Digital Manufacturing and Design

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Digital Manufacturing and Design

Publications

[Google Scholar]

Work In Progress:

  1. Ko, H.*, Kim, J., Yan, L., Shin, D., Yang, Z., Oh., Y., “Spatial-temporal Modeling using Deep Learning for Real-time Monitoring of Additive Manufacturing,” Journal of Manufacturing Science and Engineering, Under Development.
  2. Safdar, M., Xie, J., Ko, H., Lu, Y., Lamouche, G., Zhao, Y. F.*, “Transferability Analysis of Data-driven Additive Manufacturing Knowledge: A Case Study Between Powder Bed Fusion and Directed Energy Deposition,” Journal of Computing and Information Science in Engineering, Invited, Submitted.
  3. Yang*, Z., Kim, J., Lu, Y., Jones, A., Witherell, P., Ho, Y., Ko, H., “Enhancing Part Quality Management Using an Extended Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing,” Journal of Computing and Information Science in Engineering, Invited, Submitted.

Journals:

  1. Fonseca, N., Thummalapalli, S. V., Jambhulkar, S., Ravichandran, D., Zhu, Y., Patil, D., Thippanna, V., Ramanathan, A., Xu, W., Guo, S., Ko, H., Kannan, A. M., Nian, Q., Asadi, A., Guillaume, M., Anna, D., Hassan, M. K., AliAl-Maadeee, M. A., El-Dessouky, H. M., Stan, F., Song, K.*, (2023) “3D Printing-enabled Design and Manufacturing Strategies for Batteries: A Review”, Small, Accepted.
  2. Guo, S.*, Ko, H., Wang, A. (2023), “Applications and Prospects of Machine Learning for Aerosol Jet Printing: A Review“, IISE Transactions, DOI: 10.1080/24725854.2023.2223620
  3. Kim, J., Yang, Z., Ko, H., Choi, J., Cho, H., Lu, Y.*, (2023) “Deep Learning-based Data Registration for Melt Pool Monitoring of Laser Powder Bed Fusion,” Journal of Manufacturing Systems, Vol. 68, pp. 117-129, DOI: 10.1016/j.jmsy.2023.03.006.
  4. Ko, H.*, Yang, Z., Ndiaye, N. Y., Witherell, P., Lu, Y., (2023) “A Framework Driven by Physics-guided Machine Learning for Process-structure-property Causal Analytics in Additive Manufacturing,” Journal of Manufacturing Systems, Vol. 67, 2023, pp, 213-228, ISSN 0278-6125. https://doi.org/10.1016/j.jmsy.2022.09.010.
  5. Feng, S.*, Moges, T., Park, H., Yakout, M., Jones, A., Ko, H., Witherell, P. (2022). “Functional Requirements of Software Tools for Laser-based Powder Bed Fusion Additive Manufacturing for Metals,” ASME. J. Comput. Inf. Sci. Eng. June 2023; 23(3): 031005. https://doi.org/10.1115/1.4054933
  6. Park, H., Ko, H., Lee, Y.T., Feng, S., Witherell, P., Cho, H.* (2021), “Collaborative Knowledge Management to Identify Data Analytics Opportunities in Additive Manufacturing,” Journal of Intelligent Manufacturing, https://doi.org/10.1007/s10845-021-01811-1.
  7. Oh, Y., Ko, H., Sprock, T., Bernstein, W. Z., Kwon, S.* (2021), “Part Decomposition and Evaluation Based on Standard Design Guidelines for Additive Manufacturability and Assemblability,” Additive Manufacturing, 37, p.101702. [Video]
  8. Ko, H.*, Witherell, P., Lu, Y., Kim, S., Rosen, D. W. (2021), “Machine Learning and Knowledge Graph Based Design Rule Construction for Additive Manufacturing,” Additive Manufacturing, 37, p.101620.
  9. Kim, S.*, Rosen, D. W., Witherell, P., Ko, H. (2019), “A Design for Additive Manufacturing Ontology to Support Manufacturability Analysis,” Journal of Computing and Information Science in Engineering, Vol. 19, No. 4, pp. 041014-041014-10.
  10. Ko, H., Moon, S. K.*, Otto, N. K. (2015), “Design Knowledge Representation to Support Personalised Additive Manufacturing,” Virtual and Physical Prototyping, Vol. 10, No. 4, pp.217-226.
  11. Ko, H., Moon, S. K.*, Hwang, J. (2015), “Design for Additive Manufacturing in Customized Products,” International Journal of Precision Engineering and Manufacturing, Vol. 16, No. 11, pp. 2369-2375 (2017 IJPEM Highly Commended Paper Award).

Books:

  1. Kitt, A.*, Ko, H., “Data Analytics and Machine Learning in Metal Additive Manufacturing: Challenges, Segmentations, and Applications,” ASM Handbooks, ASM International: The American Society for Metals, In press.

Conference Proceedings:

  1. Safdar, M., Xie, J., Ko, H., Lu, Y., Lamouche, G., Zhao, Y. F.*, “Transferability Analysis of Data-driven Additive Manufacturing Knowledge: A Case Study Between Powder Bed Fusion and Directed Energy Deposition,” ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Boston MA, USA. August 20 – 23. Accepted.
  2. Yang, Z.*, Kim, J., Lu, Y., Jones, A., Witherell, P., Ho, Y., Ko, H., “Enhancing Part Quality Management Using an Extended Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing,” ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Boston MA, USA. August 20 – 23. Accepted (ASME CIE Best SEIKM TC Paper Award 2023).
  3. Ko, H*, Kim, J, Lu, Y, Shin, D, Yang, Z, & Oh, Y. “Spatial-Temporal Modeling Using Deep Learning for Real-Time Monitoring of Additive Manufacturing,” ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2: 42nd Computers and Information in Engineering Conference, St. Louis, Missouri, USA. August 14–17, 2022. V002T02A019. ASME. https://doi.org/10.1115/DETC2022-91021
  4. Monnier, L*. & Ko. H., “HDF5 Hierarchies for Additive Manufacturing Digital Representations and Enhanced Analytics,” 33rd Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference, Austin, Texas, USA, Jul. 25-27, 2022.
  5. Gibbons, D. W.* and Ko, H. “Configuration Control for Additive Manufacturing Digital Twins,” 32nd Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference, Austin, Texas, USA, Aug. 2-4, 2021.
  6. Milaat, F. A.*, Yang, Z., Ko, H., Jones, A. T., “Prediction of Melt Pool Geometry using Deep Neural Networks,” ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE2021), August 17-20. [Video]
  7. Oh, J., H. Ko, and Kwon, S.*, “Optimization of Part Decomposition for Efficient 3D Printing,” 2020 Korean Society of Mechanical Engineers (KSME 2020) Fall/Spring Online Conference, Dec. 20, 2020. (In Korean) (Best Paper Award)
  8. Park, H., Ko, H., Lee, Y. T., Cho, H.*, Witherell, P., “A Framework for Identifying and Prioritizing Data Analytics Opportunities in Additive Manufacturing,” 2019 IEEE International Conference on Big Data, Los Angeles, CA, USA, Dec. 9-12, 2019.
  9. Ko, H.*, Lu, Y., Witherell, P., and Ndiaye, N. Y., “Machine Learning based Continuous Knowledge Engineering for Additive Manufacturing,” 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), Vancouver, BC, Canada, Aug. 22-26, 2019 (Nominated as Best Student Paper).
  10. Kim, S.*, Rosen, D. W., Witherell, P., and Ko, H., “A Design for Additive Manufacturing Ontology to Support Manufacturabilty Analysis,” ASME 2018 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Quebec City, Quebec, Canada, Aug. 26-29, 2018.
  11. Kim, S.*, Rosen, D. W., Witherell, P., and Ko, H., “Linking Part Design to Process Planning by Design for Additive Manufacturing Ontology,” Proceedings of the 3rd International Conference on Progress in Additive Manufacturing, Singapore, May 14-17, 2018.
  12. Ko, H., Moon, S. K.*, “Contradicting Functions with Affordances in Design for Additive Manufacturing,” ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Cleveland, Ohio, USA, Aug. 6-9, 2017, Paper No. DETC2017-68157, 2017.
  13. Ko, H., Moon, S. K.*, Wood, K. L., Oh, H. S., “An Integration of Function- and Affordance-based Methods for Product-service System Utilizing Finite State Automata,” 9th IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bali, Indonesia, Dec. 4-7, 2016.
  14. Moon, S. K., Tan, Y. E., Ko, H., Chua, Z. Y., Ngo, T. H., Hwang, J. H., and Baek., J. W.*, “A Customized 3D Printed Sensor Development Framework for Component Condition Monitoring,” The 18th International Conference on Industrial Engineering (IJIE2016), Seoul, Korea, Oct. 10-12, 2016.
  15. Ko, H., Sacco, E., Chua, Z. Y., Moon, S. K.*, and Otto, K., “User-centered Design for Additive Manufacturing as a Customization Strategy,” 2nd International Conference on Progress in Additive Manufacturing (Pro-AM), Singapore, May 16-19, 2016.
  16. Ko, H., Lee, S. W., Shin, D. M., and Moon, S. K.*, “A Formal Model of Human Interactions for Service Ecosystem Design,” ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Buffalo, New York, USA, Aug. 17-20, Paper No. DETC2014-34839, 2014.
  17. Ko, H., Moon, S. K.*, and Hwang, J., “Design for Additive Manufacturing in Customized Products,” International Symposium on Green Manufacturing and Applications, Busan, South Korea, Jun. 24-28, 2014.
  18. Ko, H., Moon, S. K.*, and Otto, K., “Customization Design Knowledge Representation to Support Additive Manufacturing,” 1st International Conference on Progress in Additive Manufacturing (Pro-AM), Singapore, May 26-28, 2014.
  19. Ko, H. and Shin, D. M.*, “s-Scape: a Service Prototype Testing Space for Innovation of Service Quality Improvement,” 2011 IIE Asian Conference AIIE, Jun. 10-12, 2011, Shanghai, China.
  20. Ko, H. and Shin, D.*, “Formal Modeling of Quality-measurable Service Systems using Affordance-based Finite State Automata,” Korean Institute of Industrial Engineers, Seoul, South Korea, Nov. 5, 2011 (In Korean).