Publications

Journal articles, peer-reviewed conference proceedings, conference presentations, and patents

* indicates co-first author. † indicates corresponding author.

Journal Articles

  1. Magana, A.J., Kim, E., Beach, W.B., and Shakouri, A., “Promoting Advanced Technology Adoption Among SMEs via A Cross-Industry Community of Practice,” Journal of the Knowledge Economy, 2026. (In 2nd review)
  2. Sim, Y., Kim, E.†, Sohn, J., Barr, J., Lee, H., Beach, B., Jun, M.B.G., and Shakouri, A., “Generative Latent Space Modeling of Stamping Sound for Anomaly Detection and Predictive Maintenance,” Journal of Manufacturing Science and Engineering-Transactions of the ASME, 2026. (Accepted)
  3. Chen, S., Fu, X., Park, H., Sim, Y., Lee, H.G., Zhou, F., Kim, E., and Jun, M.B.G., “Stress-Oriented Toolpath Planning for Fused Filament Fabrication Using a Graph Neural Network Surrogate Model,” Journal of Manufacturing Science and Engineering-Transactions of the ASME, Vol. 148, Issue 10, No. 101006 (9 pages), 2026. doi
  4. Kim, E.†, Sim, Y., Li, A., Mostafiz, M., Jun, M.B.G., Bertino, E., and Shakouri, A., “Multi-sensor and MTConnect dataset of metal cutting anomaly in milling process from laboratory and industry settings,” Scientific Data, Vol. 13, No. 945 (14 pages), 2026. doi Top 15% in Multidisciplinary (JCR 2024)
  5. Sim, Y., Kim, E.†, Lee, H., Sohn, J., and Jun, M.B.G., “Structured sound data augmentation based on spectral analysis for machine tool operational state monitoring,” The International Journal of Advanced Manufacturing Technology, Vol. 141, pp. 1705–1719, 2025. doi
  6. Kim, E., Lee, H., Sim, Y., Lee, J., and Jun, M.B.G., “Overcoming sparse run-to-failure data challenges in manufacturing: a contrastive mixer framework for remaining useful life prediction,” CIRP Annals-Manufacturing Technology, Vol. 74, Issue 1, pp. 579–583, 2025. doi
  7. Kim, E., Jeon, J., Kim, Y., Yun, H., Wellman, J., Lee, S.W., Jun, M.B.G., and Lee, J., “Control-resilient wear prediction for thin wire flattening mills via internal sound-guided dynamic convolutional network,” International Journal of Precision Engineering and Manufacturing-Green Technology, Vol. 12, pp. 919–934, 2025. doi Top 15% in Engineering, Mechanical (JCR 2024)
  8. Jeon, J., Sim, Y., Lee, H., Han, C., Yun, D., Kim, E., Nagendra, S.L., and Jun, M.B.G., “ChatCNC: Conversational machine monitoring via large language model and real-time retrieval augmented generation,” Journal of Manufacturing Systems, Vol. 79, pp. 504–514, 2025. doi Top 1% in Operations Research & Management Science (JCR 2024)
  9. Saha, A., Airehenbuwa, B., Jahangir, J., Ndoye, M., Akasheh F., Kim, E., Fiock T., Meter, Z., Alam, M., and Shakouri, A., “Part Fingerprinting Based Productivity Monitoring of CNC Machines with Low-Cost Current Sensor,” The International Journal of Advanced Manufacturing Technology, Vol. 137, pp. 5913–5926, 2025. doi
  10. Kim, E., Bui, T., Yuan, J., Mouli, S.C., Ribeiro, B., Yeh, R.A., Fassnacht, M.P., and Jun, M.B.G., “Online real-time machining chatter sound detection using convolutional neural network by adopting expert knowledge,” Manufacturing Letters, Vol. 41, pp. 1386–1397, 2024. doi
  11. Lee, J., Akin, S., Sim, Y., Lee, H., Kim, E., Nam, J., Song, K., and Jun M.B.G., “A stethoscope-guided interpretable deep learning framework for powder flow diagnosis in cold spray additive manufacturing,” Manufacturing Letters, Vol. 41, pp. 1515–1525, 2024. doi
  12. Kim, E.*, Mun, D., Jun, M.B.G., and Yun, H., “Operation and Productivity Monitoring from Sound Signal of Legacy Pipe Bending Machine Via Convolutional Neural Network (CNN),” International Journal of Precision Engineering and Manufacturing, Vol. 25, pp. 1437–1456, 2024. doi
  13. Kim, E., Wiese, L., Will, H., Magana, A.J., and Jun, M.B.G., “An Experiential Learning Approach to Industrial IoT Implementation for Smart Manufacturing through Coursework and University-Industry Partnership,” Journal of Engineering Technology, Vol. 40, No. 2, pp. 8–18, 2023.
  14. Zhou, F., Fu, X., Chen, S., Kim, E., and Jun, M.B.G., “Fiber Optic Sensor for Smart Manufacturing,” International Journal of Precision Engineering and Manufacturing-Smart Technology, Vol. 1, Issue 2, pp. 125–136, 2023. doi
  15. Kim, E., Yun, H., Araujo, O.C., and Jun, M.B.G., “Sound Recognition Based on Convolutional Neural Network for Real-time Cutting State Monitoring of Tube Cutting Machines,” International Journal of Precision Engineering and Manufacturing-Smart Technology, Vol. 1, Issue 1, pp. 1–18, 2023. doi Editor-in-Chief's Choice
  16. Yun, H., Kim, E., Kim, D.M., Park, H.W., and Jun, M.B.G., “Machine learning for object recognition in manufacturing applications: A review,” International Journal of Precision Engineering and Manufacturing, Vol. 24, pp. 683–712, 2023. doi
  17. Fu, X., Zhou, F., Yun, H., Kim, E., Chen, S., and Jun, M.B.G., “Machine Straightness Error Measurement Based on Optical Fiber Fabry–Pérot Interferometer Monitoring Technique,” Journal of Manufacturing Science and Engineering-Transactions of the ASME, Vol. 145, Issue 1, 2023. doi
  18. Jang, K.H., Yoon, H.S., Lee, H.T., Kim, E., and Ahn, S.H., “50 nm Scale Alignment Method for Hybrid Manufacturing Processes for Full 3D Structuring,” International Journal of Precision Engineering and Manufacturing, Vol. 21, Issue 12, pp. 2407–2417, 2020. doi
  19. Yoon, H.S., Lee, J.Y., Kim, M.S., Kim, E., Shin, Y.J., Kim, S.Y., Min, S., and Ahn, S.H., “Power consumption assessment of machine tool feed drive units,” International Journal of Precision Engineering and Manufacturing-Green Technology, Vol. 7, Issue 2, pp. 455–464, 2020. doi Top 15% in Engineering, Mechanical (JCR 2024)
  20. Yoon, H.S., Jang, K.H., Kim, E., Lee, H.T., and Ahn, S.H., “Hybrid 3D Printing by Bridging Micro/Nano Processes,” Journal of Micromechanics and Microengineering, Vol. 27, No. 6, 2017. doi
  21. Yoon, H.S., Lee, H.T., Kim, E., and Ahn, S.H., “Direct printing of anisotropic wetting patterns using aerodynamically focused nanoparticle (AFN) printing,” Applied Surface Science, Vol. 396, pp. 1450–1457, 2017. doi Top 15% in Material Science, Coating & Films (JCR 2024)
  22. Kim, E., Shin, Y.J., and Ahn, S.H., “The Effects of Moisture and Temperature on the Mechanical Properties of Additive Manufacturing Components: Fused Deposition Modeling,” Rapid Prototyping Journal, Vol. 22, Issue 6, pp. 887–894, 2016. doi Top 25% in Engineering, Mechanical (JCR 2024)
  23. Lee, J.Y., Ahn, S.H., Shin, Y.J., Kim, M.S., Kim, E., Yoon, H.S., Kim, S.Y., Yoon. Y. C., and Min, S.K., “A simplified machine-tool power-consumption measurement procedure and methodology for estimating total energy consumption,” Journal of Manufacturing Science and Engineering-Transactions of the ASME, Vol. 138, Issue 5, 2016. doi
  24. Bilegt, E., Yoon, H.S., Lee, H.T., Kim, E., Kim, C.S., and Ahn, S.H., “Design and Evaluation of Micro-Cutting Tools for Local Planarization,” International Journal of Precision Engineering and Manufacturing, Vol. 17, No. 10, pp. 1267–1273, 2016. doi
  25. Ahn, S.H., Yoon, H.S., Jang, K.H., Kim, E., Lee, H.T., Kim, C.S., Lee, G.Y., and Cha, S.W., “Nanoscale 3D printing process using aerodynamically focused nanoparticle (AFN) printing, micro-machining, and focused ion beam (FIB),” CIRP Annals-Manufacturing Technology, Vol. 64, Issue 1, pp. 523–526, 2015. doi
  26. Lee, K.T., Kim, E., Chu, W.S., and Ahn, S.H., “Design and 3D printing of controllable-pitch Archimedean screw for pico-hydropower generation,” Journal of Mechanical Science and Technology, Vol. 29, Issue 11, pp. 4851–4857, 2015. doi
  27. Yoon, H.S., Kim, E., Kim, M.S., Lee, J.Y., Lee, G. B., and Ahn, S.H., “Towards Greener Machine Tools - A review on Energy Saving Strategies and Technologies,” Renewable and Sustainable Energy Reviews, Vol. 48, pp. 870–891, 2015. doi Top 3% in Green & Sustainable Science and Technology (JCR 2024)
  28. Kim, E., and Chung, H.T., “Aerodynamic Design and Performance Prediction of Rotor Blades in A Single-Stage Axial Fan Using CFD Methods,” Journal of Computational Fluids Engineering, Vol. 19, No. 2, pp. 93–98, 2014. doi
  29. Yoon, H.S., Lee, J.Y., Kim, H.S., Kim, M.S., Kim, E., Shin, Y.J., Chu, W.S., and Ahn, S.H., “A Comparison of Energy Consumption in Bulk Forming, Subtractive, and Additive Processes: Review and Case Study,” International Journal of Precision Engineering and Manufacturing-Green Technology, Vol. 1, No. 3, pp. 261–279, 2014. doi Top 15% in Engineering, Mechanical (JCR 2024) Springer Award: Most Cited Article 2015
  30. Yoon, H.S., Kim, E., Kim, M.S., Lee, G. B., and Ahn, S.H., “Energy Consumption of the Brushing Process for PCB Manufacturing Based on a Friction Model,” International Journal of Precision Engineering and Manufacturing, Vol. 15, No. 11, pp. 2265–2272, 2014. doi

Peer-reviewed Conference Proceedings

  1. Jun, M.B.G., Sim, Y., Lee, H., Kim, E., and Shakouri, A., “Acoustic Fingerprint for Online Condition Monitoring in Progressive Stamping,” The International Conference on the Technology of Plasticity 2026 (ICTP 2026), 2026. (Accepted)
  2. Kim, E.†, Sohn, J., Tanveer, A., Sim, Y., Oh, J., and Jun, M.B.G., “Generating Machining Sound Using Operational Context,” 2026 US-Korea Conference (UKC 2026), 2026 (Accepted)
  3. Yun, D., Lee, G., Sim, Y., Kim, E., Choi, H.J., Jun, M.B.G., and Lee, J., “Generative AI-driven Autonomous Report Generation Framework for Machine Monitoring and Prognostics,” ASME 2026 21st International Manufacturing Science and Engineering Conference (MSEC 2026), 2026. (Presented, publication details will be updated.)
  4. Kim, E.†, Bae, Y., Beach, B.W., Roberts, D., Kauffman, E., and Shakouri, A., “Real-time remote monitoring of CNC machine tools via MTConnect and part detection algorithm,” ASME 2025 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2025), Vol. 2B, V02BT02A055, 2025. doi
  5. Tubbs, N., Lawrence, D., Mason, E., Kim, E.†, Akasheh, F., Ndoye, M., and Shakouri, A., “Online and real-time 3D printer monitoring using MTConnect data integration towards printing error diagnostics,” ASME 2025 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2025), Vol. 2B, V02BT02A003, 2025. doi
  6. Sim, Y., Kim, E.†, Lee, J., Lee, H., Yun, D., Meyong, N., Hwang, Y., Park, H.W., and Jun, M.B.G., “Sound data augmentation using frequency response superposition for machine tool component running state recognition,” ASME 2025 20th International Manufacturing Science and Engineering Conference (MSEC 2025), Vol. 89022, V002T16A006, 2025. doi
  7. Carrosco, B., Zhang, M., Kim, E., Yazawa, K., Shakouri, A., and Gomez, A., “Harnessing Real-Time Sensor Data for Fault Diagnosis in the Continuous Production of Copper Magnet Wires,” Proceedings of the IISE Annual Conference & Expo 2025, 2025. doi
  8. Mostafiz, M., Kim, E.*, Li, A., Jun, M.B.G., Bertino, E., and Shakouri, A., “Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data,” 22nd IEEE International Conference on Industrial Informatics (INDIN), 2024. doi
  9. Kim, E., Yuan, J., Lee, J., Yun, H., Fassnacht, M., Lee, S.W., and Jun, M.B.G., “Real-time Cutting State Monitoring for Micro-volume Fine Milling Using MTConnect Framework Based on Sound and Convolutional Neural Network (CNN),” World Congress on Micro and Nano Manufacturing 2023 (WCMNM 2023), pp. 235–239, 2023. NSF Student Travel Support Award
  10. Kim, E., Wiese, L., Will, H., Magana, A.J., and Jun, M.B.G., “Taking an Experiential Learning Approach to Industrial IoT Implementation for Smart Manufacturing through Course Work and University-Industry Partnership,” 2023 ASEE Annual Conference & Exposition, Manufacturing Division, 2023. doi Best Paper Award and Invited for Publication in Journal of Engineering Technology
  11. Fiock, T., Mohn, J., Mack, J., Mousoulis, C., Kim, E., Wiese, L., Jun, M.B.G., Magana, A.J., and Shakouri, A., “Data Analytics Short Courses for Reskilling and Upskilling Indiana’s Manufacturing Workforce,” 2023 ASEE Annual Conference & Exposition, Manufacturing Division, 2023. doi
  12. Jun, M.B.G., Yun, H., and Kim, E., “Human expertise inspired smart sensing and manufacturing,” IEEE 2021 International Conference on Electronics, Communications and Information Technology (ICECIT), 2021. doi
  13. Kim, E., Yun, H., Jun, M.B.G., Kim, K., and Cha, S.W., “Multiple sound sensors and fusion in modern CNN-based machine state prediction,” ASME 2021 16th International Manufacturing Science and Engineering Conference (MSEC 2021), Vol. 85062, V001T05A017, 2021. doi
  14. Yun, H., Kim, H., Kim, E., and Jun, M.B.G., “Development of internal sound sensor using stethoscope and its applications for machine monitoring,” Procedia Manufacturing, Vol. 48, pp. 1072–1078, 2020. doi
  15. Yoon, H.S., Jang, K.H., Kim, E., Lee, H.T., Park, H., Kim, D.W., Kim, C.S., Lee, G.Y., Lee K., and Ahn, S.H., “Proceedings in 4th International Conference on Virtual Machining Process Technology 2015,” pp. 2–5, 2015.
  16. Kim, E., Yoon, H.S., Lee, J.Y., Kim, M.S., Shin, Y.J., Ahn, S.H., Min, S., and Dornfeld, D., “Acceleration and Deceleration Characteristics of Power Consumption on Machine Tool Feed Drive,” International Conference on Leading Edge Manufacturing in 21st Century (LEM21), Vol. 2015.8, pp. 0124-1–0124-5, 2015. doi
  17. Lee, J.Y., Yoon, H.S., Kim, M.S., Kim, E., and Ahn, S.H., “Developing Energy Consumption Model and Application to Verifying Energy Saving Strategies,” US-Korea Conference (UKC 2014), 2014
  18. Yoon, H.S., Lee, J.Y., Kim, M.S., Kim, E., and Ahn, S.H., “Empirical Study of the Power Efficiency of Various Machining Processes,” Procedia CIRP, Vol. 14, pp. 558–563, 2014. doi

Conference Presentations

  1. Kim, E.†, Sohn, J., Tanveer, A., Sim, Y., Oh, J., and Jun, M.B.G., “Generating Machining Sound Using Operational Context,” 2026 US-Korea Conference (UKC 2026), August 5–8, 2026, Orlando, FL, USA. Invited Talk in Aerospace and Ocean Cluster
  2. Sim, Y., Kim, E.†, Sohn, J., Barr, J., Lee, H., Beach, B., Jun, M.B.G., and Shakouri, A., “Generative Latent Space Modeling of Stamping Sound for Anomaly Detection and Predictive Maintenance,” ASME 2026 21st International Manufacturing Science and Engineering Conference (MSEC 2026), June 14-18, 2026, State College, PA, USA. Best Paper Award (Second Place)
  3. Chen, S., Fu, X., Park, H., Sim, Y., Lee, H.G., Zhou, F., Kim, E., and Jun, M.B.G., “Stress-Oriented Toolpath Planning for Fused Filament Fabrication Using a Graph Neural Network Surrogate Model,” ASME 2026 21st International Manufacturing Science and Engineering Conference (MSEC 2026), June 14-18, 2026, State College, PA, USA.
  4. Yun, D., Lee, G., Sim, Y., Kim, E., Choi, H.J., Jun, M.B.G., and Lee, J., “Generative AI-driven Autonomous Report Generation Framework for Machine Monitoring and Prognostics,” ASME 2026 21st International Manufacturing Science and Engineering Conference (MSEC 2026), June 14-18, 2026, State College, PA, USA.
  5. Kim, E., Lee, H., Sim, Y., Lee, J., and Jun, M.B.G., “Overcoming sparse run-to-failure data challenges in manufacturing: a contrastive mixer framework for remaining useful life prediction,” 74th CIRP General Assembly (GA), CIRP, August 18–23, 2025, Stockholm, Sweden, Part I presentation.
  6. Kim, E.†, Bae, Y., Beach, B.W., Roberts, D., Kauffman, E., and Shakouri, A., “Real-time remote monitoring of CNC machine tools via MTConnect and part detection algorithm,” ASME 2025 IDETC/CIE, August 17–20, 2025, Anaheim, CA, USA.
  7. Tubbs, N., Lawrence, D., Mason, E., Kim, E.†, Akasheh, F., Ndoye, M., and Shakouri, A., “Online and real-time 3D printer monitoring using MTConnect data integration towards printing error diagnostics,” ASME 2025 IDETC/CIE, August 17–20, 2025, Anaheim, CA, USA.
  8. Sim, Y., Kim, E.†, Lee, J., Lee, H., Yun, D., Meyong, N., Hwang, Y., Park, H.W., and Jun, M.B.G., “Sound data augmentation using frequency response superposition for machine tool component running state recognition,” ASME 2025 MSEC, June 23–27, 2025, Greenville, SC, USA.
  9. Carrosco, B., Zhang, M., Kim, E., Yazawa, K., Shakouri, A., and Gomez, A., “Harnessing Real-Time Sensor Data for Fault Diagnosis in the Continuous Production of Copper Magnet Wires,” IISE Annual Conference & Expo 2025, May 31–June 3, 2025, Atlanta, GA, USA.
  10. Mostafiz, M., Kim, E.*, Li, A., Jun, M.B.G., Bertino, E., and Shakouri, A., “Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data,” IEEE INDIN 2024, August 18–20, 2024, Beijing, China.
  11. Kim, E., Bui, T., Yuan, J., Mouli, S.C., Ribeiro, B., Yeh, R.A., Fassnacht, M.P., and Jun, “Online real-time machining chatter sound detection using convolutional neural network by adopting expert knowledge,” NAMRC 53, June 17–21, 2024, Knoxville, TN, USA.
    12. NSF ENG Travel Support Award
  12. Lee, J., Akin, S., Sim, Y., Lee, H., Kim, E., Nam, J., Song, K., and Jun M.B.G., “A stethoscope-guided interpretable deep learning framework for powder flow diagnosis in cold spray additive manufacturing,” NAMRC 53, June 17–21, 2024, Knoxville, TN, USA.
  13. Kim, E., Yuan, J., Lee, J., Yun, H., Fassnacht, M., Lee, S.W., and Jun, M.B.G., “Real-time Cutting State Monitoring for Micro-volume Fine Milling Using MTConnect Framework Based on Sound and CNN,” WCMNM 2023, September 18–21, 2023, Evanston, IL, USA.
  14. Kim, E., Yuan, J., Yun, H., and Jun M.B.G., “Sound monitoring and applications for smart manufacturing using MTConnect framework and artificial intelligence,” PRESM 2023, July 16–21, 2023, Okinawa, Japan.
  15. Kim, E., Wiese, L., Will, H., Magana, A.J., and Jun, M.B.G., “Taking an Experiential Learning Approach to Industrial IoT Implementation for Smart Manufacturing through Course Work and University-Industry Partnership,” ASEE Annual Conference & Exposition, June 25–28, 2023, Baltimore, MD, USA.
  16. Fiock, T., Mohn, J., Mack, J., Mousoulis, C., Kim, E., Wiese, L., Jun, M.B.G., Magana, A.J., and Shakouri, A., “Data Analytics Short Courses for Reskilling and Upskilling Indiana’s Manufacturing Workforce,” ASEE Annual Conference & Exposition, June 25–28, 2023, Baltimore, MD, USA.
  17. Kim, E., Yun, H., and Jun, M.B.G., “Real-time Machine State Monitoring using Sound and Machine Learning,” The 9th International Conference on Manufacturing, Machine Design and Tribology, March 8–11, 2023, Jeju, Republic of Korea.
  18. Kim, E., “Machine Sound Monitoring by Adopting Human Recognition Skills for Smart Manufacturing,” Doctoral Symposium, ASME MSEC 2022, June 27–July 1, 2022, Purdue University, West Lafayette, IN, USA.
  19. Jun, M.B.G., Yun, H., and Kim, E., “Human expertise inspired smart sensing and manufacturing,” 2021 International Conference on Electronics, Communications and Information Technology, September 14–16, 2021, Khulna, Bangladesh.
  20. Kim, E., Yun, H., Jun, M.B.G., Kim, K., and Cha, S.W., “Multiple sound sensors and fusion in modern CNN-based machine state prediction,” ASME MSEC 2021, June 21–25, 2021, Virtual conference.
  21. Kim, E., Seo, J.H., Jeong, Y.H., and Jun M.B.G., “Development of artificial neural network (ANN) model for tool wear prediction using sound sensing,” PRESM 2021, July 21–23, 2021, Jeju, Republic of Korea.
    22. Outstanding Presentation Award
  22. Yun, H., Kim, H., Kim, E., and Jun, M.B.G., “Development of Internal Sound Sensor Using Stethoscope and Its Applications for Machine Monitoring,” NAMRC 48, June 22–26, 2020, Cincinnati, OH, USA.
  23. Yoon, H.S., Jang, K.H., Kim, E., Lee, H.T., and Ahn, S.H., “Design and evaluation of micro cantilevers fabricated using nanoscale 3D printing system,” ISGMA 2016, June 21–25, 2016, Bali, Indonesia.
  24. Ahn, S.H., Yoon, H.S., Jang, K.H., Kim, E., Lee, H.T., Lee, G.Y., Kim, C.S., and Cha, S.W., “Nanoscale 3D printing process using AFN printing, micro-machining, and focused ion beam (FIB),” 65th CIRP General Assembly, August 23–29, 2015, Cape Town, South Africa.
  25. Lee, K.T., Chu, W.S., Bhandari, B., Bhandari, P., Bhattachan, A., Kim, S.M., Lee, K.I., Poudel, S.R., Kim, M.S., Kim, E., Kim, M., Lee, J.Y., Kim, H.I., Kang, H.E., Lee, J.G., Sung, Y.K., Cho, S.H., Fengpei, Y., Lee, C.S., Mogasale, V., Ahn, S.H., et al., “Construction of Renewable Energy System and Applying to Health Service in Mountainous Area of Nepal,” ISGMA 2015, June 23–27, 2015, Qingdao, China.
  26. Yoon, H.S., Kim, E., Jang, K.H., Lee, G.Y., and Ahn, S.H., “Direct Patterning of Micro Conductive Line using AFN Printing,” ISGMA 2015, June 23–27, 2015, Qingdao, China.
  27. Kim, E., Yoon, H.S., Lee, J.Y., Kim, M.S., Shin, Y.J., Ahn, S.H., Min, S.K., and David Dornfeld, “Acceleration and Deceleration Characteristics of Power Consumption on Machine Tool Feed Drive,” LEM21, October 18–22, 2015, Kyoto, Japan.
  28. Yoon, H.S., Jang, K.H., Kim, E., Lee, H.T., Park, H., Kim, D.W., Kim, C.S., Lee, G.Y., Lee, K., and Ahn, S.H., “CAD/CAM and design for manufacturing (DFM) rules for novel 3D nanoscale printing process,” 4th International Conference on Virtual Machining Process Technology, June 2–5, 2015, Vancouver, Canada.
  29. Kim, M.S., Yoon, H.S., Lee, J.Y., Kim, E., Shin, Y.J., Kim, S.Y., Min, S.K., and Ahn, S.H., “Simplified Energy Measurement Methods for Comparison of Hardware Efficiency of Various Machine Tools,” ISAAT 2015, October 4–7, 2015, Jeju, Republic of Korea.
  30. Min, S., Yoon, H.S., Lee, J.Y., Kim, M.S., Kim, E., Shin, Y.J., Kim, S.Y., and Ahn, S.H., “Assessment on power consumption of machine tool feed drive units,” MIRAI 2015, March 25–26, 2015, Kaohsiung, Taiwan.
  31. Lee, K.T., Kim, E., Chu, W.S., and Ahn, S.H., “Life Cycle Assessment of 3D Printed Water Turbine Blade,” ISGMA 2014, June 24–28, 2014, Busan, Republic of Korea.
  32. Kim, M.S., Yoon, H.S., Lee, J.Y., Kim, E., Shin, Y.J., Ahn, S.H., Min, S.K., and Dornfeld, D., “Energy Evaluation Process of Machine Tools - Case Study: Milling Machine,” International Conference of Manufacturing Technology Engineers 2014, September 30–October 2, 2014, Jeju, Republic of Korea.
  33. Lee, J.Y., Yoon, H.S., Kim, M.S., Kim, E., and Ahn, S.H., “Developing Energy Consumption Model and Application to Verifying Energy Saving Strategies,” US-Korea Conference (UKC 2014), August 6–9, 2014, San Francisco, CA, USA.
  34. Yoon, H.S., Lee, J.Y., Kim, M.S., Kim, E., Shin, Y.J., Kim, S.Y., Sangkee Min, Jae Yoon Won, Jung-Hoon Cho, and Ahn, S.H., “Empirical assessment on power consumption of feed drive systems for machine tools,” International Conference of Manufacturing Technology Engineers 2014, September 30–October 2, 2014, Jeju, Republic of Korea.
  35. Yoon, H.S., Lee, H.T., Kim, E., Jang, K.H., Bilegt, E., Lee, G.Y., Kim, C.S., and Ahn, S.H., “Micro-scale Multi-material Structure Fabricated by Aerodynamically Focused Nanoparticle (AFN) Printing,” International Aerosol Conference (IAC), August 28–September 2, 2014, Busan, Republic of Korea.
  36. Kim, E., Shin, Y.J., Chu, W.S., and Ahn, S.H., “Effect of Moisture and Temperature on Mechanical Properties of Rapid Prototyping Parts - Fused Deposition Modeling (FDM),” ISGMA 2014, June 24–28, 2014, Busan, Republic of Korea.
  37. Yoon, H.S., Lee, J.Y., Kim, M.S., Kim, E., and Ahn, “Empirical Study of the Power Efficiency of Various Machining Processes,” 6th CIRP International Conference on High Performance Cutting (HPC), June 23–25, 2014, Berkeley, CA, USA.
  38. Yoon, H.S., Lee, J.Y., Kim, M.S., Kim, E., and Ahn, S.H., “Effect of Scale of Machining Hardware on Energy Consumption,” ISGMA 2013, June 25–29, 2013, Oahu, Hawaii, USA.

Patents

  1. Lee, K.T., Park, G.W., and Kim, E., “Method of Manufacturing Bamboo Toothbrush and Bamboo Toothbrush manufacturing Thereby,” U.S. Patent No. US 11,963,610, 2024. Registered
  2. Lee, K.T., Park, G.W., Kim, E., and Ahn, S.H., “Manufacturing Method for Bamboo Toothbrush and Bamboo Toothbrush Manufactured by The Same,” Korea Patent No. 10-2020-0005623, 2020. Registered
  3. Ahn, S.H., Lee, H.T., Kim, E., Quan, Y.J., and Li, T., “Wireless Sensor by Using Structural Coloration and Method for Manufacturing The Same,” Korea Patent No. 10-2018-0077012, 2020. Registered
  4. Ahn, S.H., Yoon, H.S., Jang, K.H., Kim, E., and Lee, H.T., “Apparatus for Manufacturing Nano-scale 3-dimensional Structure and Method Thereof,” Korea Patent No. 10-1654519, 2016. Registered
  5. Choo, R., Ahn, S.H., Yoon, H.S., Kim, H.S., and Kim, E., “Transformable Transfer Apparatus Which Equipped with Joint Module,” Korea Patent No. 10-173629, 2015. Registered