mold which is subjected to lateral vibrations, directional solidification takes place due to the presence of chill at the bottom which gives rise to a functionally graded alloy. Due to the excitation, silicon present in the molten metal precipitates along its length. The castings are prepared with varying chill materials and chill volumes without vibrations and with a vibrating frequency of 50Hz. ANOVA was applied to optimize the process parameters. Hardness and Tensile test for the samples was carried out. Improvements in the properties can be attributed to the grain refinement of the casting prepared under vibrations. © 2017 Elsevier Ltd.Item Assessment and Prediction of Specific Energy Using Rock Brittleness in Rock Cutting(Springer Nature, 2020) Raghavan, V.; Murthy, C.S.N.In this study, we used picks with point attack angles of 45°, 50°, 55°, and 65° and 45°, 55°, and 65° attack angles in rock cutting experiments. The main objective is to estimate specific energy during the cutting process based on rock brittleness and study the influence of attack angle on specific energy. From the experimental data, we compared the obtained results using multiple linear regressions and ANOVA to predict the specific energy and found that the model developed were statistically significant. R2 of the brittleness B4 is 0.79 in comparision with R2 of density, UCS, BTS and abrasivity as 0.74, 0.83, 0.84 and 0.73. Specific energy not only be predicted from density, UCS, BTS, abrasivity, it can also be predicted using rock brittleness. © 2020, Springer Nature Switzerland AG.Item Optimal Parameters Identification of Quarter Car Simulink Model for Better Ride Comfort and Road Holding(Springer Science and Business Media Deutschland GmbH, 2021) Puneet, P.; Hegale, A.; Kumar, H.; Gangadharan, K.V.Advancement in vehicle technology has explored many possibilities for improvement, keeping customer satisfaction in mind. One major criterion which a passenger always wishes to possess is ride comfort. But the suspension parameters suitable for a good ride comfort may not support another salient feature called road holding. Hence, in this work an attempt has been made to simultaneously improve the ride comfort and road holding, using a quarter car test model using MATLAB Simulink for a commercial light motor vehicle. Initially, a commercially available passive damper of light motor vehicle has been characterized using dynamic testing machine (DTM) in order to obtain its force–displacement behavior and damping nature. A design of experiment (DOE) has been conducted by taking vehicle velocity, sprung mass, spring stiffness and damping coefficient into consideration, for experimentation using quarter car model. Regression equations have been extracted for relating the problem parameters to both ride comfort and road holding. Analysis of variance (ANOVA) has been used to know the influence of each parameter toward the target response. In the later stage, response surface methodology optimization technique has been used in order to optimize the parameters for better ride comfort and road holding. Optimized parameters are substituted again in the quarter car model, to validate the results obtained during optimization. The present work concluded with an optimal ride comfort and road holding and proved the effectiveness of optimization technique in achieving so. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Comparison of Response Surface Methodology (RSM) and Machine Learning Algorithms in Predicting Tensile Strength and Surface Roughness of AA8090/B4C Surface Composites Fabricated by Friction Stir Processing(Springer Science and Business Media Deutschland GmbH, 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.; Shrivathsa, T.V.; Tapariya, R.Friction stir processing is an innovative solid-state process, widely utilized for surface composite fabrication, material property enhancement, and microstructural modification. Rotational speed, traverse speed, groove width, and axial force are key FSP parameters that improve the characteristics of surface composites (SCs). This work makes use of FSP to fabricate AA8090/B4C SCs by altering parameters within ranges. Response variables include ultimate tensile strength (UTS) and surface roughness (SR). Central composite design (CCD) of response surface methodology (RSM) leads trials, establishing a mathematical relationship between input parameters and UTS/SR. The models’ adequacy is validated using ANOVA, which investigates the impact of input parameters on UTS and SR. This study also looks into machine learning regression methodologies for UTS and SR forecasting in AA8090/B4C SCs. The ML algorithms are evaluated by utilizing performance metrics like coefficient of determination (R2) and root mean squared error (RMSE). Predicted UTS and SR values from RSM are compared with machine learning outcomes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Delamination analysis in drilling process of glass fiber reinforced plastic (GFRP) composite materials(2007) Mohan, N.S.; Kulkarni, S.M.; Ramachandra, A.Machining processes are generally used to cut; drill, or contour composite laminates for building products. In fact, drilling is one of the most commonly used manufacturing processes to install fasteners for assembly of laminate composites. The material anisotropy resulting from fiber reinforcement heavily influences the machinability during machining. Machining of fiber reinforced plastic (FRP) components is often needed in spite of the fact that most FRP structures can be made to near-net shape and drilling is the most frequently employed secondary machining process for fiber reinforced materials. Therefore, the precise machining needs to perform to ensure dimensional stability and to obtain a better productivity of the component. The drilling parameters and specimen parameters evaluated were speed, feed rate, drill size and specimen thickness. A series of experiments were conducted using TRIAC VMC CNC machining center to machine the composite laminate specimens at various cutting parameters and material parameters. The measured results of delamination at the entry and exit side of the specimen were measured and analyzed using commercial statistical software MINITAB14. The experimental results indicated that the specimen thickness, feed rate and cutting speed are reckoned to be the most significant factors contributing to the delamination. A signal-to-noise ratio is employed to analyze the influence of various parameters on peel up and push down delamination factor in drilling of glass fibre reinforced plastic (GFRP) composite laminates. The main objective of this study is to determine factors and combination of factors that influence the delamination using Taguchi and response surface methodology and to achieve the optimization machining conditions that would result in minimum delamination. From the analysis it is evident that among the all significant parameters, specimen thickness and cutting speed have significant influence on peel up delamination and the specimen thickness and feed have more significant influence on push down delamination. Confirmation experiments were conducted to verify the predicted optimal parameters with the experimental results, good agreement between the predicted and experimental results obtained to be of the order of 99%. © 2007 Elsevier B.V. All rights reserved.Item Application of response surface methodology on surface roughness in grinding of aerospace materials (6061Al-15Vol%SiC25P)(2010) Dayananda Pai, D.; Rao, S.S.; Shetty, R.; Nayak, R.In this paper, the effects and the optimization of machining parameters on surface roughness in the grinding of 6061Al-SiC25P (MMCs) specimen are investigated. In the grinding process, a machining parameter, such as hardness of the specimen, flow rate of the coolant and depth of cut while machining were chosen for evaluation by the response surface methodology. By response surface methodology, a complete realization of the process parameters and their effects were achieved. The variation of surface roughness with machining parameters was mathematically modeled using response surface methodology. Finally, experimentation was carried out to identify the effectiveness of the proposed method. © 2006-2010 Asian Research Publishing Network (ARPN). All rights reserved.Item Instrumented ballistic performance of jute/epoxy sandwich with functionally graded rubber core(Inderscience Publishers, 2012) Doddamani, M.R.; Kulkarni, S.M.The qualitative analysis of instrumented ballistic impact for jute-epoxy sandwiches with fly ash reinforced functionally graded (FG) flexible, compliant rubber core is presented. An attempt is made to study the influence of fly ash weight fraction, jute orientation and core to total thickness (C/H) of sandwich on ballistic performance. Experiments are designed based upon L9 orthogonal array. Analysis of variance (ANOVA) is performed on recorded data to investigate the influence of parameters on ballistic response. An optimal parameter combination is determined leading to higher energy absorption and lower energy required for skin pullout by the bullet. A correlation derived from the results of Taguchi experimental design is proposed as a predictive equation for estimation of energy absorption of sandwiches. Furthermore, for arresting bullet optimum stack thickness of sandwich configuration is presented. Finally, the potential benefits for using such materials as a replacement for sand bags in guarding posts is highlighted. Copyright © 2012 Inderscience Enterprises Ltd.Item Application of Desirability Approach to Optimize the Control Factors in Cryogenic Diamond Burnishing(Springer, 2020) Sachin, B.; Narendranath, S.; Dupadu, D.Cryogenic diamond burnishing is an impactful method to enhance the functional performance of the product. In this article, an experimental study on the diamond burnishing of 17-4 precipitation hardenable stainless steel in a cryogenic cooling condition has been presented. This material has excellent corrosion resistance, high strength and enormous applications in the manufacturing industries. The control variables were namely burnishing force, burnishing feed and burnishing force have been studied and modeled for the output responses explicitly surface hardness and surface roughness. The influence of control variables on performance features has been analyzed using response surface graphs. The significant influence of burnishing conditions on the output responses was established by analysis of variance. Desirability function approach has been employed to optimize the multi-performance characteristics. At the corresponding highest desirability, the optimal process parameter combination was found to be burnishing feed = 0.053 mm/rev, burnishing speed = 31.29 m/min and burnishing force = 200 N which yields a minimum surface roughness = 0.199 µm and maximum surface hardness = 397.48 HV. The maximum percentage of error among the predicted and experimental results was found to be 10% and 2%, respectively, for surface roughness and surface hardness. The investigational findings were observed to be in agreement with the predicted value with permissible deviation. © 2020, King Fahd University of Petroleum & Minerals.Item Study and Experimental Investigation of the Effect of Progressive Feed Rate on Surface Roughness in CNC End Milling Process Using RSM(International Information and Engineering Technology Association, 2022) Bommisetty, S.R.; Chettu, K.B.; Hanumanthappa, S.N.The objective of this research work is to investigate the influence of cutting parameters on the average surface roughness (Ra) in an end milling process. Feed rate if). Spindle speed (s) and Depth of cut (d) are the cutting parameters considered as significant factors. A case study on the progressive feed (PF) and conventional constant feed (CF) machining characteristics of Aluminum alloy BS L168-T6511 using end milling is considered. Taguchi's design of experiments (DoE) technique is applied for various combinations of cutting factors and average surface roughness was measured using Mitutoyo surftest SJ-301 surface roughness tester. The experimental results of Ra are analyzed by response surface methodology (RSM). The predicted values using the developed regression mathematical model are compared against experimental results and were found in close agreement. ANOVA technique was applied to further analyze the data for checking the model adequacy and to predict the influence of each parameter on output response Ra. Main effect plots. Interaction plots. 3D surface plots, and Contour plots are established. The investigation reveals that output response (Ra) is predominantly affected by feed rate and progressive feed machining (PFM) yields better surface finish than the conventional constant feed machining (CFM) for the end milling. © 2022 Lavoisier. All rights reserved.