Uma Maheshwera Reddy Paturi

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Prof. N. S. ReddyProfessor of Materials Science and Engineering, Gyeongsang National University,Zweryfikowany adres z gnu.ac.kr
Suresh Kumar Reddy NaralaProfessor of Mechanical Engineering, BITS-Pilani Hyderabad CampusZweryfikowany adres z hyderabad.bits-pilani.ac.in
Suryapavan CherukuJ. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College StationZweryfikowany adres z tamu.edu
Sai teja PalakurthyZweryfikowany adres z tamu.edu
Nitin KotkundeAssociate Professor, Mechanical Engineering Department, BITS-Pilani Hyderabad CampusZweryfikowany adres z hyderabad.bits-pilani.ac.in
Rajdeep Singh PundirStudent of Mechanical Engineering, BITS Pilani Hyderabad CampusZweryfikowany adres z hyderabad.bits-pilani.ac.in
Dr. Rakesh Kumar GundaMechanical EngineeringZweryfikowany adres z hyderabad.bits-pilani.ac.in
Dr. Bhumeshwar PatleProfessor MIT Art, Design and Technology University, PuneZweryfikowany adres z mituniversity.edu.in
Bharat B. PanigrahiMaterials Science and Metallurgical Engg, Indian Institute of Technology HyderabadZweryfikowany adres z msme.iith.ac.in
hyo-jun ahngyeongsang universityZweryfikowany adres z gnu.kr
Jaekyung sungGyeongsang National UniversityZweryfikowany adres z gnu.ac.kr
S.D.S. Abhiram KalvakolanuStudent at Concordia UniversityZweryfikowany adres z live.concordia.ca
Naveen Kumar1Zweryfikowany adres z cvr.ac.in
Methuku SumanthDepartment of Mechanical Engineering, CVR College of EngineeringZweryfikowany adres z cvr.ac.in
Professor David Abimbola FadareUniversity of IbadanZweryfikowany adres z ui.edu.ng
Hyokyung SungAssociate ProfessorZweryfikowany adres z kookmin.ac.kr
Jae-keun HongKIMSZweryfikowany adres z kims.re.kr
Neeraj K JhaQualcommZweryfikowany adres z qti.qualcomm.com
Kalyan PamidimukkalaTexas A&M University, College StationZweryfikowany adres z tamu.edu
Nalband Sai Kiran CharyStudent at Texas A&M University, College StationZweryfikowany adres z tamu.edu

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Uma Maheshwera Reddy Paturi

CVR College of Engineering, Hyderabad, Telangana, India

Zweryfikowany adres z cvr.ac.in

Neural networks Machine learning Modeling&Simulation Manufacturing Tribology


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
Measurement and analysis of surface roughness in WS2 solid lubricant assisted minimum quantity lubrication (MQL) turning of Inconel 718 UMR Paturi, YR Maddu, RR Maruri, SKR Narala Procedia Cirp 40, 138-143, 2016	121	2016
Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review UMR Paturi, S Cheruku Materials Today: Proceedings 38, 2392-2401, 2021	81	2021
Constitutive flow stress formulation, model validation and FE cutting simulation for AA7075-T6 aluminum alloy UMR Paturi, SKR Narala, RS Pundir Materials Science and Engineering: A 605, 176-185, 2014	77	2014
The role of machine learning in tribology: A systematic review UMR Paturi, ST Palakurthy, NS Reddy Archives of Computational Methods in Engineering 30 (2), 1345-1397, 2023	72	2023
Application of regression and artificial neural network analysis in modelling of surface roughness in hard turning of AISI 52100 steel UMR Paturi, H Devarasetti, SKR Narala Materials Today: Proceedings 5 (2), 4766-4777, 2018	72	2018
The role of artificial neural networks in prediction of mechanical and tribological properties of composites—a comprehensive review UMR Paturi, S Cheruku, NS Reddy Archives of Computational Methods in Engineering 29 (5), 3109-3149, 2022	60	2022
Machine learning and statistical approach in modeling and optimization of surface roughness in wire electrical discharge machining UMR Paturi, S Cheruku, VPK Pasunuri, S Salike, NS Reddy, S Cheruku Machine Learning with Applications 6, 100099, 2021	55	2021
Process modeling and parameter optimization of surface coatings using artificial neural networks (ANNs): State-of-the-art review UMR Paturi, S Cheruku, SR Geereddy Materials Today: Proceedings 38, 2764-2774, 2021	40	2021
Progress of machinability on the machining of Inconel 718: A comprehensive review on the perception of cleaner machining UMR Paturi, NS Reddy Cleaner Engineering and Technology 5, 100323, 2021	36	2021
Estimation of coating thickness in electrostatic spray deposition by machine learning and response surface methodology UMR Paturi, NS Reddy, S Cheruku, SKR Narala, KK Cho, MM Reddy Surface and Coatings Technology 422, 127559, 2021	35	2021
Artificial neural networks modeling for lead removal from aqueous solutions using iron oxide nanocomposites from bio-waste mass PL Narayana, AK Maurya, XS Wang, MR Harsha, O Srikanth, AA Alnuaim, ... Environmental Research 199, 111370, 2021	31	2021
Modeling and optimization of machining parameters for minimizing surface roughness and tool wear during AISI 52100 steel dry turning UMR Paturi, A Yash, ST Palakurthy, NS Reddy Materials Today: Proceedings 50, 1164-1172, 2022	30	2022
Experimental investigation to study the effect of electrostatic micro-solid lubricant–coated carbide tools on machinability parameters in turning UMR Paturi, SKR Narala Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2015	26	2015
Estimation of machinability performance in wire-EDM on titanium alloy using neural networks UMR Paturi, S Cheruku, S Salike, VPK Pasunuri, NS Reddy Materials and Manufacturing Processes 37 (9), 1073-1084, 2022	25	2022
Modeling of surface roughness in wire electrical discharge machining of Inconel 718 using artificial neural network UMR Paturi, H Devarasetti, NS Reddy, N Kotkunde, BK Patle Materials Today: Proceedings 38, 3142-3148, 2021	24	2021
Modeling tensile strength and suture retention of polycaprolactone electrospun nanofibrous scaffolds by artificial neural networks BS Reddy, KH In, BB Panigrahi, UMR Paturi, KK Cho, NS Reddy Materials Today Communications 26, 102115, 2021	21	2021
Silver nanoparticle-based Tween 80 green cutting fluid (AgNP-GCF) assisted MQL machining-An attempt towards eco-friendly machining UMR Paturi, GN Kumar, VS Vamshi Cleaner Engineering and Technology 1, 100025, 2020	19	2020
Finite element simulations of machinability parameters in turning of Inconel 718 UMR Paturi, S Methuku, SS Siripragada, Y Sangishetty, RK Gunda Materials Today: Proceedings 38, 2658-2663, 2021	18	2021
Modeling of tool wear in machining of AISI 52100 steel using artificial neural networks UMR Paturi, S Cheruku, VPK Pasunuri, S Salike Materials Today: Proceedings 38, 2358-2365, 2021	18	2021
Application of artificial neural network and response surface methodology in modeling of surface roughness in WS2 solid lubricant assisted MQL turning of Inconel 718 UMR Paturi, H Devarasetti, DA Fadare, SKR Narala IOP conference series: materials science and engineering 346 (1), 012085, 2018	15	2018

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