| Industrial Artificial Intelligence for industry 4.0-based manufacturing systems J Lee, H Davari, J Singh, V Pandhare Manufacturing letters 18, 20-23, 2018 | 916 | 2018 |
| Field-synchronized Digital Twin framework for production scheduling with uncertainty E Negri, V Pandhare, L Cattaneo, J Singh, M Macchi, J Lee Journal of Intelligent Manufacturing 32 (4), 1207-1228, 2021 | 135 | 2021 |
| Distributed maintenance planning in manufacturing industries K Upasani, M Bakshi, V Pandhare, BK Lad Computers & Industrial Engineering 108, 1-14, 2017 | 94 | 2017 |
| Convolutional Neural Network Based Rolling-Element Bearing Fault Diagnosis for Naturally Occurring and Progressing Defects Using Time-Frequency Domain Features V Pandhare, J Singh, J Lee 2019 Prognostics and System Health Management Conference (PHM-Paris), 320-326, 2019 | 80 | 2019 |
| Intelligent Diagnostics for Ball Screw Fault Through Indirect Sensing Using Deep Domain Adaptation V Pandhare, X Li, M Miller, X Jia, J Lee IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020 | 40 | 2020 |
| Industrial AI and predictive analytics for smart manufacturing systems J Lee, J Singh, M Azamfar, V Pandhare Smart Manufacturing, 213-244, 2020 | 39 | 2020 |
| Detection and diagnosis of bottle capping failures based on motor current signature analysis M Azamfar, X Jia, V Pandhare, J Singh, H Davari, J Lee Procedia Manufacturing 34, 840-846, 2019 | 15 | 2019 |
| Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manuf. Lett. 18, 20–23 (2018) J Lee, H Davari, J Singh, V Pandhare | 14 | |
| Ball screw health monitoring with inertial sensors V Pandhare, M Miller, GW Vogl, J Lee IEEE Transactions on Industrial Informatics 19 (6), 7323-7334, 2022 | 8 | 2022 |
| Determination of significant factors affecting the bending strength of weld joint prepared by gas metal arc welding V Pandhare, P Rai, BK Lad, S Das, K Sabiruddin International Journal of Mechanical Engineering Research and Technology 2 (1 …, 2016 | 8 | 2016 |
| Collaborative Prognostics for Machine Fleets Using a Novel Federated Baseline Learner V Pandhare, X Jia, J Lee Annual Conference of the PHM Society 13 (1), 2021 | 6 | 2021 |
| Integrating PHM into production scheduling through a Digital Twin-based framework E Negri, L Cattaneo, V Pandhare, M Macchi, J Lee IFAC-PapersOnLine 55 (19), 31-36, 2022 | 5 | 2022 |
| 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 | 3 | 2024 |
| Memetic algorithm to optimize preventive maintenance schedule for a multi-component machine K UPASANI, M BAKSHI, V PANDHARE, BK LAD International Journal of Performability Engineering 12 (2), 183-195, 2016 | 3 | 2016 |
| Monitoring system for estimating useful life of a machine component M Azamfar, V Pandhare, M Miller, F Li, LI Pin, J Singh, H Davari, J Lee, ... US Patent App. 17/551,648, 2022 | 1 | 2022 |
| Industry 4.0 readiness assessment for micro small and medium-sized enterprises (MSMEs) R Kumar, A Gaur, MS Kulkarni, S Kumar, V Pandhare, B Kumar Lad IET Conference Proceedings CP885 2024 (11), 146-152, 2024 | | 2024 |
| Smart scheduling for next generation manufacturing systems: a systematic literature review S Chorghe, R Kumar, MS Kulkarni, V Pandhare, BK Lad Journal of Intelligent Manufacturing, 1-30, 2024 | | 2024 |
| Deriving inferences through natural language from structured datasets for asset lifecycle management S Bhattacharjee, V Pandhare IFAC-PapersOnLine 58 (8), 145-150, 2024 | | 2024 |
| Tool condition monitoring system M Azamfar, V Pandhare, M Miller, F Li, LI Pin, J Singh, H Davari, J Lee, ... US Patent App. 17/551,652, 2022 | | 2022 |
| Analyzing data obtained via wind farm supervisory control and data acquisition J Lee, X Jia, V Pandhare, M Miller Utility-scale Wind Turbines and Wind Farms 171, 105, 2021 | | 2021 |
Jay LeeClark Distingusihed Professor and Director of Industrial AI, University of Maryland College ParkVerified email at umd.edu
