Publication

* underline denotes my Ph.D. student or my research fellow.

Some working papers

    • Exploring Novel Uncertainty Quantification through Forward Intensity Function Modeling, Journal of Machine Learning Research, minor revision. (with Wang Y. and Tang C.Y.)
    • Analyzing Recurrent Failure Data from a Large Directed Physical Network: An Application to Distribution Pipes. Journal of the American Statistical Association, to appear. (with Zhai, Q., Li, C., Revie, M., and Dunson, D.)
    • Likelihood-based Inference under Non-Convex Boundary Constraints, Biometrika, to appear. (with Wang, J., and Chen, Y.)
    • Optimal Abort Policy for Mission-Critical Systems under Imperfect Condition Monitoring, Operations Research, 2023, under minor revision (with Sun, Q., and Hu, J.)
    • Asymptotic Analysis for Data-Driven Inventory Policies, Operations Research, to appear, (with Zhang, X. and Haskell, W. B.)
    • Robust Condition-Based Production and Maintenance Planning for Degradation Management, Production and Operations Management, 32(12), 3951-3967. (with Sun, Q., Chen, P., and Wang, X.)
    • Analysis of Product Return Data with Two-Layer Censoring, Journal of the Royal Statistical Society, Series C, to appear (with Wang, Y.)
    • ‘Learning Local Cascading Failure Pattern from Massive Network Failure Data,  Journal of the Royal Statistical Society, Series C, to appear (with Xiao, X. and Revie, M.)
    • Remaining Useful Life Prediction Based on Forward Intensity, Technometrics, tentatively accepted. (with Xiao, P., Wang, Y., and Liu, W.)

Statistics and Operations Management

      • Conditional Modeling of Panel Count Data with Partly Interval-censored Failure Event, Biometrics, 2024, to appear. (with Hu, X., Su, W. and Zhao, X.)
      • Simplex-based Proximal Multicategory Support Vector Machine, IEEE Transactions on Information Theory, 2023, 69 (4), 2427-2451. (with Fu, S., and Chen, P.)
      • Paired or partially paired two-sample tests with unordered samples, Journal of the Royal Statistical Society, Series B, 2022, 84(4), 1503-1525. (with Wang Y. and Tang, Y.)
      • Analytics in warranty reserve planning: Demand forecasting and funds pooling, Manufacturing & Service Operations Management, 2022, 24 (4), 2221-2239. (with Wang, X., Li, L., Zhong, Y., Xie, W.)
      • Simplex-based Multinomial Logistic Regression with Diverging Numbers of Categories and Covariates. Statistica Sinica, 2022, to appear. (with Fu, S., Chen, P. and Liu Y.)
      • A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators. Journal of Machine Learning Research. [arxiv], 2022, 23 (1), 2608-2651. (with Zhang, X. and Haskell, W. B.)
      • Dynamic Warranty Reserve Planning Over a Finite Horizon. IEEE Transactions on Automatic Control, 2021, 67(4), 2004-2010. (with Wang X. and Xie, W.)
      • Efficient Semiparametric Estimation of Time-Censored Intensity-Reduction Models for Repairable Systems, Scandinavia Journal of Statistics, 49(4), 1860-1888. (with Wang, J. and Chen, P.)
      • Estimating the Inter-Occurrence Time Distribution from Superposed Renewal Processes, Bernoulli, 2021, 27(4), 2804-2826. (with Li, X. and Tang, C.)
      • On computation of semi-parametric maximum likelihood estimators with shape constraint, Biometrics, 2021, 77(1), 113-124. (with Wang, Y. and Cao, H.)
      • Reliability Estimation from Left-Truncated and Right-Censored Data Using Splines, Statistica Sinica, 30, 845-875. (with Jiang, W. and Zhao X.)
      • Closed-form estimators for the gamma distribution derived from likelihood equations. American Statistician, 2017, 71(2), 177-181. (with Chen N.)
      • On analysis of incomplete field failure data, The Annals of Applied Statistics, 2014, 8(3), 1713-1727. (with Ng, K.H.T.)
      • How do heterogeneities in operating environment affect field failure predictions and test planning? The Annals of Applied Statistics, 2013, 7(4), 2249-2271. (with Hong, Y. and Xie Y.)

 

Industrial Statistics:

      • Spatio-Temporal Analysis and Prediction of Mass Telecommunication Base Station Failure Events, Technometrics, accepted. (with Wu, T., Wang, Y., and Chen N.)
      • Statistical Modeling of the Effectiveness of Preventive Maintenance for Repairable Systems, Technometrics, to appear. (with Ye, X., Cai, J. and Tang L.C.)
      • Zhai, Q. and Ye, Z.S. (2022+) A Multivariate Stochastic Degradation Model for Dependent Performance Characteristics, Technometrics. Accepted.
      • Liu, X., Du, J., & Ye, Z. S. (2023) A Covariate-regulated Sparse Subspace Learning Model and Its Application to Process Monitoring and Fault Isolation, Technometrics. 65(2), 269-280.
      • Lu, L., Wang, B., Hong, Y. and Ye, Z.S. (2021) General Path Models for Degradation Data with Multiple Characteristics and Covariates, Technometrics, 63 (3), 354-369.
      • Cai, J., Cigsar, C. and Ye Z.S. (2020) Assessing the Effect of Repair Delays on a Repairable System, Journal of Quality Technology, 52(3), 293-303.
      • Xiao, X., Chen, P., Ye, Z.S. and Tsui, K.L. (2021). On computing multiple change points for the gamma distribution. Journal of Quality Technology, 53(3), 267-288.
      • Sun, Q., Ye, Z.S. and Hong, Y. (2020) Statistical modeling of multivariate destructive degradation tests with blocking. Technometrics, 62(4), 536-548.
      • Hong, L.Q., Tan, M., and Ye, Z.S. (2020) Nonparametric link functions with shape constraints in stochastic degradation processes: Application to emerging contaminants. Journal of Quality Technology, 52(4), 370-384.
      • Chen, P., Wang, B.X. and Ye, Z.S. (2019) A yield-based process capability indices for non-normal processes. Journal of Quality Technology, 51(2), 171-180.
      • Zhai, Q. and Ye, Z.S. (2018) Degradation in Common Dynamic Environments, Technometrics, 60(4), 461-471.
      • Ye, Z.S., Hu, Q.P. and Yu, D. (2019) Strategic allocation of test units in an accelerated degradation test plan. Journal of Quality Technology, 51(1), 64-80.
      • Hong, L.Q., Ye, Z.S. and Ling, R. (2018) Environmental risk assessment of emerging contaminants using degradation data, Journal of Agricultural, Biological, and Environmental Statistics, 23(3), 390-409.
      • Wang, X.,Ye, Z.S., Hong. Y.L. and Tang, L.C. (2018) Analysis of field return data with failed-but-not-reported events”. Technometrics, 60(1), 90-100.
      • Chen, P., and Ye, Z.S. (2018) Uncertainty quantification for monotone stochastic degradation models. Journal of Quality Technology, 50(2), 207-219.
      • Chen, P., Ye, Z.S. and Zhao X. (2017) Minimum distance estimation for the generalized Pareto distribution, Technometrics, 59(4), 528-541.
      • Hong, L.Q. and Ye, Z.S. (2017) When is acceleration unnecessary in a degradation test? Statistica Sinica, 27(3), 1461-1483.
      • Chen, P. and Ye, Z.S. (2017) Estimation of field reliability based on aggregate lifetime data, Technometrics, 59(1), 115-125.
      • Chen, P. and Ye, Z.S. (2017) Approximate statistical limits for a Gamma distribution. Journal of Quality Technology, 49(1), 64-77.
      • Ye, Z.S. and Tang, L.C. (2016) Augmenting the unreturned for field data with information on returned failures only, Technometrics, 58(4), 513-523.
      • Shen, L.; Sun, D.; Ye, Z.S. and Zhao, X. (2016) Inference on an adaptive accelerated life test with application to smart grid data-acquisition-devices. Journal of Quality Technology, 49(3), 191-212.
      • Ye, Z.S.; Xie, M.; Tang, L.C. and Chen, N. (2014) Efficient semiparametric estimation of gamma processes for deteriorating products. Technometrics, 56(4), 504-513.
      • Ye, Z.S. and Chen, N. (2014) The inverse Gaussian process as a degradation model. Technometrics, 56 (3) 302-311.
      • Wang, B and Ye, Z.S. (2014) Inference on the Weibull distribution based on record values. Computational Statistics and Data Analysis, 83, 2636.
      • Ye, Z.S.; Xie, M.; Tang, L.C. and Shen, Y. (2012) Degradation-based burn-in planning under competing risks, Technometrics, 54 (2), 159-168.
      • Ye, Z.S.; Tang, L.C. and Xie, M. (2011) A burn-in scheme based on percentiles of the residual life. Journal of Quality Technology, 43 (4), 334-345.

Reliability Engineering:

    • Wei, Y., Pan, E., and Ye Z.S. (2024). Condition monitoring based on corrupted multiple time series with common trends. Reliability Engineering & System Safety, 251, 110324.
    • Wei, Y., Chen, Z., Ye Z.S. and Pan, E. (2024). High-dimensional process monitoring under time-varying operating conditions via covariate-regulated principal component analysis. Reliability Engineering & System Safety, 110440.
    • Yin, J., Ye, Z.S., & Cui, L. (2024). Reliability and Optimal Replacement Policy of a Multistate System Under Markov Renewal Shock Model. IEEE Transactions on Reliability.
    • Yan, J., Ye, Z. S., He, S., & He, Z. (2024). A feature disentanglement and unsupervised domain adaptation of remaining useful life prediction for sensor-equipped machines. Reliability Engineering & System Safety, 242, 109736.
    • Wang, L., Cao, H., Ye, Z.S., Xu, H., & Yan, J. (2024). DVGTformer: A dual-view graph Transformer to fuse multi-sensor signals for remaining useful life prediction. Mechanical Systems and Signal Processing, 207, 110935.
    • Kang, F., Cui, L., Ye, Z.S., & Zhou, Y. (2024). Reliability analysis for systems with self-healing mechanism in degradation-shock dependence processes with changing degradation rate. Reliability Engineering & System Safety, 241, 109671.
    • Wang, L., Cao, H., Ye, Z.S., and Xu, H. (2023) Bayesian Large-kernel Attention Network for Bearing Remaining Useful Life Prediction and Uncertainty Quantification, Reliability Engineering and System Safety, 238, 109421.
    • Yang, Y., Peng, J. C. H., & Ye, Z. S. (2023). Distributionally robust frequency dynamic constrained unit commitment considering uncertain demand-side resources. Applied Energy, 331, 120392.
    • Jiang, T., Liu, Y., & Ye, Z. S. (2023). A stochastic time scale based framework for system reliability under a Markovian dynamic environment. Naval Research Logistics (NRL), 70(4), 320-339.
    • Peng, W., Chen, Y., Xu, A., & Ye, Z. S. (2023). Collaborative online RUL prediction of multiple assets with analytically recursive Bayesian inference. IEEE Transactions on Reliability.
    • Liu, X., Wang, X., Xie, M., & Ye, Z. S. (2023). Robust degradation state identification in the presence of parameter uncertainty and outliers. IEEE Transactions on Industrial Informatics.
    • Wen, P., Ye, Z. S., Li, Y., Chen, S., Xie, P., & Zhao, S. (2023). Physics-informed neural networks for prognostics and health management of lithium-ion batteries. IEEE Transactions on Intelligent Vehicles.
    • Yu, Y., Qingyu Xiong, Ye, Z. S., Xingchen Liu, Qiude Li, Kai Wang (2022) A Review on Acoustic Reconstruction of Temperature Profiles: From Time Measurement to Reconstruction Algorithm. IEEE Transactions on Instrumentation and Measurement, to appear.
    • Rong Zhu; Yuan Chen; Peng, W.W., & Ye, Z. S. (2022) Bayesian Deep-Learning for RUL Prediction An Active Learning Perspective, Reliability Engineering and System Safety, to appear.
    • Yang, Y., Peng, J. C. H., Ye, C., & Ye, Z. S. (2022). Optimal Reserve Allocation With Simulation-driven Frequency Dynamic Constraint: A Distributionally Robust Approach. IEEE Transactions on Circuits and Systems II: Express Briefs, to appear.
    • Pan, TY., Chen, J., Ye, Z.S., Li, A. (2022) A Multi-Head Attention Network with Adaptive Meta-Transfer Learning for RUL Prediction of Rocket Engines, Reliability Engineering & System Safety, 225, 108610
    • Fallahi F., Bakir I., Yildirim M., Ye Z.S. (2022) A Chance-Constrained Optimization Framework for Wind Farms to Manage Fleet-Level Availability in Condition Based Maintenance and Operations Renewable and Sustainable Energy Reviews, 168, 112789.
    • Yang, Y., Raman, G., Peng, J. and Ye, Z.S. (2022) Resilient Consensus-based AC Optimal Power Flow against Data Integrity Attacks Using PLC, IEEE Transactions on Smart Grid, 3(5), 3786-3797.
    • Raed Kontar, Naichen Shi, Xubo Yue, Seokhyun Chung, Eunshin Byon, Mosharaf Chowdhury, Judy Jin, Wissam Kontar, Neda Masoud, Maher Noueihed, Chinedum E. Okwudire, Garvesh Raskutti, Romesh Saigal, Karandeep Singh, and Ye Z.S. (2022) The Internet of Federated Things (IoFT), IEEE access, 9, 156071 – 156113.
    • Wang, S. and Ye, Z.S. (2021) Distributionally Robust State Estimation for Linear Systems Subject to Uncertainty and Outlier. IEEE Transactions on Signal Processing, 70, 452-467..
    • Hu, J., Sun, Q., and Ye, Z. S. (2021) Replacement and Repair Optimization for Production Systems Under Random Production Waits. IEEE Transactions on Reliability, 71(4), 1488-1500.
    • Hu, J., Sun, Q., Ye, Z. S., and Ling, X. (2021) Sequential degradation-based burn-in test with multiple periodic inspections. Frontiers of Engineering Management, 8(4), 519-530.
    • Yang, Y.; Peng, J.C.H. and Ye, Z.S. (2021) A Market Clearing Mechanism Considering Primary Frequency Response Rate,” IEEE Transactions on Power Systems, Vol. 36, No. 6, pp. 5952-5955.
    • Yang, Y., Peng, J.C.H., Ye, C., Ye, Z.S. and Ding, Y (2021) A Criterion and Stochastic Unit Commitment towards Frequency Resilience of Power Systems. IEEE Transactions on Power Systems, 37(1), 640 – 652.
    • Cai, J. and Ye, Z.S. (2021). Optimal design of accelerated destructive degradation tests with block effects. IISE Transactions, 54(1), 73-90.
    • Cai, J. and Ye Z.S. (2021) Contamination Source Identification: A Bayesian Framework Integrating Physical and Statistical Models, IEEE Transactions on Industrial Informatics, 17(12), 8189 – 8197.
    • Liu, X., Du, J. and Ye, Z.S. (2021) A Condition Monitoring and Fault Isolation System for Wind Turbine based on SCADA Data, IEEE Transactions on Industrial Informatics, 18(2), 986 – 995.
    • Hu J., Sun, Q., Ye, Z.S., and Zhou, Q. (2020) Joint Modeling of Degradation and Lifetime Data for RUL Prediction of Deteriorating Products. IEEE Transactions on Industrial Informatics, 17(7), 4521-4531.
    • Guo, K., Ye, Z.S., Liu, D. and Peng, X. (2021) UAV flight control sensing enhancement with a data-driven adaptive fusion model. Reliability Engineering & System Safety, 213, 107654.
    • Liu, X., Sun Q., Ye, Z.S. and Yildirim, M. (2021) Optimal multi-type inspection policy for systems with imperfect online monitoring, Reliability Engineering & System Safety, 207, 107335.
    • Wang X. and Ye, Z.S. (2020) Design of customized two-dimensional extended warranties considering use rate and heterogeneity. IISE Transactions, 53(3), 341-351.
    • Hu, J., Sun, Q. and Ye, Z.S. (2021) Condition-based Maintenance Planning for Systems Subject to Dependent Soft and Hard Failures, IEEE Transactions on Reliability, 70(4), 1468 – 1480.
    • Gao L., Ye, Z.S., Chen, W., Qian P. and Pan J. (2020) Accelerated Life Test Planning for Minimizing Misclassification Risks, IEEE Transactions on Reliability, 70(2), 459-471.
    • Chen, P., Ye, Z. S., and Zhai, Q. (2020). Parametric Analysis of Time-Censored Aggregate Lifetime Data. IISE Transactions, 52(5), 516-527.
    • Sun, Q., Ye, Z.S. and Zhu, X. (2020) Managing component degradation in series systems for balancing degradation through reallocation and maintenance. IISE transactions, 52(7), 797-810.
    • Zhai Q. and Ye, Z.S. (2020) How reliable should military UAVs be?IISE Transactions, 52(11), 1234-1245.
    • Shen, J., Hu, J. and Ye, Z.S. (2020) Optimal switching policy for warm standby systems subjected to standby failure mode. IISE Transactions, 52(11), 1262-1274.
    • Yang, L., Sun, Q., and Ye, Z.S. (2019). Designing Mission Abort Strategies Based on Early-Warning Information: Application to UAV. IEEE Transactions on Industrial Informatics, 16(1), 277-287.
    • Peng, W., Ye, Z.S., and Chen, N. (2019). Bayesian Deep Learning based Health Prognostics Towards Prognostics Uncertainty. IEEE Transactions on Industrial Electronics, 67(3), 2283-2293..
    • Chen, P., Ye, Z.S., and Xiao, X. (2019) Pairwise Model Discrimination with Applications in Lifetime Distributions and Degradation Processes, Naval Research Logistics, 66(8), 675-686.
    • Sun, Q.Z., Ye, Z. S., Revie, M., and Walls, L. (2019). Reliability modelling of infrastructure load-sharing systems with workload adjustment. IEEE Transactions on Reliability, 68(4), 1283-1295.
    • Yang, L., Ye, Z.S., Lee, C.G., Yang, S. and Peng, R. (2019) A two-phase preventive maintenance policy considering imperfect repair and postponed replacement. European Journal of Operational Research, 274(3), 966-977.
    • Hong, L.Q., Wang, X., Zhai, Q and Ye, Z.S. (2018) System Reliability Evaluation under Dynamic Operating Conditions. IEEE Transactions on Reliability, 68(3), 800-809.
    • Sun, Q.Z, Ye, Z.S. and Peng W. (2018) Scheduling Preventive Maintenance Considering the Saturation Effect. IEEE Transactions on Reliability, 68(2), 741-752.
    • Peng, W, Ye, Z.S. and Chen, N. (2018) Joint Online RUL Prediction for Multi-Deteriorating Systems. IEEE Transactions on Industrial Informatics, 15(5), 2870-2878.
    • Hong, L.Q., Ye, Z.S. and Sari, J. (2018) Interval Estimation for Wiener Processes Based on Accelerated Degradation Test Data, IISE Transactions, 50(12), 1043-1057.
    • Raman, G., Kong, Y., Peng, J. and Ye, Z.S. (2018) Demand baseline estimation using similarity based technique for tropical and wet climates, IET Generation, Transmission & Distribution, 12(13), 3296-3304.
    • Sun, Q., Ye, Z.S., and Chen, N. (2018) Optimal Inspection and Replacement Policies for Multi-Unit Systems Subject to Degradation, IEEE Transactions on Reliability, 67(1), 401-413.
    • Chen, P. and Ye, Z.S. (2018) A systematic look at the gamma process capability indices. European Journal of Operational Research, 265(2), 589-597.
    • Zhai, Q. and Ye, Z.S. (2017) RUL prediction of deteriorating products using an adaptive Wiener process model, IEEE Transactions on Industrial Informatics, 13(6), 2911-2921.
    • Zhai, Q. and Ye, Z.S. (2017) Robust degradation analysis with non-Gaussian measurement errors, IEEE Transactions on Instrumentation & Measurement, 66(11), 2803-2812.
    • Wang, X., Xie, W., Ye, Z.S. and Tang, L.C. (2017) Aggregate discounted warranty cost forecasting considering the failed-but-not-reported events, Reliability Engineering & System Safety, 168, 355-364.
    • Zhang, C.W., Ye, Z.S. and Xie, M. (2017) Monitoring the shape parameter of the Weibull renewal process, IISE Transactions, 49(8), 800-813.
    • Kong Y. and Ye, Z.S. (2017) Goodness-of-fit tests in the multi-state Markov model, Reliability Engineering & System Safety, 166, 16-24.
    • Chen, P. and Ye, Z.S. (2017) Random Effects Models for Aggregate Lifetime Data, IEEE Transactions on Reliability, 66(1), 76-83.
    • Kong Y. and Ye, Z.S. (2017) Interval estimation for k-out-of-n load-sharing systems. IIE Transactions, 49(3), 344-353.
    • Zhai, Q., Ye, Z.S. and Peng, R. (2017) Defense and attack of load-sharing common bus systems, European Journal of Operational Research, 256(3), 962-975.
    • Chen, P., Xu, A. and Ye, Z.S. (2016) Generalized fiducial inference for accelerated life tests with Weibull distribution and progressively Type-II censoring, IEEE Transactions on Reliability, 65(4), 1737-1744.
    • Kong Y. and Ye, Z.S. (2016) A cumulative-exposure-based algorithm for failure data From a load-sharing system, IEEE Transactions on Reliability, 65(2), 1001-1013.
    • Zhai, Q., Ye, Z.S., Yang, J. and Zhao, Y. (2016) Measurement errors in degradation-based burn-in, Reliability Engineering & System Safety, 150, 126-135.
    • Chen, N.; Tang, Y., and Ye, Z.S.(2016) Robust quantile analysis for accelerated life test data, IEEE Transactions on Reliability, 65(2), 901-913.
    • Xiao X. and Ye, Z.S. (2016) Optimal design for destructive degradation tests with random initial degradation values using the Wiener process, IEEE Transactions on Reliability, 65(3), 1327-1342.
    • Xie, W. and Ye, Z.S. (2016) Aggregate discounted warranty cost forecast for a new product considering stochastic sales, IEEE Transactions on Reliability, 65(1), 486-497.
    • Ye, Z.S. and Murthy D.N.P. (2016) Warranty menu design for a two-dimensional warranty. Reliability Engineering & System Safety, 155, 21-29.
    • Ye, Z.S., Chen, N., and Shen, Y. (2015) A new class of Wiener process models for degradation analysis, Reliability Engineering & System Safety, 139, 58-67.
    • Ye, Z.S. and Xie, M. (2015) Stochastic modelling and analysis of degradation for highly reliable products. Applied Stochastic Models in Business and Industry, 31 (1), 16-36.
    • Chen, N., Ye, Z.S., Xiang, Y., and Zhang, L. (2015) Condition-based Maintenance using the Inverse Gaussian Degradation Model, European Journal of Operational Research, 243 (1), 190199.
    • Zhang, M., Ye, Z.S. and Xie, M. (2014) A condition-based maintenance strategy for heterogeneous populations. Computers & Industrial Engineering, 77, 103-114.
    • Shen, Y. and Ye, Z.S. (2014) On the behaviours of the percentile residual life for components and for k-out-of-n systems. Probability in the Engineering and Informational Sciences, 29 (02), 291-308.
    • Zhang, M.M.; Ye, Z.S. and Xie, M. (2014) Statistical inferences of progressively censored data with the stochastic EM algorithm. Quality & Reliability Engineering International, 30 (5), 711-722
    • Ye, Z.S.; Walls, L. and Revie, M. (2014) A load sharing system reliability model with managed component degradation. IEEE Transactions on Reliability, 63(3), 721-730.
    • Ye, Z.S.; Chen, L.P.; Tang, L.C. and Xie, M. (2014) Accelerated degradation test planning using the inverse Gaussian process. IEEE Transactions on Reliability, 63(3), 750-763.
    • Ye, Z.S.; Chan, P.S.; Xie, M. and Ng, H.K.T. (2014) Statistical inference for the extreme value distribution under adaptive Type-II progressive censoring schemes. Journal of Statistical Computation and Simulation, 84(5), 1099-1114.
    • Wang, Y; Ye, Z.S. and Tsui, K.L. (2014) Stochastic evaluation of magnetic head wears in hard disk drives. IEEE Transactions on Magnetics, 50 (5), 3301507.
    • Ye, Z.S., Li, J.G. and Zhang M. (2014) Statistical methods for design and production of alloy wheels. Journal of Applied Statistics, 41 (7), 1436-1452.
    • Ye, Z.S.; Chen, N. and Tsui, K.L. (2014) A Bayesian approach to condition monitoring with imperfect inspections. Quality & Reliability Engineering International, 31 (3), 513-522.
    • Ye, Z.S.; Tang, L.C. and Xie, M. (2014) Bi-objective burn-in modeling and optimization. Annals of Operations Research, 212(1), 201-214.
    • Chen, L.P.; Ye, Z.S. and Xie, M. (2013) Joint maintenance and spare component provisioning policy for k-out-of-n Asia Pacific Journal of Operational Research, 30(6), 1350023.
    • Ye, Z.S. (2013) On the conditional increments of degradation processes. Statistics & Probability Letters, 83 (11), 2531-2536.
    • Ye, Z.S.; Wang, Y.; Tsui, K.L and Pecht, M. (2013) Degradation data analysis using Wiener processes with measurement errors. IEEE Transactions on Reliability, 62 (4), 772-780.
    • Ye, Z.S.; Xie, M. and Tang, L.C. (2013) Reliability evaluation of hard disk drive failures based on counting processes. Reliability Engineering & System Safety, 109, 110-118.
    • Ye, Z.S.; Murthy, D.N.P.; Xie, M. and Tang, L.C. (2013) Optimal burn-in for repairable products sold with a two-dimensional warranty. IIE Transactions, 45 (2), 164-176.
    • Ye, Z.S.; Shen, Y. and Xie, M. (2012) Degradation-based burn-in with preventive maintenance. European Journal of Operational Research, 221 (2), 360-367.
    • Ye, Z.S.; Tang, L.C. and Xu, H.Y. (2011) A distribution-based systems reliability model under extreme shocks and natural degradation. IEEE Transactions on Reliability, 60 (1), 246-256.
    • Ye, Z.S.; Li, Z.Z. and Xie, M. (2010) Some improvements on adaptive genetic algorithms for reliability-related applications. Reliability Engineering & System Safety, 95 (2), 120-126.
    • Huang, B. and Ye, Z.S. (2010) The effects of lumpy demand and shipment size constraint. Decision Support Systems, 48 (2), 421-425.