张晓红
教授、博士生导师、硕士生导师
地址: 太原市万柏林区窊流路66号
邮编: 030024
Email: zhangxh@tyust.edu.cn
专业背景
机械设计及理论博士；计算机应用技术硕士
研究领域
复杂系统故障预测与健康管理；工业大数据与智能运维
讲授课程
数据结构；人工智能；智能制造概论；可靠性数学概论；故障预测与健康管理
支持和主要参与科研项目
[1] 国家自然科学基金面上项目:考虑预测可信度评估的多部件系统预测维修与备件库存联合决策研究(72071183)
[2] 国家自然科学基金青年项目:可修多部件系统视情非完美维修及其与备件库存的联合决策研究(71701140)
[3] 国家自然科学基金面上项目:复杂多部件系统视情维修及其与备件库存联合决策的建模与优化研究(61573250)
[4] 山西省科技创新人才团队:复杂装备故障预测与健康管理 (202304051001032）
[5] 山西省科技重大专项计划课题: 基于大数据和深度学习的智慧发电全负荷优化技术研究
[6] 山西省重点研发计划项目课题: 轧机减速机关键运行参数的智能化多模在线监测技术
[7] 山西省重点研发计划项目课题:风电机组大数据应用服务系统设计与开发
[8] 山西省高等学校人文社会科学重点研究基地项目:大数据产业与装备制造业融合创新发展路径研究(20220123)
[9] 山西省自然科学基金面上项目:随机环境影响的多性能退化系统剩余寿命预测及维修决策研究(202203021211194)
[10] 山西省青年科技研究基金:面向轧辊的可修多部件系统最优视情更换与备件库存联合优化研究(201601D021082)
[11] 山西省回国留学人员科研资助项目:考虑可信度评估的多性能退化系统剩余寿命预测与维修决策(2022-161)
[12] 山西省高等学校科学研究优秀成果培育项目:复杂多部件系统视情机会维修与备件库存联合决策研究(2019SK028)
[13] 山西省高等学校科技创新项目:基于服务质量评估的租赁系统最优维护方案决策研究(201802091)
[14] 山西省教学改革创新项目:新工科建设背景下工业工程专业创新人才培养模式研究(J20220716)
代表性学术论文
[1] Mechanism data-driven modeling of stochastic wear and degradation of rolls in hot finishing mill, Wear, 2025, 568-569: 205926. (通讯作者,SCI: Q1)
[2] Six-Dimensional Digital Twin Modeling and Software Platform Design for Complex Industrial Systems, Journal of Intelligent Manufacturing, , 2025: 1-22 (SCI: Q1)
[3] Integrated decision of production scheduling and condition-based maintenance planning for multi-unit systems with variable replacement thresholds, Journal of Manufacturing Systems, 2024(74): 647–664. (通讯作者,SCI: Q1)
[4] A chance-constrained net revenue model for online dynamic predictive maintenance decision-making, Reliability Engineering & System Safety, 2024, 110233. (通讯作者,SCI: Q1)
[5] Real-Time Evaluation of the Credibility of Remaining Useful Life Prediction Result, IEEE Transactions on Reliability, 2024. 73(3): 1606-1618. (通讯作者,SCI: Q1)
[6] Failure Mode Division and Remaining Useful Life Prognostics of Multi-indicator Systems with Multi-fault, Reliability Engineering & System Safety, 2024, 109961, (通讯作者,SCI: Q1)
[7] Multiple-failure mode division and condition-based maintenance decision making for systems with multi-indicator performance degradation. Computers & Industrial Engineering, 2024. 191: 110118. (第一作者,SCI: Q1)
[8] Optimal switching and condition-based maintenance of cold standby systems subject to competitive failure and imperfect switchover. Journal of the Operational Research Society, 2024, 75(5): 982-999. (通讯作者,SCI)
[9] Degradation modeling and remaining life prediction of multi-state long-life systems under random environmental influences, MeasurementSCIence and Technology 2024, 35(9): 095110. (通讯作者,SCI)
[10] Remaining Useful Life Prediction of Weighted k-out-of-n Systems Based on Dynamic Random Weights of Importance, Computers & Industrial Engineering, 2023, 183: (通讯作者,SCI: Q1)
[11] Reliability Analysis of Mining Machinery Pick Subject to Competing Failure Processes With Continuous Shock and Changing Rate Degradation. IEEE Transactions on Reliability, 2023. 72(2): 795-807. (通讯作者,SCI: Q1)
[12] Remaining useful life prediction for complex systems with multiple indicators of stochastic correlation considering random shocks. Mechanical Systems and Signal Processing, 2023. 204: 110767. (SCI: Q1)
[13] Dynamic group-maintenance strategy for wind farms based on imperfect maintenance model. Ocean Engineering, 2022, 259: 111311. (通讯作者,SCI)
[14] Joint decision of condition-based opportunistic maintenance and scheduling for multi-component production systems, International Journal of Production Research, 2021: 1-10. (通讯作者,SCI: Q1)
[15] Optimal Condition-based Opportunistic Maintenance and Spare Parts Provisioning for a Two-unit System using a State Space Partitioning Approach. Reliability Engineering & System Safety, 2021,209: 107451. (第一作者,SCI: Q1)
[16] Optimal dynamic imperfect preventive maintenance of wind turbines based on general renewal processes. International Journal of Production Research. 2020. 58(22): 6791-6810 (通讯作者,SCI: Q1)
[17] Lessees’ satisfaction and optimal condition-based maintenance policy for leased system. Reliability Engineering and System Safety. 2019, 191: 106532. (通讯作者,SCI: Q1)
[18] Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems. European Journal of Operational Research, 2017, 262(2): 479-498. (第一作者,SCI: Q1)
[19] A General Modeling Method for Opportunistic Maintenance Modeling of Multi-unit Systems. Reliability Engineering & System Safety, 2015. 140: 176-190. (第一作者,SCI: Q1)
[20] Deterioration state space partitioning method for opportunistic maintenance modelling of identical multi-unit systems. International Journal of Production Research, 2015. 53(7): 2100-2118. (第一作者,SCI: Q1)
[21] Joint Sequential Decision of Maintenance and Spare Parts Inventory for Multi-unit Repairable Systems. International Journal of Reliability and Safety, 2025, 19(1): 22-59. (第一作者, EI)
[22] Joint Optimization and Termination of Sequential Prediction Maintenance and Spare Parts Ordering under Dynamic Remaining Useful Time Prediction, 2023 5th International Conference on System Reliability and Safety Engineering, (SRSE 2023), 2023: 274-279. (通讯作者, EI)
[23] 冷/温混合贮备系统最优切换及视情维修决策.控制与决策,2024,39(6):2069-2078. (第一作者, EI)
[24] 相依多模失效下冷贮备系统最优切换及视情维护决策.控制与决策,2023,38(09):2672-2680. (第一作者, EI)
[25] 基于多状态空间划分的风电机组非完美维修决策. 太阳能学报, 2022, 43(11): 203-214. (第一作者, EI)
[26] 基于多状态劣化空间划分的多部件系统维修决策. 计算机集成制造系统, 2022.28(3):769-779.(第一作者, EI)
[27] 加速冲击损伤退化系统剩余寿命预测及预测维修决策. 控制与决策, 2022. 37(10): 2647-2656. (通讯作者, EI)
[28] 基于马尔可夫过程的多部件系统劣化状态空间划分模型. 控制与决策, 2021. 36(2): 418-428. (第一作者, EI)
[29] 基于状态空间划分的可修系统视情维修决策. 系统工程理论与实践, 2020, 40(5): 1350-1360 (通讯作者, EI)
[30] 基于退化状态空间划分的风电机组视情维修决策. 控制与决策, 2019. 34(9): 1909–1916. (第一作者, EI)
专利
[1] 一种旋转机械在线RUL预测结果实时可信度评估方法
[2] 一种齿轮的实时剩余寿命预测方法
[3] 一种机械维修可靠性工作台
[4] 一种面向复杂系统场景的数字孪生平台构建方法
[5] 面向数字孪生平台的关系型和时序型数据库协同运行方法
专著
多部件系统维修与备件库存联合决策模型与方法. 科学出版社
荣誉奖励
[1] 山西省第十二次社会科学研究优秀成果二等奖, 2022.11
[2] 2021年度“百部(篇)工程”一等奖, 2021.6
[3] 山西省第十一次社会科学研究优秀成果二等奖, 2020.11
[4] 2019年山西省高等学校科学研究优秀成果一等奖, 2019.03
[5] 2017年度“百部(篇)工程”二等奖, 2018.11
研究生招生专业
现任威廉希尔williamhill管理科学与工程学科、工业工程学科硕士生导师，控制科学与工程学科博士生导师。
