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Kaushal A Desai
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Automated surface defect detection framework using machine vision and convolutional neural networks
SA Singh, KA Desai
Journal of Intelligent Manufacturing 34 (4), 1995-2011, 2023
912023
Error compensation in flexible end milling of tubular geometries
TC Bera, KA Desai, PVM Rao
Journal of Materials Processing Technology 211 (1), 24-34, 2011
652011
Process geometry modeling with cutter runout for milling of curved surfaces
KA Desai, PK Agarwal, PVM Rao
International Journal of Machine Tools and Manufacture 49 (12-13), 1015-1028, 2009
652009
On cutter deflection surface errors in peripheral milling
KA Desai, PVM Rao
Journal of Materials Processing Technology 212 (11), 2443-2454, 2012
542012
Machine learning-based instantaneous cutting force model for end milling operation
S Vaishnav, A Agarwal, KA Desai
Journal of Intelligent Manufacturing 31, 1353-1366, 2020
462020
Effect of direction of parameterization on cutting forces and surface error in machining curved geometries
KA Desai, PVM Rao
International Journal of Machine Tools and Manufacture 48 (2), 249-259, 2008
332008
Comparative assessment of common pre-trained CNNs for vision-based surface defect detection of machined components
SA Singh, AS Kumar, KA Desai
Expert Systems with Applications 218, 119623, 2023
282023
On milling of thin-walled tubular geometries
TC Bera, KA Desai, PVM Rao
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2010
252010
Modeling of cutting force, tool deflection, and surface error in micro-milling operation
TM Moges, KA Desai, PVM Rao
The International Journal of Advanced Manufacturing Technology 98, 2865-2881, 2018
222018
Importance of bottom and flank edges in force models for flat-end milling operation
A Agarwal, KA Desai
The International Journal of Advanced Manufacturing Technology 107, 1437-1449, 2020
202020
Build orientation optimization for strength enhancement of fdm parts using machine learning based algorithm
M Malviya, K Desai
Comput. Des. Appl 17, 783-796, 2019
152019
Build Orientation Optimization for Strength Enhancement of 3-D Printed Parts Using Machine Learning based Algorithm
KAD Malviya, Manoj
engrXiv, 2019
15*2019
Improved process geometry model with cutter runout and elastic recovery in micro-end milling
TM Moges, KA Desai, PVM Rao
Procedia Manufacturing 5, 478-494, 2016
142016
On modeling of cutting forces in micro-end milling operation
TM Moges, KA Desai, PVM Rao
Machining Science and Technology 21 (4), 562-581, 2017
132017
Predictive framework for cutting force induced cylindricity error estimation in end milling of thin-walled components
A Agarwal, KA Desai
Precision Engineering 66, 209-219, 2020
122020
Tool and workpiece deflection induced flatness errors in milling of thin-walled components
A Agarwal, KA Desai
Procedia CIRP 93, 1411-1416, 2020
122020
Modeling of flatness errors in end milling of thin-walled components
A Agarwal, KA Desai
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2021
102021
Amalgamation of physics-based cutting force model and machine learning approach for end milling operation
A Agarwal, KA Desai
Procedia CIRP 93, 1405-1410, 2020
102020
Machining of curved geometries with constant engagement tool paths
KA Desai, PVM Rao
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2016
102016
NSLNet: An improved deep learning model for steel surface defect classification utilizing small training datasets
V Nath, C Chattopadhyay, KA Desai
Manufacturing Letters 35, 39-42, 2023
92023
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Articles 1–20