(* indicates current or former student; ** is current or former postdoc)
Wu, D.**, Wei, Y.*, and Terpenny, J., “Predictive Modeling of Surface Roughness in Additive Manufacturing Using Machine Learning,” International Journal of Production Research
Wu, D.**, Ren, A.*, Zhang, W., Terpenny, J., Liu, P., Fan, F., and Fu, X., “Cyber security for digital manufacturing,” Journal of Manufacturing Systems
Li, Z., Wu, D.**, Hu, C., and Terpenny, J., “ An Ensemble Learning-based Prognostic Approach with Degradation-Dependent Weights for Remaining Useful Life Prediction,” Special Issue on Impact of Prognostics and Health Management in Systems Reliability and Maintenance Planning, Reliability Engineering & System Safety
Wu, D.**, Liu., S., Zhang, L., Terpenny, J., Gao, R, Kurfess, T., & Guzzo, J., “A Fog Computing-Based Framework for Process Monitoring and Prognosis in Cyber-Manufacturing,” Journal of Manufacturing Systems, 43(1): 25-34, 2017.
Wu, D.**, Liu. X., Hebert, S., Gentzsch, W., & Terpenny, J., “Democratizing Digital Design and Manufacturing Using High Performance Cloud Computing: Performance Evaluation and Benchmarking,” Journal of Manufacturing Systems, 2017.
Jennings, C.*, Wu, D.**, and Terpenny, J., “Forecasting obsolescence risk and product lifecycle with machine learning,” IEEE Transactions on Components, Packaging, and Manufacturing Technology ( Volume: 6, Issue: 9, Sept. 2016 ).
Wu, D.**, Terpenny, J., & Schaefer, D. (2016). Digital Design and Manufacturing on the Cloud: A Review of Software and Services, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Cambridge University Press.
Publications by Category
- Cloud-based Design and Manufacturing
- Obsolescence Management and Forecasting
- Machine Learning
- Product Complexity and Product Families