Mr. Akhand Rai

Designation:

Visiting Assistant Professor

Specialization:

Machine Design

Email:

akhand.rai@thapar.edu

Education
• Ph.D. (IIT Roorkee) in Mechanical Engineering (Thesis Submitted).
• M. Tech in Machine Design, IIT-Banaras Hindu University, Varanasi, U.P./ First class (9.0 CGPA)
• B.Tech in Mechanical Engineering/ College of Engineering Roorkee, Roorkee, U.K./ First class (73%)

Experience: Total Experience 3 years
• June 2018- Present, Thapar Institute of Technology, Patiala, Punjab.
• Jan. 2, 2013 - June 19, 2015: Assistant Professor, Jaypee University of Engineering and Technology, Raghogarh, Guna -M.P.
• June 18, 2012 - Nov. 9, 2012: Engineering Development Programmer, GE Aviation, Bangalore, Karnataka


Teaching Interests:
• Strength of Materials
• Vibrations
• Dynamics of Machines
• Kinematics of Machines
• Machine Design


Research Interest:
• Condition monitoring
• Machine learning
• Fault diagnosis
• Fault prognosis
• Vibration analysis
• Signal processing


Publications:
Journals
1. Rai, A., & Upadhyay, S. H. (2017). Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering. Mechanical Systems and Signal Processing, 93, 16–29. Elsevier Publications (I.F. = 4.116)
2. Rai, A., & Upadhyay, S. H. (2017). The use of MD-CUMSUM and NARX neural network for anticipating the remaining useful life of bearings. Measurement, 111, 397-410. Elsevier Publications (I.F. = 2.359);
3. Rai, A., & Upadhyay, S. H. (2018). Intelligent bearing performance degradation assessment and remaining useful life prediction based on self-organising map and support vector regression. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 232(6), 1118-1132. Sage Publications (I.F. = 1.015).
4. Rai, A., & Upadhyay, S. H. (2016). A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings. Tribology International, 96, 289-306. Elsevier Publications (IF = 2.971)
5. Rai, A., & Upadhyay, S. H. (2018). An integrated approach to bearing prognostics based on EEMD-multi feature extraction, Gaussian mixture models and Jensen-Rényi Divergence. Applied Soft Computing, 71, 36-50. Elsevier Publications (I.F. = 3.541).
6. Rai, A., & Upadhyay, S. H. (2018). The application of semi-nonnegative matrix factorization for detection of incipient faults in bearings. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Sage Publications (I.F. = 1.015). [First Revision received].

Conferences

1. Rai, A., & Upadhyay, S. H., “Estimating the performance degradation of bearings based on multiscale-entropy and Support vector data description”, In Proceedings of the National Symposium on Rotor Dynamics, 2017 - NSRD 2017, IIT Patna, India, Dec., 12-13, 2017.
2. Rai, A., & Upadhyay, S. H., “Bearing degradation process prediction based on PCA and regression trees”, In Proceedings of the National Tribology Conference 2016 -NTC 2016, IIT (BHU) Varanasi, India, Dec., 08-10, 2016.
3. Rai, A., & Upadhyay, S. H., "A neural network approach for calculating the remaining useful life of bearings", In Proceedings of 60th Congress of ISTAM, MNIT, Jaipur, Rajasthan, India, Dec. 16-19, 2015.
4. Rai, A., & Upadhyay, S. H., "Evaluation of the performance degradation of rolling element bearings based on a combination of empirical mode decomposition and fuzzy c-means", International Conference and Exhibition on Mechanical & Aerospace Engineering, Orlando, Florida, USA, Oct. 03-04, 2016.
5. Rai, A., & Upadhyay, S. H., "Prognostics of rolling element bearings based on nonlinear autoregressive neural network with exogenous inputs", Conference on Vibrations in Rotating Machinery - VIRM 11, University of Manchester, Manchester, United Kingdom, Sept. 13-15, 2016.


Achievement, Awards and Recognitions:
• Awarded IIT BHU-Varanasi medal for standing first in Mechanical Engineering at the M.Tech Examination 2012.
• Reviewer of various International Journals like Measurement, Mechanism and Machine Theory, Journal of Low Frequency Noise and Vibration control, IEEE transactions on Industrial Electronics

Message to Students & Community
A person is respected by his character not the position he holds. One should always work on shaping his character also while shaping his career.