Ashish Garg
IIT Kharagpur ashish.gargnitt@gmail.com
B.Tech in Production & Industrial Engineering in year 2011 from
University College of Engineering, Kota, Rajasthan. M.Tech from
the department of Industrial Engineering & Management in 2014
from NIT,Tirchy. Currently pursuing PhD. in Uncertainty Modeling.
Education
Indian Institute of Technology, Kharagpur, West Bengal
Doctor of Philosophy (PhD)
Industrial and Systems Engineering
July 2016 - Ongoing
National Institute of Technology, Tiruchirappalli, Tamilnadu
Master of Technology (MTech)
Industrial Engineering & Management
July 2012 - June 2014
Rajasthan Technical University, Kota, Rajasthan
University college of engineering
Bachelor of Technology (BTech.)
Production and Industrial Engineering
July 2007 - May Ongoing
Research
Research Area
- Uncertainty Modeling in risk assessment
Research Interest
Publications
2022
- Dhalmahapatra, K., Garg, A., Singh, K., Xavier, N. F., & Maiti, J. (2022). An integrated RFUCOM–RTOPSIS approach for failure modes and effects analysis: A case of manufacturing industry. Reliability Engineering & System Safety, 221, 108333.
- Gupta, A. K., Pardheev, C. G. V. S., Choudhuri, S., Das, S., Garg, A., & Maiti, J. (2022). A novel classification approach based on context connotative network (CCNet): A case of construction site accidents. Expert Systems with Applications, 202, 117281.
- Garg, A., Maiti, J., & Kumar, A. (2022). Granulized Z-OWA aggregation operator and its application in fuzzy risk assessment. International Journal of Intelligent Systems, 37(2), 1479-1508.
- Das, S., Garg, A., Khorania, Y., & Maiti, J. (2022). Dual hesitant Z-number (DHZN), correlated distance, and risk quantification. International Journal of Intelligent Systems, 37(1), 625-660.
2021
- Das, S., Garg, A., Maiti, J., Krishna, O. B., Thakkar, J. J., & Gangwar, R. K. (2021). A comprehensive methodology for quantification of Bow-tie under type II fuzzy data. Applied Soft Computing, 103, 107148.
2020
- Garg, A., Das, S., Maiti, J., & Pal, S. K. (2020). Granulized Z-VIKOR model for failure mode and effect analysis. IEEE Transactions on Fuzzy Systems.
2019
- Das, S., Garg, A., Pal, S. K., & Maiti, J. (2019). A weighted similarity measure between Z-numbers and bow-tie quantification. IEEE Transactions on Fuzzy Systems, 28(9), 2131-2142.
2015