K.Anton Savio Lewise
@karunya.edu
Assistant Professor
Karunya Institute of Technology & Sciences
EDUCATION
Phd in Aeronautical Engineering (Aera of Interest: Aerospace Materials)
ME in Aeronautical Engineering
BE in Aeronautical Engineering
RESEARCH INTERESTS
Aerospace Materials, Composite Materials, Material Characterization, Friction stir welding, Manufacturing Technology
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
K Eqbert, K Anton Savio Lewise, N Jeyaprakash, Ibrahim A Alnaser, and Sundara Subramanian Karuppasamy
IOP Publishing
Abstract Friction Stir Spot Welding (FSSW) belongs to the category of solid-state welding process and is most suitable for joining lightweight materials. For obtaining highly efficient spot welds with good structural integrity, there is a need to optimize the process parameters involved in the FSSW process. This work is aimed at optimizing the process parameters for the spot welds fabricated in the AA2014-AA7075 alloy via the FSSW process. With the aid of Box-Behnken design, the sequence of experimental trials was performed at three levels along with the results obtained from the ANOVA methodology. The empirical modeling was established via Response Surface Methodology (RSM) and compared with the experimental trials. Results showed that the tool rotating speed serves as the most influential parameter followed by the tool shoulder diameter, plunge depth and dwell time. With the effect of response, contour and desirability plots, the optimal process parametric values were found and these values were correlated with the 7th experimental trial which was based on the maximum tensile strength offered by the spot weld. Further, the optical micrograph captured at the weld zone of the 7th trial specimen was rich in equiaxed grains with intermetallic phases. This grain refinement and intermetallic phases contributed to a higher hardness of the spot welds and thus offering maximum tensile strength with good structural integrity.
Ramanan G, Edwin Raja Dhas J, Anton Savio Lewise K, Naveen Kumar Kulandaiyappan, Beena Stanislaus Arputharaj, Parvathy Rajendran, Vijayanandh Raja, and Arunkumar Karuppasamy
Springer Science and Business Media LLC
M. Sunil Kumar Hemanth, J. Edwin Raja Dhas, and K. Anton Savio Lewise
Springer Science and Business Media LLC
P. Vijayaparkavan, K. Anton Savio Lewise, and R. Ajith Raj
Pleiades Publishing Ltd
A. K. Darwins, M. Satheesh, J. Edwin Raja Dhas, K. Anton Savio Lewise, R. Ajith Raj, and B. Manideep
Springer Science and Business Media LLC
A. K. Darwins, K. Anton Savio Lewise, Mohammed Fahad, M. Satheesh, J. Edwin Raja Dhas, and A. Vivek Anand
Springer Science and Business Media LLC
Jeyaprakash Natarajan and K. Anton Savio Lewise
CRC Press
K. Anton Savio Lewise, J. Edwin Raja Dhas, and M. Satheesh
CRC Press
V S Akash, J Edwin Raja Dhas, K Anton Savio Lewise, and C P Jesuthanam
IOP Publishing
Abstract Surface of a machined component is a significant factor in evaluating the quality. Quality of machined surface plays an important role in predicting the fatigue strength, corrosion resistance and creep life. It is tedious to realize the process parameters behind the surface roughness formation mechanism. Hence development of models, which can predict a wide variety of process parameters to assist the real time factory floor decision making process is challenging. This article addresses the development of particle swarm optimization-based support vector regression model for machining quality prediction. Data set for training and testing the proposed model is obtained from experimental observations supported with regression results with spindle speed, feed rate, depth of cut and vibration as input parameters and surface roughness as output parameter. K-fold cross validation is applied for training and testing the proposed model. Predicted results from swarm-based support vector regression model are validated with fuzzy and support vector regression models. Analysis of Variance is done using the results from signal to noise ratio computations for identifying the influence of controllable factors involved. The analysis from ANOVA indicates that spindle speed and feed rate play significant roles in determining the surface quality of the machined component. Test results reveal that the developed model can be used successfully for machinability data selection.
Sampath Boopathi, K. Anton Savio Lewise, J. Edwin Raja Dhas, and M. Satheesh
CRC Press
R. Mukesh, Sarat C. Dass, M. Vijay, G. Ramanan, K. Anton Savio Lewise, and A. Vivek Anand
Informa UK Limited
K. Anton Savio Lewise, J. Edwin Raja Dhas, R. Pandiyarajan, and S. Sabarish
Elsevier BV
J. Edwin Raja Dhas, K. Anton Savio Lewise, and M. Satyanarayana Gupta
AIP Publishing
K. Anton Savio Lewise, J. Edwin Raja Dhas, and R. Pandiyarajan
AIP Publishing
K. Anton Savio Lewise, J. Edwin Raja Dhas, and R. Pandiyarajan
Springer Nature Singapore
Sampath Boopathi, G. Venkatesan, and K. Anton Savio Lewise
Springer Nature Singapore
M.A. Unnikrishnan, J. Edwin Raja Dhas, K. Anton Savio Lewise, John C. Varghese, and M. Ganesh
Elsevier BV
Jeyachandran Vivek, P Veerathevar Arul Kumar, Kuzhanthai Anton Savio Lewise, and Viruthachaam Velmurugan
Springer Science and Business Media LLC
J. Vivek, T. Maridurai, K. Anton Savio Lewise, R. Pandiyarajan, and K. Chandrasekaran
Springer Science and Business Media LLC
J. Edwin Raja Dhas, K. Anton Savio Lewise, K. Naveen Kumar, Vijayanandh Raja, Hussein A. Z. AL-bonsrulah, Hijaz Ahmad, Shao-Wen Yao, and Mohammed Al-Bahrani
Frontiers Media SA
Lightweight materials are being employed in aeronautical and automobile industries for high strength, lower weight, and energy consumption. Attention is needed to control pollution through the usage of harmful synthetic composites globally. In this work, coconut shell nanofillers are reinforced in the development of various palm fiber (leaf stalk, leaf sheath, leaf-spine, and fruit) composites using the hand layup technique. Mechanical and morphological effects of the addition of nano-coconut-shell-powder to the composites are addressed. The palm fibers are sandwiched within the glass fiber to improve the strength of composites. The addition of coconut shell nanoparticles in the composites improves the tensile, flexural, impact, hardness, and water absorption characteristics. SEM image observations on the composite indicate the buildup of nanomodified matrix residues around the fiber bundle. The adhesive property of the composite is confirmed by Fourier transform infrared spectroscopy examination, which reveals the presence of one additional alcohol/phenol OH stretch, one less alkyl CH stretch, and aromatic CH bending functional groups. The inclusion of palm fibers during the fabrication of composites facilitated the pushing of curves to higher temperatures with considerable degradation temperatures, thereby increasing thermal stability and making them suitable for thermal applications. Development of the eco-composite changes environmental impact factors aiming sustainability.
K. Anton Savio Lewise and J. Edwin Raja Dhas
Informa UK Limited
The novelty of the present work is the investigation of friction stir spot welding between AA2024 and AA7075 aluminum plates performed by Box-Behnken technique of response surface methodology. The ...
K. Anton Savio Lewise, J. Edwin Raja Dhas, and R. Pandiyarajan
Informa UK Limited
ABSTRACT The present novel work is the investigation of dissimilar AA2024/AA7075 aluminium alloy friction stir spot welded joint. The input welding process parameters were analysed to determine the most influencing process parameter on mechanical and morphological properties of the weld. The welding process and input parameters were optimised by Box–Behnken design and response surface methodology. Among the enhanced mechanical characteristics, tensile shear force was observed to be enhanced to maximum being influenced by the rotational speed of the friction stir tool. Optimised performance characteristics were obtained by using desirability approach, and the resulting optimal input parameters were: Tool plunge depth = 3.3 mm, rotational speed of tool = 2000 rpm and Tool dwell time = 40 s. The optimal tensile shear force and hardness obtained were 4.18 kN and 134 HV, respectively, which were validated by comparing the experimental and predicted output response. The elemental composition and morphology of materials were tcharacterised by X-ray diffraction – scanning electron microscope, while the mechanical properties were analysed by tensile and Vickers hardness testing.
K Anton Savio Lewise, Edwin Raja Dhas J, and R. Pandiyarajan
Informa UK Limited
ABSTRACT The present study was the result of an investigation of friction stir spot (FSS)-welded similar aluminum alloys 2024-T3 joint and 7075-T6 joint and dissimilar aluminum alloy 2024-T3-7075-T6 joint. The mechanical, microstructural, and tribological behavior of the different FSS-welded specimens were characterized for effects of influence of the input process parameters. The dissimilar FSS-welded 2024-T3-7075-T6 joint exhibited uniform distribution in material flow in the welded zone. A marked improvement in microhardness was noted when it increased from 30 to 40.94 HV, while an increase in tensile strength from 128 to 166.3 MPa was observed for the FSS-welded dissimilar 2024-T3-7075-T6 joint alloy. The dissimilar alloy weld joint exhibited improved microhardness and tensile properties than their counterparts in both variants of the similar FSS-welded specimens, with a 35.6% increase in microhardness for the bottom plate in welded nugget zone and improvement of 13.14% and 5.54% in ultimate tensile strength when compared to aluminum alloy 2024-T3 joint and 7075-T6 joint under same welding parameters.