Home > Industrial and Systems Engineering > Akhilesh Kumar
Ph.D., Wayne State University, Detroit, Michigan
Associate Professor
Industrial and Systems Engineering
Dr. Akhilesh Kumar is currently working as an Associate Professor in the Department of Industrial & Systems Engineering at Indian Institute of Technology, Kharagpur. Previously, he worked as a Solution Architect in Consulting Team at JDA Software, Bangalore. He received his B.Tech degree in Manufacturing Engineering from National Institute of Foundry and Forge Technology (India) and Ph.D. degree in Industrial Engineering from Wayne State University (U.S.A.) in the year 2005 and 2011, respectively. He has authored several technical papers. His publications appeared in such journals as International Journal of Production Economics, European Journal of Operational Research, Expert System with Applications, IEEE. Currently, he is working on a consultancy project with Shell on Conditioned Based Maintenance. He is also team lead for IoT in predictive maintenance project with Department of Heavy Industry and Tata Sons. He was part of collaborative research team in US with Ford Motor Company and Delphi Automotive LLP. His teaching interests include non-linear programming, multivariate statistical models, generalized linear models, machine learning and data analytics. He has authored various courses, lectures and workshops on applied machine learning and data analytics at IIT Kharagpur, other premier institutes and companies such as ZS Associates, CDAC, JDA. He has delivered lectures on various topics in companies as TELCON, HAL, McNally Bharat. He also appeared on Marquis Who’s Who in America in 2011 and in World in 2017. Dr. Kumar is also recipient of Faculty Excellence Award 2020.
Multi-Period Green Reverse Logistics Network Design: An Improved Benders-Decomposition-based Heuristic Approach by Reddy K. N., Kumar A. , Choudhary A. , Cheng T. E. European Journal of Operational Research - (Accepted/In-Press)
Effect of Carbon Tax on Reverse Logistics Network Design by Reddy K. R., Kumar A. , Sarkis J. , Tiwari M. K. Computers & Industrial Engineering 139 - (Accepted/In-Press)
Modelling and analysis of sustainable freight transportation by Kumar A., Calzavara M. , Velaga N. , Choudhary A. , Shankar R. International Journal of Production Research 57 6086-6089 (2019)
A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach by De A., Pratap S. , Kumar A. , Tiwari M. K. Annals of Operations Research - (Accepted/In-Press)
Hazard rate models for core return modeling in auto parts remanufacturing by Kumar A., Chinnam R. B., Murat A. International Journal of Production Economics 183 354-361 (2017)
AI-Driven Resilient Semiconductor Supply Chain Scheme for Promotion of Academic and Research Collaboration (SPARC), Apex Committee of SPARC
Digital Twins for Predictive Maintenance of Industrial Rotatory Equipment IIT KHARAGPUR AI4ICPS I HUB FOUNDATION
Digital Manufacturing and Industrial Internet of Things for Enhanced Supply Chain Co-ordination, Quality and Maintenance TATA SONS PRIVATE LIMITED,Department of Heavy Industries (DHI)
Sumit Pal
Area of Research: Predictive Maintainence
Shashi Kumar
Area of Research: Supply Chain
Suraj Gupta
Area of Research: Supply Chain 4.0
Vineet Chauhan
Area of Research: Predictive Maintenance
R Bharathram
Area of Research: Asset Failure Prediction, Predictive Maintenance
Rima Dolai
Area of Research: Supply Chain Optimization
