Journal Articles
- Shi, J., Rivera, A., & Wu, D. (2022). Battery Health Management Using Physics-Informed Machine Learning: Online Degradation Modeling and Remaining Useful Life Prediction, Mechanical Systems and Signal Processing, accepted.
- Zhang, Z., Liu, Q., & Wu, D. (2022). Predicting Stress-Strain Curves Using Transfer Learning: Knowledge Transfer Across Polymer Composites, Materials & Design, 218: 110700.
- Yavas, D., Liu, Q., Zhang, Z., & Wu, D. (2022). Design and Fabrication of Architected Multi-Material Lattices with Tunable Stiffness, Strength, and Energy Absorption, Materials & Design, 217: 110613.
- Wang, Z., Yang, W., Liu, Q., Zhao, Y., Liu, P., Wu, D., Banu, M., & Chen, L. (2022). Data-Driven Modeling of Process, Structure and Property in Additive Manufacturing: A Review and Future Directions, Journal of Manufacturing Processes, 77: 13-31.
- Wei, Y., Wu, D., & Terpenny, J. (2022). Constructing Robust and Reliable Health Indices and Improving the Accuracy of Remaining Useful Life Prediction, Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems, 5(2): 021009.
- Wang, D., Liu, Q., Wu, D., & Wang, L. (2022). Meta Domain Generalization for Smart Manufacturing: Tool Wear Prediction with Small Data, Journal of Manufacturing Systems, 62: 441-449.
- Shi, J., Peng, D., Peng, Z., Zhang, Z., Goebel, K., & Wu, D. (2022). Planetary Gearbox Fault Diagnosis Using Bidirectional-Convolutional LSTM Networks, Mechanical Systems and Signal Processing, 162: 107996.
- Wei, Y., Wu, D., & Terpenny, J. (2021). Learning the Health Index of Complex Systems Using Dynamic Conditional Variational Autoencoders, Reliability Engineering and System Safety, 216:108004.
- Zhang, Z., Yavas, D., Liu, Q., & Wu, D. (2021). Effect of Build Orientation and Raster Pattern on the Fracture Behavior of Carbon Fiber Reinforced Polymer Composites Fabricated by Additive Manufacturing, Additive Manufacturing, 47: 102204.
- Xie, R. and Wu, D. (2021). Optimal Transport-based Transfer Learning for Smart Manufacturing: Tool Wear Prediction Using Out-of-Domain Data, Manufacturing Letters, 29:104-107.
- Hyer, H., Zhou, L., Liu, Q., Wu, D., Song, S., Bai, Y., McWilliams, B., Cho, K., & Sohn, Y. (2021). High Strength WE43 Microlattice Structures Manufactured by Laser Powder Bed Fusion, Materialia, 16: 101067.
- Yavas, D., Zhang, Z., Liu, Q., & Wu, D. (2021). Fracture Behavior of 3D Printed Carbon Fiber Reinforced Polymer Composites, Composites Science and Technology, 208: 108741.
- Zhang, Z., Liu, Z., & Wu, D. (2021). Prediction of Melt Pool Temperature in Directed Energy Deposition Using Machine Learning, Additive Manufacturing, 37: 101692.
- Xu, H., Liu, Q., Casillas, J., Mcanally, M., Mubtasim, N., Gollahon, L., Wu, D., & Xu, C. (2021). Prediction of Cell Viability in Dynamic Optical Projection Stereolithography-based Bioprinting Using Machine Learning, Journal of Intelligent Manufacturing, https://doi.org/10.1007/s10845-020-01708-5.
- Shi, J., Yu, T., Goebel, K., & Wu, D. (2021). Remaining Useful Life Prediction of Bearings Using Ensemble Learning: The Impact of Diversity in Base Learners and Features, Transactions of the ASME, Journal of Computing and Information Science in Engineering, 21(2): 021004.
- Yavas, D., Zhang, Z., Liu, Q., & Wu, D. (2021). Interlaminar Shear Behavior of Continuous and Short Carbon Fiber Reinforced Polymer Composites Fabricated by Additive Manufacturing, Composites Part B: Engineering, 204: 108460.
- Zhang, Z., Shi, J., Yu, T., Santomauro, A., Gordon, A., Gou, J., & Wu, D. (2020). Predicting Flexural Strength of Additively Manufactured Continuous Carbon Fiber-Reinforced Polymer Composites Using Machine Learning, Transactions of the ASME, Journal of Computing and Information Science in Engineering, 20(6): 061015.
- Wei, Y., Wu, D., & Terpenny, J. (2020). Robust Incipient Fault Detection of Complex Systems Using Data Fusion, IEEE Transactions on Instrumentation and Measurement, 69(12), 9526-9534.
- Alam, MDE, Wu, D., & Dickerson, AK. (2020). Predictive Modeling of Drop Ejection from Damped, Dampened Wings by Machine Learning, Proceedings of the Royal Society A, 476(2241).
- Wei, Y., Wu, D., & Terpenny, J. (2020). Decision-Level Data Fusion in Quality Control and Predictive Maintenance, IEEE Transactions on Automation Science and Engineering, in press.
- Yu, T., Zhang, Z., Liu, Q., Kuliiev, R., Orlovskaya, N., & Wu, D. (2020). Extrusion-Based Additive Manufacturing of Yttria-Partially-Stabilized Zirconia Ceramics, Ceramics International, 46 (2020), 5020-5027.
- Zhang, Z., Poudel, L., Sha, Z., Zhou, W., & Wu, D. (2020). Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing, Transactions of the ASME, Journal of Computing and Information Science in Engineering, 2020, 20(2): 021002.
- Li, Z., Liu, R., & Wu, D. (2019). Data-Driven Smart Manufacturing: Tool Wear Monitoring with Audio Signals and Machine Learning, Journal of Manufacturing Processes, 48, 66-76.
- Zhang, L., Li, Z., Królczyk, G., Wu, D., & Tang, Q. (2019). Mathematical Modeling and Multi-attribute Rule Mining for Energy Efficient Job-shop Scheduling, Journal of Cleaner Production, 241, 118289.
- Yu, T., Hyer, H., Sohn, Y., Bai, Y., & Wu, D. (2019). Structure-Property Relationship in High Strength and Lightweight AlSi10Mg Microlattices Fabricated by Selective Laser Melting, Materials and Design, 108062.
- Yu, T., Zhang, Z., Song, S., Bai, Y., & Wu, D. (2019). Tensile and Flexural Behaviors of Additively Manufactured Continuous Carbon Fiber-Reinforced Polymer Composites, Composite Structures, 111147.
- Hao, J., Li, C., Meng, Q., Li, Z., & Wu, D. (2019). Effect of Tilt Angle on Bead Morphology in Multi-Axis Laser Cladding, Journal of Manufacturing Processes, 43, 311-322.
- Yu, T., Wu, D., & Li, Z. (2019). Predictive Modeling of Material Removal Rate in Chemical Mechanical Planarization with Physics-Informed Machine Learning, Wear, 426, 1430-1438.
- Li, Z., Zhang, Z., Shi, J., & Wu, D. (2019). Prediction of Surface Roughness in Extrusion-based Additive Manufacturing with Machine Learning, Robotics and Computer-Integrated Manufacturing, 57, 488-495.
- Li, Z., Wu, D., & Yu, T. (2019). Prediction of Material Removal Rate for Chemical Mechanical Planarization Using Decision Tree-Based Ensemble Learning, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 141(3), 031003.
- Li, Z., Goebel, K., & Wu, D. (2019). Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning, Transactions of the ASME, Journal of Engineering for Gas Turbines and Power, 141(4), 041008.
- Wu, D., Wei, Y., & Terpenny, J. (2018). Predictive Modeling of Surface Roughness in Fused Deposition Modeling Using Data Fusion, International Journal of Production Research.
- Wu, D. & Xu, C. (2018). Predictive Modeling of Droplet Formation Processes in Inkjet-Based Bioprinting, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 140(10), 101007.
- Wu, D., Ren, A., Zhang, W., Fan, F., Liu, P., Fu, X., & Terpenny, J. (2018). Cybersecurity for Digital Manufacturing, Transactions of the SME, Journal of Manufacturing Systems, 48, 3-12.
- Wang, J., Ma, Y., Zhang, L., Gao, R., & Wu, D. (2018). Deep Learning for Smart Manufacturing: Methods and Applications, Transactions of the SME, Journal of Manufacturing Systems, 48, 144-156.
- Li, Z., Wu, D., Hu, C, & Terpenny, J. (2018). An Ensemble Learning-based Prognostic Approach with Degradation-Dependent Weights for Remaining Useful Life Prediction, Reliability Engineering and System Safety, 184, 110-122.
- Wu, D., Jennings, C., Terpenny, J., Kumara, S., & Gao, R. (2018). Cloud-Based Parallel Machine Learning for Tool Wear Prediction, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 140(4), 041005.
- Wu, D., Jennings, C., Terpenny, J., Gao, R., & Kumara, S. (2017). A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 139(7), 071018.
- Wu, D., Liu., S., Zhang, L., Terpenny, J., Gao, R, Kurfess, T., & Guzzo, J. (2017). A Fog Computing-Based Framework for Process Monitoring and Prognosis in Cyber-Manufacturing, Transactions of the SME, Journal of Manufacturing Systems, 43(1), 25-34.
- Wu, D., Liu, X., Hebert, S., Gentzsch, W., & Terpenny, J. (2017). Democratizing Digital Design and Manufacturing Using High Performance Cloud Computing: Performance Evaluation and Benchmarking, Transactions of the SME, Journal of Manufacturing Systems, 43(1), 316-326.
- Jennings, C., Wu, D., & Terpenny, J. (2016). Forecasting Obsolescence Risk and Product Life Cycle with Machine Learning, IEEE Transactions on Components, Packaging, and Manufacturing Technology, 6(9), 1428-1439.
- Wu, D., Rosen, D.W., Panchal, J., & Schaefer, D. (2016). Understanding Communication and Collaboration in Social Product Development through Social Network Analysis, Transactions of the ASME, Journal of Computing and Information Science in Engineering, 16(1), 011001.
- Wu, D., Terpenny, J., & Gentzsch, W. (2015). Economic Benefit Analysis of Cloud-Based Design, Engineering Analysis, and Manufacturing, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 137(4), 040903.
- Wu, D., Rosen, D.W., & Schaefer, D. (2015). Scalability Planning for Cloud-Based Manufacturing Systems, Transactions of the ASME, Journal of Manufacturing Science and Engineering, 137(4), 040911.
- Wu, D., Rosen, D.W., Wang, L., & Schaefer, D. (2015). Cloud-Based Design and Manufacturing: A New Paradigm in Digital Manufacturing and Design Innovation, Computer-Aided Design, 59(1), 1-14.
- Wu, D., Thames, J.L., Rosen, D.W., & Schaefer, D. (2013). Enhancing the Product Realization Process with Cloud-Based Design and Manufacturing Systems, Transactions of the ASME, Journal of Computing and Information Science in Engineering, 13(4), 041004-041004-14.
- Wu, D., Greer, M.J., Rosen, D.W., & Schaefer, D. (2013). Cloud Manufacturing: Strategic Vision and State-of-the-Art, Transactions of the SME, Journal of Manufacturing Systems, 32(4), 564-579.
- Wu, D., Zhang, L., Jiao, J., & Lu, R. (2013). SysML-based Design Chain Information Modeling for Variety Management in Production Reconfiguration, Journal of Intelligent Manufacturing, 24(3), 575-596.