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Nagesh Tambake | Machine Learning and Computer Aided Design In Mechanical Engineering| Best Researcher Award

Assistant Professor, Walchand Institute of Technology, Solapur, India.

Mr. Nagesh Rajshekhar Tambake is an Assistant Professor and dedicated researcher at Walchand Institute of Technology, Solapur, Maharashtra, India. Specializing in mechanical engineering, his work focuses on machine condition monitoring, vibration analysis, and advanced manufacturing processes. With a strong commitment to innovation, Mr. Tambake integrates machine learning techniques into industrial applications, contributing to advancements in predictive maintenance and fault diagnosis for CNC machinery. He has published numerous high-impact research papers in reputed journals and actively collaborates with esteemed institutions globally, including COEP Technological University, India, and VSB-Technical University of Ostrava, Czech Republic. His expertise spans smart manufacturing and industrial productivity enhancement.

Publication Profile

Google Scholar

Education :

Mr. Tambake holds advanced degrees in mechanical engineering with a focus on manufacturing technologies and data-driven methodologies. He pursued his undergraduate degree at a reputed institution in India, where he gained foundational knowledge in core mechanical engineering principles. For his postgraduate studies, he specialized in advanced manufacturing  processes and machining processes, earning accolades for his academic excellence. His education has been instrumental in shaping his expertise in integrating machine learning and mechanical engineering. Throughout his academic journey, Mr. Tambake demonstrated an inclination toward applied research, particularly in the development of intelligent systems for fault diagnosis and condition monitoring of industrial machinery.

Experience :

With over a decade of academic and research experience, Mr. Tambake has been an integral part of Walchand Institute of Technology as an Assistant Professor. He has mentored numerous undergraduate and postgraduate students while actively leading research projects in machine learning applications for manufacturing processes. His industry-oriented experience includes collaborations with international universities and organizations, where he worked on real-world problems such as vibration analysis and tool health monitoring in CNC machines. His ongoing research initiatives focus on integrating smart systems into mechanical processes, enhancing reliability and efficiency.

Research Focus :

Mr. Tambake’s research centers on machine condition monitoring, fault diagnosis, and predictive maintenance using machine learning techniques. He focuses on vibration signal analysis and the optimization of machining processes to improve industrial productivity. His work addresses challenges in CNC hobbing cutter fault diagnosis, leveraging three-axis vibration data to develop efficient monitoring systems. His interdisciplinary approach integrates mechanical engineering, data science, and advanced analytics to create innovative solutions for smart manufacturing and industrial automation.

Awards:

Elisabetta Ferrara has been recognized for her research excellence, earning accolades such as the prestigious “Cortina International Scientific Award” and the “TAOBUK Da Vinci Award” for her contributions to periodontal and microbiota research. Her achievements include awards at national and international congresses for innovations in dental and healthcare sciences.

 

Publication :

Data Driven Cutting Tool Fault Diagnosis System Using Machine Learning Approach: A Review
Authors: BBDADP Nagesh R Tambake
Journal: Journal of Physics: Conference Series 1969 (012049)
Citations: 24
Year: 2021

Development of a Low-Cost Data Acquisition System and Training of J48 Algorithm for Classifying Faults in Cutting Tool
Authors: N Tambake, B Deshmukh, A Patange
Journal: Materials Today: Proceedings 72, 1061-1067
Citations: 6
Year: 2023

Machine Learning for Monitoring Hobbing Tool Health in CNC Hobbing Machine
Authors: N Tambake, B Deshmukh, S Pardeshi, HA Mahmoud, R Cep, S Salunkhe, …
Journal: Frontiers in Materials 11, 1377941
Citations: 4
Year: 2024

Fault Diagnosis of a CNC Hobbing Cutter through Machine Learning Using Three-Axis Vibration Data
Authors: N Tambake, B Deshmukh, S Pardeshi, S Salunkhe, R Cep, EA Nasr
Journal: Heliyon
Citations: Not available (likely newly published)
Year: 2025

Condition Monitoring of a CNC Hobbing Cutter Using Machine Learning Approach
Authors: N Tambake, B Deshmukh, S Pardeshi, S Salunkhe, R ÄŒep, E Abouel Nasr
Journal: Advances in Mechanical Engineering 16 (9), 16878132241275750
Citations: Not available
Year: 2024

Fatigue Failure of Flange in Screw Conveyor: A Review
Authors: NR Tambake
Journal: International Journal of Innovations in Engineering Research and Technology
Citations: Not available
Year: 2021

Design Analysis and Optimization of Rolling Mill Housing Using CAE
Authors: NR Tambake, KH Jatkar
Journal: Not explicitly provided
Citations: Not available
Year: Unknown

Conclusion :

Given his profound expertise, research impact, and commitment to addressing critical challenges in the manufacturing and engineering sectors, Mr. Tambake is a highly deserving nominee for the Best Researcher Award. His contributions are not only advancing academic knowledge but also significantly improving industrial practices, positioning him as a leader in his field.

Nagesh Tambake | Manufacturing processes| Best Researcher Award

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