Alaa Elwany, Ph.D.

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  • Texas A&M
  • Associate Professor, Industrial & Systems Engineering
  • Mike and Sugar Barnes Career Development Fellowship I, Industrial & Systems Engineering
  • Kincaid Professorship in Undergraduate Teaching Excellence, Texas A&M Engineering
  • Affiliated Faculty, Materials Science & Engineering

Educational Background

  • Ph.D., Industrial & Systems Engineering, Georgia Institute of Technology - 2009

Research Interests

  • Dr. Alaa Elwany's research interests are in the modeling, analysis and control of advanced manufacturing processes and systems, with particular emphasis on metal additive manufacturing.

    His research projects have been supported by federal and industrial sponsors and are focused on:

    • Additive manufacturing of metals
    • Process monitoring and control of additive manufacturing processes
    • Printability assessment of new materials and alloys for additive manufacturing
    • Uncertainty quantification and data analytics for advanced manufacturing
    • Reliability engineering and maintenance optimization

    Elwany is also very active in workforce development through developing, offering and scaling programs to train the next-generation advanced manufacturing workforce.

    Experience

    • Assistant Director for Technology at the Office of Advanced Manufacturing, National Institute of Standards and Technology (NIST), U.S. Department of Commerce (as ASME Foundation Swanson Fellow)
    • Science and Technology Policy Fellow at the U.S. Department of Energy’s Advanced Manufacturing Office (as AAAS Fellow)
    • Research scientist at the Manufacturing Systems Research laboratory (General Motors R&D)
    • Faculty member in Eindhoven University of Technology, the Netherlands 


    Intellectual Property

    • Arinez, J., Elwany, A., Biller, S., Baird Jr, R., and D'arcy. J., "Method and Apparatus for Managing Heat Energy in a Metal Casting Plant" U.S. Patent 9,272,330 , issued March 1, 2016.
    • Megahed, A., Tata, S., Mohamed, M., and Elwany, A., "Monitoring system for metric data." U.S. Patent 10,742,534, issued 11 Aug. 2020..
    • Zhang, B., Asthana, S., Megahed, A., and Elwany, A., “A Method for Predicting Low Frequency Data in IoT Systems,” Patent Pending, August, 2019.
    • Zhang, B., Johnson, L., Seede, R., Arroyave, R., Karaman, I., and Elwany, A., “Methods of Optimizing 3-D Printing Parameters for Metallic Materials,” Patent Pending, June 2022.

Awards & Honors

  • Science and Technology Policy Fellowship, American Association for the Advancement of Science (AAAS), 2022
  • University Professorship in Undergraduate Teaching Excellence, Texas A&M University, 2022
  • George L. Smith International Award for Excellence in Promotion of Industrial Engineering Award, Institute of Industrial & Systems Engineering, 2022
  • Federal Fellow Award, American Society of Mechanical Engineers (ASME), 2021
  • John L. Imhoff Global Excellence Award for Industrial Engineering Education, American Society for Engineering Education (ASEE), 2021
  • Chao & Trigger Young Manufacturing Engineer Award, American Society of Mechanical Engineers (ASME), 2020
  • Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM) Conference Best Paper Award, Institute of Electrical and Electronics Engineers (IEEE), 2020
  • Engineering Genesis Award, Texas A&M Engineering Experiment Station (TEES), 2020
  • Faculty Fellow Award, Texas A&M College of Engineering, 2020
  • CAREER Award – Advanced Manufacturing Program, National Science Foundation, 2019
  • Dean of Engineering Excellence Award – Assistant Professor Level, Texas A&M College of Engineering, 2019
  • Ephrahim Garcia Best Paper Award, American Society of Mechanical Engineers (ASME), 2018
  • Faculty Award, IBM, 2018
  • Montague Center for Teaching Excellence Award, Texas A&M, 2017
  • Engineering Excellence in Teaching Award, Texas A&M College of Engineering, 2017
  • Outstanding Young Manufacturing Engineer, Society of Manufacturing Engineers, 2016
  • Best Track Paper Award (Engineering Management Track), Institute of Industrial and Systems Engineers (IISE), Industrial and Systems Engineering Research Conference (ISERC), 2015
  • Faculty Appreciation Award, Texas A&M Institute for Operations Research and the Management Sciences (INFORMS) Student Chapter, 2015
  • Professor of the Year Award, Texas A&M Institute of Industrial and Systems Engineers IISE Student Chapter, 2014
  • Outstanding Young Investigator Award (VENI), Netherlands Organization for Scientific Research, 2010
  • Manufacturing Scholarship, General Motors, 2008

Selected Publications

  • Zhang, B., Seede, R., Xue, L., Atli, K.C., Zhang, C., Karaman, I., Arroyave, R., and Elwany, A., “An Efficient Framework for Printability Assessment in Laser Powder Bed Fusion Metal Additive Manufacturing  ,” Additive Manufacturing, Vol. 46, 102018, 2021.
  • Seede, R., Shoukr, D., Zhang, B., Whitta, A., Gibbons, S., Flater, P., Elwany, A., Arroyave, R., and Karaman, I., “Optimizing Process Parameters for Ultra-High Strength Martensitic Steel Fabricated using Laser Powder Bed Fusion Additive Manufacturing: Densification, Microstructure, and Mechanical Properties,” Acta Materialia, Vol. 186, 199-214, 2020.
  • Johnson, L., Mahmoudi, M., Zhang, B., Seede, R., Huang, X., Maier, J., Maier, H., Karaman, I., Elwany, A., and Arróyave, R. , “Assessing printability maps in additive manufacturing of metal alloys,” Acta Materialia, Vol. 176, 199-210, 2019.
  • Ma, J., Franco, B., Tapia, G., Karayagiz, K., Johnson, L, Liu, J., Arroyave, R., Karaman, I., Elwany, A., “Spatial Control of Functional Response in 4D-Printed Active Metallic Structures,” Scientific Reports, Vol. 7, Article number: 46707, 2017.
  • Tapia, G. and Elwany, A., “A Review on Process Monitoring and Control in Metal-Based Additive Manufacturing,” American Society of Mechanical Engineers (ASME) Journal of Manufacturing Science and Engineering, Vol. 136, No. 6: 060801, 2014.
  • Elwany, A., Gebraeel, N.Z., and Maillart, L., “Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors”, Operations Research, Vol. 59, No. 3, pp. 684- 695, 2011.
  • Elwany, A. and Gebraeel, N. Z., “Sensor-Driven Prognostic Models for Equipment Replacement and Spare Parts Inventory,” Institute of Industrial and Systems Engineers (IISE) Transactions, Vol. 40, 629-639, 2008.