Department: Mechanical Engineering
Intended audience: Industry participants, Faculty
About: Every developed and developing countries working towards digitalization as a major source for growing the economy with the improved productivity and efficiency of manufacturing systems across various domains. With this need and the visualized benefits of digitalization, every manufacturing industries across the world move towards the implementation industry 4.0. The industry 4.0 implementation and its benefit realization lies on the how effectively the gathered data will be used to understand and forecast the operational performances. Based on this information the organization effectively schedule the maintenance activities extend the life of the system with the reduction in downtime. Also all the activities associated with the manufacturing industries digitalized and will be made available to the stakeholders of the organization using a well-connected network. For realization this benefits it is very much essential to have introduce a course which discusses about various sensors, selection of sensors, data acquisition system, data pre-processing methods involves data de-noising and data imputation, signal processing for feature extraction, feature selection, model building for diagnostics and prognostics with decision making models. By keeping this requirement in mind, we have formulated a STTP course on Prognostics and health management of engineering systems to enlighten faculties and various research professionals to take up this topic of research for contributing India’s mission on digitalization.
Session dates: 7-03-2022 to 12-03-2022
Time: 9 AM to 4 PM IST
Click here to download the program calendar
Last date of registration: 04-03-2022
Profile of the Instructor(s)
Name: Prof. N Arunachalam
Profile: N Arunachalam holds a Ph.D. with 14 years of result-driven Research and Development experience from various industries and academic institutions.
He is currently working as an Associate Professor in the Department of Mechanical Engineering at IIT Madras, Chennai since October 2013. During 2011-2013, he worked as a Research Engineer at Global Research centre, General Electric, Bangalore. Prior to that, he worked as Deputy Manager Technology at Global Research centre, Crompton Greaves, Mumbai from 2008-2010. He received a bachelor degree in Mechanical Engineering from the College of Engineering Guindy, Anna University and an M.E degree with a specialization in Manufacturing Engineering from the Madras Institute of Technology, Anna University. He received his PhD in Mechanical Engineering with a specialization on condition monitoring of grinding wheel using multi-sensor fusion for redress life assessment from the Indian Institute of Technology, Madras Chennai in 2010.
His research interests centre on prognostics and health management of machine tools. It considers the application of data mining, machine learning techniques with real-time sensor data for estimating the remaining useful life of any critical components or systems within the machine tools.
He received an expertise award thrice for his contribution to prognostics and health management of gas turbine combustors with GE, Global Research, Bangalore.
He has published more than FIFTY research articles in various International Journals and conferences to his credit.
Eligibility & Fees
Eligibility requirement of participants: B.Tech., M.E/MTECH./MS/PhD, MBA
Maximum number of participants that can be accommodated :
- Faculty – 30
- Student – 20
- Students – 500
- Faculty – 1000
- Industry – 5000
“The registration fee will be refunded for the first 30 faculty participants from AICTE colleges once they attend and complete the training program”.
Click here to download the Sponsorship Certificate format.
Click here to submit your sponsorship certificate and other details.
Criteria: Attending all the sessions and submitting the assignments, if any.