Academic Profile

Prof Moon received his Ph.D. degree in Industrial Engineering from the Pennsylvania State University in 2008, his M.S. and B.S. degrees in Industrial Engineering from Hanyang University, South Korea, in 1995 and 1992, respectively. He worked as a Senior Research Engineer at the Hyundai Motor Company, South Korea for eight years before embarking on his PhD degree. After completing his doctoral degree, he joined the Department of Mechanical Engineering, Texas A&M University for one year as a postdoctoral research associate. Prior to joining MAE, he served as a Research Associate of Industrial & Manufacturing Engineering at the Pennsylvania State University between October 2009 and March 2011.
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Assoc Prof Moon Seung Ki
Associate Professor, School of Mechanical & Aerospace Engineering
Assistant Chair (Research), School of Mechanical and Aerospace Engineering (MAE)

He is interested in the boundary-spanning research that integrates the knowledge of design, engineering, and economics. His current focuses include applying sciences and economic theory to the design of customized and sustainable products, services and systems, strategic and multidisciplinary design optimization, data mining, advanced modeling and simulation, design for additive manufacturing/3D printing, embedded sensor design for 3D Printing, digital twins, smart factory, and redesign and remanufacturing for green technologies.
 
  • Electric Vehicle Manufacturing

  • Metal 3D Printing In Aerospace Industry
 
  • Zhang, H., Choi, J.P., Moon, S.K., and Ngo, T.H. (2020). A hybrid multi-objective optimization of aerosol jet printing process via response surface methodology. Additive Manufacturing, 33(May), 101096.

  • Sacco, E. and Moon, S.K. (2019). Additive Manufacturing for Space: Status and Promise. International Journal of Advanced Manufacturing Technology, 105(10), 4123-4146.

  • Zhang, H., Moon, S.K., and Ngo, T.H. (2019). Hybrid Machine Learning Method to Determine the Optimal Process Operating Window in Aerosol Jet 3D Printing. ACS Applied Materials and Interfaces, 11(19), 17994-18003.

  • Kim, S. and Moon, S.K. (2019). Eco-Modular Product Architecture Identification and Assessment for Product Recovery. Journal of Intelligent Manufacturing, 30(1), 383-403.

  • Yao, X., Moon, S.K., and Bi, G. (2017). A Hybrid Machine Learning Approach for Additive Manufacturing Design Feature Recommendation. Rapid Prototyping Journal, 23(6), 983-997.