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Faculty & Staff
Home / Faculty & Staff / Faculty / Mohammed Shafae
  • shafae1@arizona.edu
    520.621.0525

    Engineering 317

    Full details at profiles.arizona.edu

Mohammed Shafae

  • Assistant Professor of Systems and Industrial Engineering

Degrees

  • Ph.D. Industrial and Systems Engineering
    • Virginia Tech, Blacksburg, Virginia, United States
    • Advancing the Utility of Manufacturing Data for Modeling, Monitoring, and Securing Machining Processes
  • M.S. Industrial and Systems Engineering
    • Virginia Tech, Blacksburg, Virginia, United States
  • M.S. Production Engineering
    • Alexandria University, Alexandria, Egypt
    • Simulation based Performance Evaluation and Enhancement in Call Centers
  • B.S. Production Engineering
    • Alexandria University, Alexandria, Egypt

Work Experience

  • The University of Arizona (2018 - Ongoing)

Interests

Research

Cyber-Physical Systems Security; Smart Manufacturing Systems; Statistical Process Monitoring; Manufacturing Process Data Analytics (Modeling, Monitoring, and Diagnosis); Advanced Metrology Systems Data Driven Quality Control

Selected Publications

Journals/Publications

  • Budinoff, H. D., & Shafae, M. (2022). Connecting part geometry and cost for metal powder bed fusion. The International Journal of Advanced Manufacturing Technology, 121(9), 6125-6136.
  • Dastoorian, R., Wells, L., & Shafae, M. (2022). Assessing the performance of control charts for detecting previously unexplored shift types in high density spatial data. Quality Engineering, 34(1), 125-141.
  • Rahman, M. H., & Shafae, M. (2022). Physics-based detection of cyber-attacks in manufacturing systems: A machining case study. Journal of Manufacturing Systems.
  • Budinoff, H. D., Bushra, J., & Shafae, M. (2021). Community-driven PPE production using additive manufacturing during the COVID-19 pandemic: Survey and lessons learned. Journal of Manufacturing Systems, 60, 799-810.
  • Shafae, M. S., Wells, L. J., & Camelio, J. A. (2021). Modeling in-process machining data using spatial point cloud vs. time series data structures. Procedia Manufacturing, 53, 44-51.
  • Shafae, M. S., Wells, L. J., & Purdy, G. T. (2019). Defending against product-oriented cyber-physical attacks on machining systems. The International Journal of Advanced Manufacturing Technology, 1-21.
  • Wells, L. J., Shafae, M. S., & Camelio, J. A. (2016). Automated Surface Defect Detection Using High-Density Data. Journal of Manufacturing Science and Engineering, 138(7), 071001-071001-10.
  • Shafae, M. S., Dickinson, R. M., Woodall, W. H., & Camelio, J. A. (2015). Cumulative Sum Control Charts for Monitoring Weibull-distributed Time Between Events. Quality and Reliability Engineering International, 31(5), 839-849.

Proceedings Publications

  • Wells, L. J., Shafae, M. S., & Camelio, J. A. (2013, 2013). Automated Part Inspection Using 3D Point Clouds. In The ASME 2013 International Manufacturing Science and Engineering Conference.

Awards

  • First Place in the ASCEND Propel Pitch Competition
    • American Institute of Aeronautics and Astronautics (AIAA) ASCEND conference, Fall 2020
  • Virginia Tech Teaching Excellence Award
    • Department of Industrial and Systems Engineering, Virginia Tech, Spring 2017
  • Harold Schneikert Graduate Fellowship
    • Department of Industrial and Systems Engineering, Virginia Tech, Spring 2016
  • David H. Burrows Graduate Fellowship
    • Department of Industrial and Systems Engineering, Virginia Tech, Fall 2015
  • Best Track Paper Award (Modeling and Simulation Track)
    • The Third International Conference 2012 on Industrial Engineering and Operations Management (IEOM), Summer I 2012
  • Prize for Excellence in Senior Design Project
    • Young Innovators Award Program, Cairo, Egypt, Summer I 2009
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The University of Arizona
Department of Systems & Industrial Engineering
1127 E. James E. Rogers Way
P.O. Box 210020
Tucson, AZ 85721-0020
520.621.6551

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