| A machine learning approach for vibration-based multipoint tool insert health prediction on vertical machining centre (VMC) AD Patange, R Jegadeeshwaran Measurement 173, 108649, 2021 | 94 | 2021 |
| A Bayesian optimized discriminant analysis model for condition monitoring of face milling cutter using vibration datasets NS Bajaj, AD Patange, R Jegadeeshwaran, KA Kulkarni, RS Ghatpande, ... Journal of Nondestructive Evaluation, Diagnostics and Prognostics of …, 2022 | 50 | 2022 |
| Application of bayesian family classifiers for cutting tool inserts health monitoring on CNC milling AD Patange, R Jegadeeshwaran International Journal of Prognostics and Health Management 11 (2), 2020 | 47 | 2020 |
| Milling cutter condition monitoring using machine learning approach AD Patange, R Jegadeeshwaran, NC Dhobale IOP Conference Series: Materials Science and Engineering 624 (1), 012030, 2019 | 47 | 2019 |
| Application of metaheuristic optimization based support vector machine for milling cutter health monitoring NS Bajaj, AD Patange, R Jegadeeshwaran, SS Pardeshi, KA Kulkarni, ... Intelligent Systems with Applications 18, 200196, 2023 | 38 | 2023 |
| Development of 12 channel temperature acquisition system for heat exchanger using max6675 and arduino interface SP Nalavade, AD Patange, CL Prabhune, SS Mulik, MS Shewale Innovative Design, Analysis and Development Practices in Aerospace and …, 2019 | 38 | 2019 |
| Application of machine learning for tool condition monitoring in turning AD Patange, R Jegadeeshwaran, NS Bajaj, AN Khairnar, NA Gavade Sound Vib 56, 127-145, 2022 | 36 | 2022 |
| Augmentation of decision tree model through hyper-parameters tuning for monitoring of cutting tool faults based on vibration signatures AD Patange, SS Pardeshi, R Jegadeeshwaran, A Zarkar, K Verma Journal of Vibration Engineering & Technologies 11 (8), 3759-3777, 2023 | 34 | 2023 |
| Review on tool condition classification in milling: A machine learning approach AD Patange, R Jegadeeshwaran Materials Today: Proceedings 46, 1106-1115, 2021 | 34 | 2021 |
| Prediction and classification of tool wear and its state in sustainable machining of Bohler steel with different machine learning models ME Korkmaz, MK Gupta, M Kuntoğlu, AD Patange, NS Ross, H Yılmaz, ... Measurement 223, 113825, 2023 | 32 | 2023 |
| Comparison of tool wear, surface roughness, cutting forces, tool tip temperature, and chip shape during sustainable turning of bearing steel H Demirpolat, R Binali, AD Patange, SS Pardeshi, S Gnanasekaran Materials 16 (12), 4408, 2023 | 30 | 2023 |
| Deep learning algorithms for tool condition monitoring in milling: A review SS Patil, SS Pardeshi, AD Patange, R Jegadeeshwaran Journal of Physics: Conference Series 1969 (1), 012039, 2021 | 30 | 2021 |
| Improving program outcome attainments using project based learning approach for: UG course-mechatronics AD Patange, AK Bewoor, SP Deshmukh, SS Mulik, SS Pardeshi, ... Journal of Engineering Education Transformations 33 (1), 1-8, 2019 | 30 | 2019 |
| Novel machine health monitoring system MS Shewale, SS Mulik, SP Deshmukh, AD Patange, HB Zambare, ... Proceedings of the 2nd International Conference on Data Engineering and …, 2019 | 29 | 2019 |
| A white-box SVM framework and its swarm-based optimization for supervision of toothed milling cutter through characterization of spindle vibrations TY Deo, AD Patange, SS Pardeshi, R Jegadeeshwaran, AN Khairnar, ... arXiv preprint arXiv:2112.08421, 2021 | 28 | 2021 |
| Design of bagged tree ensemble for carbide coated inserts fault diagnosis HS Khade, AD Patange, SS Pardeshi, R Jegadeeshwaran Materials Today: Proceedings 46, 1283-1289, 2021 | 27 | 2021 |
| Development of Deep belief network for tool faults recognition AP Kale, RM Wahul, AD Patange, R Soman, W Ostachowicz Sensors 23 (4), 1872, 2023 | 26 | 2023 |
| Supervision of carbide tool condition by training of vibration-based statistical model using boosted trees ensemble A Khairnar, A Patange, S Pardeshi, R Jegadeeshwaran International Journal of Performability Engineering 17 (2), 229, 2021 | 25 | 2021 |
| Development and experimental assessment of a fluid flow monitoring system using flow sensor and arduino interface SS Mulik, AD Patange, R Jegadeeshwaran, SS Pardeshi, A Rahegaonkar Innovative Design, Analysis and Development Practices in Aerospace and …, 2021 | 24 | 2021 |
| Data driven cutting tool fault diagnosis system using machine learning approach: A review NR Tambake, BB Deshmukh, AD Patange Journal of Physics: Conference Series 1969 (1), 012049, 2021 | 22 | 2021 |
R JegadeeshwaranVellore Institute of Technology (VIT University), Chennai.Verified email at vit.ac.in
