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Govind Narayan Sahu

Assistant Professor
Department of Mechanical Engineering
IIT Tirupati
Office: CIF-101
Email: govinds@iittp.ac.in

Welcome to the Smart Manufacturing and Automation Laboratory (SMAL) at IIT Tirupati, where we specialize in researching machine tool dynamics and vibration control. Our lab is dedicated to integrating cutting-edge tools and technologies into manufacturing systems, transforming them into smart solutions. Our approach combines experimental rigor with theoretical insights.

At SMAL, we are passionate about developing new technologies that benefit manufacturing, automotive, aerospace, medical, and society at large. We are committed to sharing knowledge through hands-on training, empowering students and industry professionals to learn, test, and implement emerging technologies.

We are eager to tackle industry challenges and are actively seeking consultancy or sponsored projects. Whether you wish to learn more about our research, join our group, or collaborate with us, please do not hesitate to reach out.

Additionally, we are seeking dedicated and talented individuals to join us as PhD, MS/MTech, and BTech interns. If you are enthusiastic and driven, we invite you to contact me directly at govinds@iittp.ac.in.

Education

Post-Doc
:
Fraunhofer Institute for Machine Tools and Forming Technology (IWU), Germany, 2023
Post-Doc
:
Indian Institute of Technology, Delhi, India, 2022
Ph.D.
:
Indian Institute of Technology, Kanpur, India, 2021
M.Tech
:
Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, India, 2015
B.E.
:
Chhattisgarh Swami Vivekananda Technical University, Bhilai, India, 2013

Past Research Work

  • Machining dynamics
  • Hardware-in-Loop (HIL) simulations
  • Active control of machine tool vibrations
  • Experimental and numerical modal analysis
  • Characterization and control of actuators
  • Virtual instrumentation

Current Research Work

  • Intelligent milling machine
  • Augmented reality for machine tools
  • IoT platform for condition monitoring of machine tools
  • Machine learning for manufacturing systems
  • Automated inspection technologies
  • Miniature wireless accelerometer