Ramabalan S
@egspec.org
Principal
E.G.S. Pillay Engineering College, Nagapattinam
EDUCATION
B.E., M.E., Ph.D.,
RESEARCH INTERESTS
Robotics, CAD?CAM, Optimization
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
K. Govindan, S. Ramabalan, and S. Vishvanathperumal
Springer Science and Business Media LLC
N Ramasubbu and S Ramabalan
Springer Science and Business Media LLC
K Govindan, S Ramabalan, S Vishvanathperumal, and S Chockalingam
Springer Science and Business Media LLC
V. Sathiya, K. Nagalakshmi, J. Jeevamalar, R. Anand Babu, R. Karthi, Ángel Acevedo-Duque, R. Lavanya, and S. Ramabalan
Elsevier BV
Manikandan Kaliyaperumal, Ramabalan Sundaresan, Balu Pandian, and Silambarasan Rajendran
Walter de Gruyter GmbH
Abstract Due to the enormous of fossil fuels and the ensuing increase in automobiles, an unprecedented scenario has arisen with pollution levels that are out of human control. In this study, a fuzzy logic model is developed to predict how well a spark-ignition engine running on gasoline and ethanol mixes would operate. A test engine was operated on pure gasoline and gasoline–ethanol fuel mixtures in a range of ratios at varying engine speeds. In order to estimate outputs such as brake-specific fuel consumption (BSFC), brake thermal efficiency, nitrogen oxides (NOx), hydrocarbon emissions, and carbon monoxide, a fuzzy logic model, a sort of logic model application, has been developed using experimental data. The developed fuzzy logic model’s output was compared to the results of the trials to see how well it performed. The output parameters were indicated, including braking power, thermal, volumetric, and mechanical efficiency. The input parameters were engine speed and ethanol mixes. Regression coefficients were nearly equal for training and testing data. According to the study, a superior method for accurately forecasting engine performance is the fuzzy logic model. To eliminate proportionality signs from equations, regression analysis is used. It is accurate to develop mathematical relations based on dimensional analysis. Based on the root mean square errors, BSFC is a minimum of 6.12 and brake power is a maximum of 8.16; lower than 2% of errors occur on average.
A. Arunkumar, S. Ramabalan, and D. Elayaraja
Computers, Materials and Continua (Tech Science Press)
V. Sathiya, M. Chinnadurai, and S. Ramabalan
Elsevier BV
Ramasubbu Narasimmalu, Ramabalan Sundaresan, and Rajmohan Murugesan
Springer Science and Business Media LLC
Ramasubbu Narasimmalu and Ramabalan Sundaresan
Emerald
Purpose AA8090 aluminum alloy is used in industrial applications for weight reduction purposes. However, its usage is limited due to shortcomings such as low wear resistance. Hence, the purpose of this study is to improve the wear properties of the material. A particle strengthening mechanism was tried to improve the wear properties of materials. Design/methodology/approach AA8090 aluminum alloy composites were prepared by stir casting methods using AA8090, boron carbide (B4C) and aluminum oxide (Al2O3) materials. Totally, four different types of composites were prepared, namely, AA/3Al, AA/1BC-2Al, AA/2BC-1Al and AA/3BC. Wear behavior and mechanical properties of the composites were analyzed by conducting wear test, microhardness test, tensile test and morphological analysis. Findings Results showed that the composite materials showed superior properties compared with AA8090 alloy due to the reinforcing effect of B4C and Al2O3 particles. Further, the AA/3BC composite showed 12.9% and 10.8% enhancement in microhardness and tensile strength, respectively. Further, a minimum wear rate of 0.009 × 10–3 mm3/m was observed for AA/3BC composite. Originality/value This study is original and would add new information to the literature. Further, it solves the problem of low wear resistance issues in AA8090 aluminum alloy materials.
Ramasubbu Narasimmalu and Ramabalan Sundaresan
IOP Publishing
Abstract Al6063 composites are widely used in automobile, aerospace and biomedical industries due to their excellent mechanical properties. Machining of micro channels in composites is difficult for conventional machining process due to presence of hard reinforcement. Materials with base metal. Micro Electrical discharge (μED) milling is popular micromachining technique for machining simple, intricate shapes and microchannels on any conductive material. However, it a slow machining process, the identification of optimum condition has become wide research area in μEDM. The present work aims to study the influence of process variables namely voltage, spindle speed and threshold on machining characteristics of μED milling of Hybrid Metal Matrix Composites (HMMCs). Experimental trials are carried out with copper electrode at different parametric condition. Al6063%-5%B4C-5%ZrSiO4 composite was fabricated using stir casting method and experimental runs were designed using general full factorial method. The significant parameters are identified using Analysis of Variance (ANOVA) and the ideal machining conditions for multi-response are determined using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The morphology of machined surface with best and worst conditions is examined using SEM. Results indicated that the voltage and threshold are the influencing parameters for considered response indicators. Recast layer thickness seems to be low with best machining conditions as compared to worst conditions. Increase in voltage and threshold increases the Material Removal Rate (MRR) and decreases the Electrode Wear Rate (EWR). Surface finish is better when the lower order of capacitance and voltage is used. MRR is increased by 48% with best machining conditions compared to worst machining condition.
N. Godwin Raja Ebenezer, S. Ramabalan, and S. Navaneethasanthakumar
Springer Science and Business Media LLC
S. Ramabalan, V. Sathiya, and M. Chinnadurai
Springer Nature Singapore
S. Ramabalan, K. SenthilKannan, K. Suganya, G. Flora, R. Manikandan, and M. Vimalan
Elsevier BV
S. Velmurugan, K. Sivakumar, and S. Ramabalan
Elsevier BV
N. Godwin Raja Ebenezer, S. Ramabalan, and S. Navaneethasanthakumar
Informa UK Limited
Jayaraj JEEVAMALAR, Sundaresan RAMABALAN, and Jayaraj JANCIRANI
Kaunas University of Technology (KTU)
In order to achieve higher productivity and product quality, the investigation of machining parameters on Electrical Discharge Drilling and surface characteristic analysis are most critical for manufacturing industries. The intention of this article is to assess the impact on performance matrices including Material Removal Rate, and Surface Roughness of input factors of peak current, pulse-on and off duration while drilling with a rotary hollow copper tool on Inconel 718 under Tungsten powder suspended kerosene. Analysis of Variance has been implemented using MINITAB release 18 software to identify the most significant input factors. An Artificial Neural Network was used for validating the experimental results of the drilling process. The additional intention of this research is to discover the significance of influencing input parameters and analyze the quality surface of the workpiece were observed by microscope tests. The experimental results indicated that the peak current and pulse-on period have an effect on the performance of the drilling process considerably.
V. Sathiya, M. Chinnadurai, S. Ramabalan, and Andrea Appolloni
Springer Science and Business Media LLC
P. Anandraj and S. Ramabalan
Computers, Materials and Continua (Tech Science Press)
Ramasubbu Narasimmalu and Ramabalan Sundaresan
Institute of Metals and Technology
Electrode wear and metal removal exhibited nonlinear behavior in the Electrical Discharge Machining (EDM) of Hastelloy B2 plate. Hence, mathematical modeling was used to solve this problem. The hole size, pulse duration, duty cycle, and current were selected as inputs. Squareness and taper angle were considered as responses. Therefore, the Modified-Additive Ratio Assessment Method (M-ARAS) based Adaptive Neuro Fuzzy Inference System (ANFIS) method was used to find the optimum EDM process parameters. The overall analysis showed that the M-ARAS-based ANFIS algorithm provided a good fit for optimization of the process parameters and could be used for further multi-objective optimization problems.
S. Ramabalan, V. Sathiya, and M. Chinnadurai
Springer Singapore
S. Ramabalan, S. Mahalakshmi, and M. Chinnadurai
Springer Singapore
Jayaraj JEEVAMALAR, Sundaresan RAMABALAN, and Chinnamuthu SENTHILKUMAR
Kaunas University of Technology (KTU)
Modelling is used for correlating the relationship between the input process parameters and the output responses during the machining process. To characterize real-world systems of considerable complexity, an Artificial Neural Network (ANN) model is regularly used to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of the ANN modeling process for Electrical Discharge Drilling of Inconel 718 superalloy and hollow tubular copper as tool electrode. The most important process parameters in this work are peak current, pulse on time and pulse off time with machining performances of material removal rate and surface roughness. The experiments were performed by L20 Orthogonal Array. In such conditions, an Artificial Neural Network model is developed using MATLAB programming on the Feed Forward Back Propagation technique was used to predict the responses. The experimental data were separated into three parts to train, test the network and validate the model. The developed model has been confirmed experimentally for training and testing in considering the number of iterations and mean square error convergence criteria. The developed model results are to approximate the responses fairly exactly. The model has the mean correlation coefficient of 0.96558. Results revealed that the proposed model can be used for the prediction of the complex EDM drilling process.
Singaravelu Chockalingam, S. Ramabalan, and K. Govindan
Elsevier BV
Abstract Chatter is a self-excited vibration that occurs during any machining process. Chatter sensations were stir up during boring process due to cantilever shape of boring bars. These vibrations amplify the temperature of the boring tool additional which ultimately increases the tool wear. In this project a proper damping material is fixed on the boring bar, used to measure temperature for various positioning of the damper, different levels of speed, feed rate and depth of cut in the machining test. The main intention of the work is to design damped tool holder for existing machine tools with low cost. The enhancement of the damping ability of boring tool and control the chatter were attempted using different types of dampers such as Copper and Brass. These materials comprise high density and so that inertia mass of the boring tool is improved to suppress the chatter of boring operations. Modal analysis of boring bar is done by using ANSYS software in this current investigation. Modal examination is used to determine the natural frequencies and mode shapes of a structure. The natural frequencies and mode shapes are incredibly important factor in the design of a structure for vibrant loading conditions.
N. Godwin Raja Ebenezer, S. Ramabalan, and S. Navaneethasanthakumar
Springer Science and Business Media LLC
Gears are used to transmit mechanical power in systems such as automotives, automation and machine tools. The demand for lighter and optimally designed gears is high in power transmission systems, as they save material, energy and also considerably influence performance. Hence, in this paper, a bevel gear pair is optimized. The problem consists of a non linear objective function, four design variables and eight inequality constraints. The objective is to minimize the volume of the gear. The design variables are: number of teeth, module, face width and diameter of the shaft, which is a new addition. Apart from considering regular mechanical constraints, six other additional critical constraints on contact ratio, load carrying capacity, power loss, root not cut, no involute interference and line of action are also included. Nature inspired algorithms, namely, simulated annealing, fire fly, cuckoo search and fmincon solver are employed in MATLAB environment. Results of simulation are analysed, compared and validated with literature.