Xiaolei Fang

Assistant Professor

 
Xiaolei Fang‘s research interest lies in the field of industrial data analytics for high-dimensional and big data applications in the energy, manufacturing, and service sectors.

Methodologies:

  • Data science
  • Machine learning

Applications:

  • System performance assessment and optimization
  • System anomalies detection
  • Fault root causes diagnostics
  • Remaining useful lifetime prediction
  • Decision-making and control

Research Interests:

  • Addressing analytical, computational, and scalability challenges
  • Development of statistical and optimization methodologies
  • Analyzing massive amounts of complex data structures
  • Real-time asset management and optimization

Discover more about Xiaolei Fang

 

 

Publications

DISTRIBUTIONALLY ROBUST OPTIMIZATION: A REVIEW ON THEORY AND APPLICATIONS
Lin, F., Fang, X., & Gao, Z. (2022). [Review of , ]. NUMERICAL ALGEBRA CONTROL AND OPTIMIZATION, 12(1), 159–212. https://doi.org/10.3934/naco.2021057
Spatiotemporal denoising wavelet network for infrared thermography-based machine prognostics integrating ensemble uncertainty
Jiang, Y., Xia, T., Wang, D., Fang, X., & Xi, L. (2022), MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 7. https://doi.org/10.1016/j.ymssp.2022.109014
Infrared image stream based regressors for contactless machine prognostics
Dong, Y., Xia, T., Wang, D., Fang, X., & Xi, L. (2021), MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 154. https://doi.org/10.1016/j.ymssp.2020.107592
Integrated Remanufacturing and Opportunistic Maintenance Decision-Making for Leased Batch Production Lines
Xia, T., Zhang, K., Sun, B., Fang, X., & Xi, L. (2021), JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 143(8). https://doi.org/10.1115/1.4049963
Multichannel profile-based monitoring method and its application in the basic oxygen furnace steelmaking process
Qian, Q., Fang, X., Xu, J., & Li, M. (2021), JOURNAL OF MANUFACTURING SYSTEMS, 61, 375–390. https://doi.org/10.1016/j.jmsy.2021.09.010
Multistream sensor fusion-based prognostics model for systems under multiple operational conditions
Li, X., & Fang, X. (2021), Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021, 2. https://doi.org/10.1115/MSEC2021-62348
Remaining useful life prediction based on a multi-sensor data fusion model
Li, N., Gebraeel, N., Lei, Y., Fang, X., Cai, X., & Yan, T. (2021), RELIABILITY ENGINEERING & SYSTEM SAFETY, 208. https://doi.org/10.1016/j.ress.2020.107249
Two-dimensional variable selection and its applications in the diagnostics of product quality defects
Jeong, C., & Fang, X. (2021), IISE TRANSACTIONS. https://doi.org/10.1080/24725854.2021.1904524
Multi-sensor prognostics modeling for applications with highly incomplete signals
Fang, X., Yan, H., Gebraeel, N., & Paynabar, K. (2020), IISE TRANSACTIONS, Vol. 53, pp. 597–613. https://doi.org/10.1080/24725854.2020.1789779
Image-Based Prognostics Using Penalized Tensor Regression
Fang, X., Paynabar, K., & Gebraeel, N. (2019), TECHNOMETRICS, 61(3), 369–384. https://doi.org/10.1080/00401706.2018.1527727

View all publications via NC State Libraries

Xiaolei Fang