Xiaolei Fang
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Refereed Journal Articles (Published/Accepted)

  1. Jeong, C., Byon, E., He, F., & Fang, X. (2024). Tensor-Based Statistical Learning Methods for Diagnosing Product Quality Defects in Multistage Manufacturing Processes. IISE Transactions, (accepted), 1-75.
  2. Arabi, M., & Fang, X. (2024). A Federated Data Fusion-Based Prognostic Model for Applications with Multi-Stream Incomplete Signals. IISE Transactions, (accepted), 1-56.
  3. Lin, F., Fang, S. C., Fang, X., Gao, Z., & Luo, J. (2024). A distributionally robust chance-constrained kernel-free quadratic surface support vector machine. European Journal of Operational Research, 316(1), 46-60.
  4. Lin, F., Fang, S. C., Fang, X., & Gao, Z. (2024). Distributionally robust chance-constrained kernel-based support vector machine. Computers & Operations Research, 170, 106755.
  5. Zhou, C., & Fang, X. (2024). A supervised tensor dimension reduction-based prognostic model for applications with incomplete imaging data. INFORMS Journal on Data Science, 3(1), 84-104.
  6. Koprov, P., Fang, X., & Starly, B. (2024). Machine identity authentication via unobservable fingerprinting signature: A functional data analysis approach for MQTT 5.0 protocol. Journal of Manufacturing Systems, 76, 59-74.
  7. Li, R., Xia, T., Jinag, Y., Wu, J., Fang, X., Gebraeel, N., and Xi., L. (2024). Deep Complex Wavelet Denoising Network for Interpretable Fault Diagnosis of Industrial Robots with Noise Interference and Imbalanced Data. IEEE Transactions on Instrumentation & Measurement, (accepted)
  8. 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.
  9. 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.
  10. 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, 108827.
  11. 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.
  12. 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, 109014.
  13. 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.
  14. Lin, F., Fang, X., & Gao, Z. (2022). Distributionally robust optimization: A review on theory and applications. Numerical Algebra, Control and Optimization, 12(1), 159-212.
  15. 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.
  16. 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, 143(8), 081003.
  17. 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, 107592.
  18. 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, 107249.
  19. 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.
  20. Fang, X., Paynabar, K., & Gebraeel, N. (2019). Image-based prognostics using penalized tensor regression. Technometrics, 61(3), 369-384.
  21. 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.
  22. 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, 141(5), 051011.
  23. Xia, T., Xi, L., Pan, E., Fang, X., & Gebraeel, N. (2017). Lease-oriented opportunistic maintenance for multi-unit leased systems under product-service paradigm. Journal of Manufacturing Science and Engineering, 139(7), 071005.
  24. Fang, X., Paynabar, K., & Gebraeel, N. (2017). Multistream sensor fusion-based prognostics model for systems with single failure modes. Reliability Engineering & System Safety, 159, 322-331.
  25. Fang, X., Gebraeel, N. Z., & Paynabar, K. (2017). Scalable prognostic models for large-scale condition monitoring applications. IISE Transactions, 49(7), 698-710.
  26. 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.

Refereed Journal Articles (Under Review)

  1. Zhou, C., Su, Y., Xia, T., & Fang, X. (2023). Federated multilinear principal component analysis with applications in prognostics. Under Revision
  2. Sheng, J., & Fang, X. (2024). Differentially Private Log-Location-Scale Regression Using Functional Mechanism. Under Revision
  3. Su, Y., & Fang, X. (2024). Deep Learning-Based Residual Useful Lifetime Prediction for Assets with Uncertain Failure Modes. Under Revision
  4. Su, Y., & Fang, X. (2024). A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals. Under Review
  5. Fang, X., Paynabar, K., and Gebraeel, N.(2023). A Supervised Dimension Reduction-Based Prognostics Model for Applications with Incomplete Signals and Censored Failure Times, Under Revision
  6. Peters, B., Mohanty, A., Fang, X., and Gebraeel, N. (2023). Sensor fusion-based Prognostics Framework for Complex Engineering Systems Exhibiting Multiple Failure Modes, Under Revision
  7. Su, B., Qing, L., Lu, L., Jung, S., Fang, X., Xu, X. (2024) Enhancing Data Privacy in Human Factors Studies with Federated Learning, Human Factors, Under Review
  8. Jung, S. , Wang, H., Su, B. , Lu, L., Qing, L., Fang, X., and Xu. X. (2023). Learning Undergraduate Data Science Through a Mobile Device and Full Body Motions, Under Review

Refereed Conference Proceedings

  1. Li, X., & Fang, X. (2021, June). Multistream sensor fusion-based prognostics model for systems under multiple operational conditions. In International Manufacturing Science and Engineering Conference (Vol. 85079, p. V002T09A003). American Society of Mechanical Engineers.
  2. Fang, X., Paynabar, K., & Gebraeel, N. (2018, January). Real-time predictive analytics using degradation image data. In 2018 Annual Reliability and Maintainability Symposium (RAMS) (pp. 1-6). IEEE.