Jay Lee

@umd.edu

Mechanical Engineering
Univ. of Maryland College Park



                             

https://researchid.co/jay.lee

Dr. Jay Lee is Clark Distinguished Professor and Director of Industrial AI Center in the Mechanical Engineering Dept. of the Univ. of Maryland College Park. Previously, he served as an Ohio Eminent Scholar, L.W. Scott Alter Chair and Univ. Distinguished Professor at Univ. of Cincinnati. He was Founding Director of National Science Foundation (NSF) Industry/University Cooperative Research Center (I/UCRC) on Intelligent Maintenance Systems ( during 2001-2019 with over 100 company memberships. IMS was selected as the most economically impactful I/UCRC in the NSF Economic Impact Study Report in 2012. He is also the Founding Director of Industrial AI Center ( ). He is a fellow of ASME, SME, PHM Society, and ISEAM, and a member of World Economic Forum (WEF) Global Future Council in Advanced Manufacturing and Value Chain. Previously served as Program Director of NSF during 1991-1998 and Director of United Technologies Research Center during 1998-2000.

RESEARCH, TEACHING, or OTHER INTERESTS

Mechanical Engineering, Industrial and Manufacturing Engineering, Engineering, Artificial Intelligence

42458

Scholar Citations

82

Scholar h-index

296

Scholar i10-index

Scopus Publications




RECENT SCHOLAR PUBLICATIONS

  • Novel topological machine learning methodology for stream-of-quality modeling in smart manufacturing
    J Lee, DY Ji, YM Hsu
    Manufacturing Letters 43, 60-63 2025

  • An Advanced Diagnostic Model for Gearbox Degradation Prediction Under Various Operating Conditions and Degradation Levels
    H Su, J Lee
    Annual Conference of the PHM Society 16 (1) 2024

  • A novel technique for multiple failure modes classification based on deep forest algorithm
    J Taco, P Kundu, J Lee
    Journal of Intelligent Manufacturing 35 (7), 3115-3129 2024

  • A unified industrial large knowledge model framework in industry 4.0 and smart manufacturing
    J Lee, H Su
    International Journal of AI for Materials and Design 3681, 20 2024

  • PHM for Spacecraft Propulsion Systems: Developing Resilient Models for Real-World Challenges
    T Minami, DY Ji, J Lee
    PHM Society European Conference 8 (1), 7-7 2024

  • Data Issues in Industrial AI System: A Meta-Review and Research Strategy
    X Li, C Yang, C Mller, J Lee
    arXiv preprint arXiv:2406.15784 2024

  • Digital twin-enabled robust production scheduling for equipment in degraded state
    V Pandhare, E Negri, L Ragazzini, L Cattaneo, M Macchi, J Lee
    Journal of Manufacturing Systems 74, 841-857 2024

  • The Pharmacy 5.0 framework: A new paradigm to accelerate innovation for large-scale personalized pharmacy care
    AC Lin, J Lee, MK Gabriel, RN Arbet, Y Ghawaa, AM Ferguson
    American Journal of Health-System Pharmacy 81 (5), e141-e147 2024

  • Volumetric nondestructive metrology for 3D semiconductor packaging: A review
    Y Su, J Shi, YM Hsu, DY Ji, AD Suer, J Lee
    Measurement 225, 114065 2024

  • Cyber–physical systems framework for AI in smart manufacturing and maintenance
    J Lee, W Li, YM Hsu, X Jia
    Artificial Intelligence in Manufacturing, 233-272 2024

  • Data Analytics and Cyber-physical Systems for Smart Manufacturing and Maintenance
    J Lee, W Li, YM Hsu, XJ Jia
    Artificial Intelligence in Manufacturing: Application and Case Studies 2024

  • Machine learning approaches for diagnostics and prognostics of industrial systems using open source data from PHM data challenges: a review
    H Su, J Lee
    arXiv preprint arXiv:2312.16810 2023

  • A Unified Industrial Large Knowledge Model Framework in Smart Manufacturing
    J Lee, H Su
    arXiv:2312.14428v1 [cs.LG] 22 Dec 2023 2023

  • Advancing predictive maintenance: A study of domain adaptation for fault identification in gearbox components
    S Tsuruta, K Wakimoto, T Nakamura, S Siahpour, M Miller, J Taco, J Lee
    PHM Society Asia-Pacific Conference 4 (1) 2023

  • Novel ensemble domain adaptation methodology for enhanced multi-class fault diagnosis of highly-connected fleet of assets
    T Minami, A Suer, P Kundu, S Siahpour, J Lee
    Phm society asia-pacific conference 4 (1) 2023

  • Phm for spacecraft propulsion systems: Similarity-based model and physics-inspired features
    T Minami, J Lee
    Phm society asia-pacific conference 4 (1) 2023

  • Digital Twin-enabled robust production scheduling for equipment in degraded state
    EN Vibhor Pandhare, L Ragazzini, L Cattaneo, M Macchi, J Lee
    Journal of Engineering Applications of Artificial Intelligence 2023

  • Ball Screw Health Monitoring With Inertial Sensors
    V Pandhare, M Miller, GW Vogl, J Lee
    IEEE Transactions on Industrial Informatics 19 (6) 2023

  • Designing Robust Topological Features for Wafer Map Pattern Classification
    X Han, X Jia, DY Ji, J Lee
    2023 34th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC 2023

  • Alignment of the IEEE industrial agents recommended practice standard with the reference architectures RAMI4. 0, IIRA, and SGAM
    P Leito, S Karnouskos, TI Strasser, X Jia, J Lee, AW Colombo
    IEEE Open Journal of the Industrial Electronics Society 4, 98-111 2023

MOST CITED SCHOLAR PUBLICATIONS

  • A cyber-physical systems architecture for industry 4.0-based manufacturing systems
    J Lee, B Bagheri, HA Kao
    Manufacturing letters 3, 18-23 2015
    Citations: 6571

  • Service innovation and smart analytics for industry 4.0 and big data environment
    J Lee, HA Kao, S Yang
    Procedia cirp 16, 3-8 2014
    Citations: 2950

  • Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications
    J Lee, F Wu, W Zhao, M Ghaffari, L Liao, D Siegel
    Mechanical systems and signal processing 42 (1-2), 314-334 2014
    Citations: 1871

  • Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics
    H Qiu, J Lee, J Lin, G Yu
    Journal of sound and vibration 289 (4-5), 1066-1090 2006
    Citations: 1720

  • Recent advances and trends in predictive manufacturing systems in big data environment
    J Lee, E Lapira, B Bagheri, H Kao
    Manufacturing letters 1 (1), 38-41 2013
    Citations: 1612

  • Industrial Artificial Intelligence for industry 4.0-based manufacturing systems
    J Lee, H Davari, J Singh, V Pandhare
    Manufacturing letters 18, 20-23 2018
    Citations: 1027

  • A review on prognostics and health monitoring of Li-ion battery
    J Zhang, J Lee
    Journal of power sources 196 (15), 6007-6014 2011
    Citations: 906

  • Intelligent prognostics tools and e-maintenance
    J Lee, J Ni, D Djurdjanovic, H Qiu, H Liao
    Computers in industry 57 (6), 476-489 2006
    Citations: 883

  • Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility
    SM Rezvanizaniani, Z Liu, Y Chen, J Lee
    Journal of power sources 256, 110-124 2014
    Citations: 844

  • Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods
    R Huang, L Xi, X Li, CR Liu, H Qiu, J Lee
    Mechanical systems and signal processing 21 (1), 193-207 2007
    Citations: 688

  • Industrial artificial intelligence in industry 4.0-systematic review, challenges and outlook
    RS Peres, X Jia, J Lee, K Sun, AW Colombo, J Barata
    IEEE access 8, 220121-220139 2020
    Citations: 683

  • A similarity-based prognostics approach for remaining useful life estimation of engineered systems
    T Wang, J Yu, D Siegel, J Lee
    2008 international conference on prognostics and health management, 1-6 2008
    Citations: 669

  • Handbook of maintenance management and engineering
    M Ben-Daya, SO Duffuaa, A Raouf, J Knezevic, D Ait-Kadi
    Springer 2009
    Citations: 666

  • Industrial big data analytics and cyber-physical systems for future maintenance & service innovation
    J Lee, HD Ardakani, S Yang, B Bagheri
    Procedia cirp 38, 3-7 2015
    Citations: 645

  • Smart agents in industrial cyber–physical systems
    P Leitao, S Karnouskos, L Ribeiro, J Lee, T Strasser, AW Colombo
    Proceedings of the IEEE 104 (5), 1086-1101 2016
    Citations: 564

  • Robust performance degradation assessment methods for enhanced rolling element bearing prognostics
    H Qiu, J Lee, J Lin, G Yu
    Advanced Engineering Informatics 17 (3-4), 127-140 2003
    Citations: 543

  • Cyber-physical systems architecture for self-aware machines in industry 4.0 environment
    B Bagheri, S Yang, HA Kao, J Lee
    IFAC-PapersOnLine 48 (3), 1622-1627 2015
    Citations: 535

  • Maintenance: changing role in life cycle management
    S Takata, F Kirnura, FJAM van Houten, E Westkamper, M Shpitalni, ...
    CIRP annals 53 (2), 643-655 2004
    Citations: 533

  • Watchdog Agent—an infotronics-based prognostics approach for product performance degradation assessment and prediction
    D Djurdjanovic, J Lee, J Ni
    Advanced Engineering Informatics 17 (3-4), 109-125 2003
    Citations: 459

  • Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation
    X Zhou, L Xi, J Lee
    Reliability engineering & system safety 92 (4), 530-534 2007
    Citations: 450

Publications

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