Xiaolei Fang

Zhou, C., & Fang, X. (2023). A convex two-dimensional variable selection method for the root-cause diagnostics of product defects. RELIABILITY ENGINEERING & SYSTEM SAFETY, 229. https://doi.org/10.1016/j.ress.2022.108827

Jiang, Y., Xia, T., Fang, X., Wang, D., Pan, E., & Xi, L. (2023). Sparse Hierarchical Parallel Residual Networks Ensemble for Infrared Image Stream-Based Remaining Useful Life Prediction. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 19(10), 10613–10623. https://doi.org/10.1109/TII.2022.3229493

Koprov, P., Gadhwala, S., Walimbe, A., Fang, X., & Starly, B. (2023). Systems and methods for authenticating manufacturing Machines through an unobservable fingerprinting system. Manufacturing Letters, 35, 1009–1018. https://doi.org/10.1016/j.mfglet.2023.08.051

Jiang, Y., Xia, T., Wang, D., Fang, X., & Xi, L. (2022). Adversarial Regressive Domain Adaptation Approach for Infrared Thermography-Based Unsupervised Remaining Useful Life Prediction. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 18(10), 7219–7229. https://doi.org/10.1109/TII.2022.3154789

Lin, F., Fang, X., & Gao, Z. (2022). [Review of DISTRIBUTIONALLY ROBUST OPTIMIZATION: A REVIEW ON THEORY AND APPLICATIONS]. NUMERICAL ALGEBRA CONTROL AND OPTIMIZATION, 12(1), 159–212. https://doi.org/10.3934/naco.2021057

Jiang, Y., Xia, T., Wang, D., Fang, X., & Xi, L. (2022). Spatiotemporal denoising wavelet network for infrared thermography-based machine prognostics integrating ensemble uncertainty. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 173. https://doi.org/10.1016/j.ymssp.2022.109014

Jeong, C., & Fang, X. (2022). Two-dimensional variable selection and its applications in the diagnostics of product quality defects. IISE TRANSACTIONS, 54(7), 619–629. https://doi.org/10.1080/24725854.2021.1904524

Dong, Y., Xia, T., Wang, D., Fang, X., & Xi, L. (2021). Infrared image stream based regressors for contactless machine prognostics. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 154. https://doi.org/10.1016/j.ymssp.2020.107592

Xia, T., Zhang, K., Sun, B., Fang, X., & Xi, L. (2021). Integrated Remanufacturing and Opportunistic Maintenance Decision-Making for Leased Batch Production Lines. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 143(8). https://doi.org/10.1115/1.4049963

Fang, X., Yan, H., Gebraeel, N., & Paynabar, K. (2021). Multi-sensor prognostics modeling for applications with highly incomplete signals. IISE TRANSACTIONS, 53(5), 597–613. https://doi.org/10.1080/24725854.2020.1789779

Qian, Q., Fang, X., Xu, J., & Li, M. (2021). Multichannel profile-based monitoring method and its application in the basic oxygen furnace steelmaking process. JOURNAL OF MANUFACTURING SYSTEMS, 61, 375–390. https://doi.org/10.1016/j.jmsy.2021.09.010

Li, X., & Fang, X. (2021). Multistream sensor fusion-based prognostics model for systems under multiple operational conditions. Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021, 2. https://doi.org/10.1115/MSEC2021-62348

Li, N., Gebraeel, N., Lei, Y., Fang, X., Cai, X., & Yan, T. (2021). Remaining useful life prediction based on a multi-sensor data fusion model. RELIABILITY ENGINEERING & SYSTEM SAFETY, 208. https://doi.org/10.1016/j.ress.2020.107249

Fang, X., Paynabar, K., & Gebraeel, N. (2019). Image-Based Prognostics Using Penalized Tensor Regression. TECHNOMETRICS, 61(3), 369–384. https://doi.org/10.1080/00401706.2018.1527727

Xia, T., Fang, X., Gebraeel, N., Xi, L., & Pan, E. (2019). Online Analytics Framework of Sensor-Driven Prognosis and Opportunistic Maintenance for Mass Customization. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 141(5). https://doi.org/10.1115/1.4043255

Jeong, C., & Fang, X. (2019). Penalized matrix regression for two-dimensional variable selection. ArXiv. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85098348719&partnerID=MN8TOARS

Dong, Y., Xia, T., Fang, X., Zhang, Z., & Xi, L. (2019). Prognostic and health management for adaptive manufacturing systems with online sensors and flexible structures. COMPUTERS & INDUSTRIAL ENGINEERING, 133, 57–68. https://doi.org/10.1016/j.cie.2019.04.051

Fang, X., Paynabar, K., & Gebraeel, N. (2018). Real-Time Predictive Analytics Using Degradation Image Data. Proceedings - Annual Reliability and Maintainability Symposium, 2018-January. https://doi.org/10.1109/RAM.2018.8463083

Fang, X., Paynabar, K., & Gebraeel, N. (2017). Image-based prognostics using penalized tensor regression. ArXiv. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85092884816&partnerID=MN8TOARS

Lease-Oriented Opportunistic Maintenance for Multi-Unit Leased Systems under Product- Service Paradigm. (2017). Journal of Manufacturing Science and Engineering, Transactions of the ASME, 139(7). https://doi.org/10.1115/1.4035962

Fang, X., Paynabar, K., & Gebraeel, N. (2017). Multistream sensor fusion-based prognostics model for systems with single failure modes. Reliability Engineering and System Safety, 159, 322–331. https://doi.org/10.1016/j.ress.2016.11.008

Fang, X., Gebraeel, N. Z., & Paynabar, K. (2017). Scalable prognostic models for large-scale condition monitoring applications. IISE Transactions, 49(7), 698–710. https://doi.org/10.1080/24725854.2016.1264646

Fang, X., Zhou, R., & Gebraeel, N. (2015). An adaptive functional regression-based prognostic model for applications with missing data. RELIABILITY ENGINEERING & SYSTEM SAFETY, 133, 266–274. https://doi.org/10.1016/j.ress.2014.08.013