个人简介
教育背景
2007-2011 香港大学 工业及制造系统工程 博士
2004-2006 清华大学 自动化 硕士
2000-2004 上海交通大学 船舶与海洋工程 学士
工作经历
2019.12-今 上海交通大学，工业工程与管理系，系副主任（分管科研）
2017.12-今 上海交通大学，机械与动力工程学院，副教授，博士生导师
2014.07-2017.12 上海交通大学，机械与动力工程学院，讲师
出访及挂职经历
2016.05-2016.11 中航商用航空发动机制造有限责任公司 工艺技术主管
2018.03-2019.03 上海市临港地区智能制造专项办公室 主任助理
科研项目
2022-2023 商用飞机系统工程中心联合基金项目：“大数据驱动的飞机装配大纲精准执行方法”，负责人。
2020-2022 上海市“科技创新行动计划”：“飞机移动对接位姿追踪与精确测量技术研究”，负责人。
2020-2021 国防基础科研计划：“基于大数据的航空复杂结构件加工车间决策优化技术”，单位负责人。
2019-2022 国家重点研发计划课题：“业务驱动的超大型集装箱码头智能化作业规划与决策技术”，负责人。
2018-2021 国家自然科学基金面上项目：“基于复杂网络理论的晶圆制造自动化物料运输系统动态调度方法”，负责人。
2017-2020 航天先进制造技术联合基金重点项目：“面向智慧工厂的防空导弹结构件混线生产实时优化协同管理”，单位负责人。
2017-2019 工信部智能制造新模式与新标准项目：“空心胶囊智能制造新模式应用项目”，单位负责人。
2017-2018 上海航天科技创新基金：“基于三维设计模型的航天复杂舱体结构制造特征网络模型构建方法”，负责人。
2016-2018 工信部智能制造新模式与新标准项目：“中医药产品智能制造新模式应用项目”，单位负责人。
2016-2018 临港地区智能制造产业专项：“圆柱形电芯动力电池组智能化生产车间”，单位负责人。
2016-2017 微软委托项目：“微软制造执行系统”，负责人。
2016-2017 玉柴委托项目：“数据驱动的柴油发动机功率一致性分析与多参数控制方法“，负责人。
2015-2017 国家科技支撑计划：“食品无菌纸盒包装机器人自动化生产线”，单位负责人。
2014-2016 国家自然科学基金青年项目：“状态参数驱动的晶圆制造系统建模与性能预测方法研究”，负责人。
2013-2015 中国博士后基金：“基于无尺度网络和系统动力学的晶圆制造系统建模方法”，负责人。
2012-2014 上海市“科技创新行动计划”:“面向复杂产品制造过程的精确控制技术研究”，单位负责人。
专著：
[1] 秦威. 面向智能制造的机器智能理论与方法 [M]. 电子工业出版社, 2020. （已签约，撰稿中）
[2] 张洁, 秦威, 高亮. 大数据驱动的智能车间运行分析与决策方法 [M]. 华中科技大学出版社. 2020.
[3] 张小红, 秦威. 智能制造导论 [M]. 上海交通大学出版社, 2019.
[4] Jie Zhang, Wei Qin, Lihui Wu, Junliang Wang, Youlong Lv and Xiaoxi Wang. Wafer Fabrication: Automatic Materiel Handling System [M]. Walter de Gruyter GmbHr, 2018.
[5] 张洁, 秦威. 制造系统智能调度方法与云服务 [M]. 华中科技大学出版社, 2018.
[6] 张洁, 秦威, 鲍劲松. 制造业大数据 [M]. 上海科学技术出版社, 2016.
[7] 张洁, 秦威, 吴立辉. 晶圆制造自动化物料运输系统调度 [M]. 华中科技大学出版社, 2015.
教学工作
本科生课程：大数据分析与机器智能、运筹学
研究生课程：大数据分析
软件版权登记及专利
专利：
[1] 基于堆叠残差因果卷积神经网络的锂电池健康状态检测方法，专利号：ZL202010689054.9
[2] 基于注意力机制的高炉热负荷异常状态监测方法，公开号：CN114015825A
[3] 工业软测量中考虑因果效应的辅助变量选择方法，公开号：CN113821982A
[4] 可解释集成学习的间歇过程质量在线预测方法，公开号：CN113807606A
[5] 基于超启发式算法的自动化码头出口箱箱位分配优化方法，公开号：CN112598255A
[6] 两阶段的面向复杂约束下的钢铁企业设备检修调度方法，公开号：CN111950786A
软著：
[1] New Master 智能制造执行系统，登记号：2016SR323633
[2] New Master制造执行系统，登记号：2016SR107234
[3] 面向多制造过程的调度算法库与插件平台，登记号：2014SR026660
[4] 混流装配生产线工艺发布和质量自检系统，登记号：2013SR114322
[5] 航空复杂结构件加工工艺与生产调度优化软件，登记号：2021SR1694944
[6] 三维工序模型数控程序快速生成系统， 登记号：2020SR0968323
[7] 自动化集装箱码头车辆动态自适应调配优化软件, 登记号：2022SR0965154
荣誉奖励
2021 “一汽丰田杯”中国工业工程与精益管理创新大赛 一等奖（指导教师）
2021 上海交通大学教学成果奖 一等奖
2020 “一汽丰田杯”中国工业工程与精益管理创新大赛 一等奖（指导教师）
2019 上海交通大学机械与动力工程学院青年教师教学竞赛 一等奖
2017 上海交通大学教职工年度考核 优秀
2017 上海交通大学机械与动力工程学院非全日制专业学位研究生教育“优秀论文指导教师”
2014 上海交通大学“优秀班主任”
2009 香港“U-21 RFID技术应用创新奖”
2008 香港大学 University Postgraduate Fellowships
近期论文
查看导师新发文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
SCI论文：
2023年
[1] Xu H W, Qin W*, Sun Y N, et al. Attention mechanism-based deep learning for heat load prediction in blast furnace ironmaking process[J]. Journal of Intelligent Manufacturing, 2023: 1-14.
2022年
[1] Sun Y-N, Qin W*, Xu H-W, et al. A multiphase information fusion strategy for data-driven quality prediction of industrial batch processes [J]. Information Sciences, 2022, 608: 81-95.
[2 ]Xu H-W, Qin W*, Lv Y-L, et al. Data-Driven Adaptive Virtual Metrology for Yield Prediction in Multi-Batch Wafers[J]. IEEE Transactions on Industrial Informatics, 2022. doi:10.1109/TII.2022.3162268.
[3] Qin W*, Zhuang Z, Liu Y, et al. Sustainable service oriented equipment maintenance management of steel enterprises using a two-stage optimization approach[J]. Robotics and Computer-Integrated Manufacturing, 2022, 75: 102311.
[4]Zhuang Z, Li Y, Sun Y, Qin W*, et al. Network-based dynamic dispatching rule generation mechanism for real-time production scheduling problems with dynamic job arrivals[J]. Robotics and Computer-Integrated Manufacturing, 2022, 73: 102261.
[5]Zhuang Z, Zhang Z, Teng H, Qin W*, et al. Optimization for integrated scheduling of intelligent handling equipment with bidirectional flows and limited buffers at automated container terminals[J]. Computers & Operations Research, 2022: 105863.
[6]Qin W*, Hu Q, et al. A novel 6D pose estimation method for texture-less and occluded industrial parts. Journal of Intelligent Manufacturing, 2022.
2021年
[1] Qin W*, Sun Y N, Zhuang Z L, et al. Multi-agent reinforcement learning-based dynamic task assignment for vehicles in urban transportation system[J]. International Journal of Production Economics, 2021, 240: 108251.
[2] Qin W*, Zhuang Z, Guo L, et al. A hybrid multi-class imbalanced learning method for predicting the quality level of diesel engines[J]. Journal of Manufacturing Systems, 2022, 62: 846-856.
[3] Qin W*, Zhuang Z, Zhou Y, et al. Dynamic dispatching for interbay automated material handling with lot targeting using improved parallel multiple-objective genetic algorithm[J]. Computers & Operations Research, 2021, 131: 105264.
[4] Qin W*, Zhuang Z, Huang Z, et al. A novel reinforcement learning-based hyper-heuristic for heterogeneous vehicle routing problem[J]. Computers & Industrial Engineering, 2021, 156: 107252.
[5] Qin W*, Zhuang Z, Guo L, et al. A hybrid multi-class imbalanced learning method for predicting the quality level of diesel engines[J]. Journal of Manufacturing Systems, 2022, 62: 846-856.
[6] Sun Y N, Zhuang Z L, Xu H W, Qin W* et al. Data-driven modeling and analysis based on complex network for multimode recognition of industrial processes[J]. Journal of Manufacturing Systems, 2022, 62: 915-924.
[7] Sun Y N, Qin W*, Zhuang Z L. Nonparametric-copula-entropy and network deconvolution method for causal discovery in complex manufacturing systems[J]. Journal of Intelligent Manufacturing, 2021, 1-15.
[8] Sun Y N, Qin W*, Zhuang Z L, Xu H W. An adaptive fault detection and root-cause analysis scheme for complex industrial processes using moving window KPCA and information geometric causal inference[J]. Journal of Intelligent Manufacturing, 2021, 32: 2007-2021.
2020年
[1] Zhuang Z, Huang Z, Sun Y, Qin W*, et al. Optimization for cooperative task planning of heterogeneous multi-robot systems in an order picking warehouse[J]. Engineering Optimization, 2021, 53(10): 1715-1732.
[2] Zhuang Z, Chen Y, Sun Y, and Qin W*. Complex scheduling network: an objective performance testing platform for evaluating vital nodes identification algorithms [J]. The International Journal of Advanced Manufacturing Technology. 2020, 111: 273–282.
[3] Zhuang Z, Guo L, Huang Z, Qin W*,et al. DyS-IENN: a novel multiclass imbalanced learning method for early warning of tardiness in rocket final assembly process[J]. Journal of Intelligent Manufacturing, 2021, 32(8): 2197-2207.
[4] Datta N, Zhuang Z, Qin W*. Experimental study of a liquid desiccant regeneration system: performance analysis for high feed concentrations[J]. Clean Technologies and Environmental Policy, 2020, 22(6): 1255-1267.
2019年
[1] Qin W*, Lv H, Liu C, et al. Remaining useful life prediction for lithium-ion batteries using particle filter and artificial neural network [J]. Industrial Management & Data Systems. 2019.
[2] Qin W*, Zhuang Z, Liu Y, et al. A two-stage ant colony algorithm for hybrid flow shop scheduling with lot sizing and calendar constraints in printed circuit board assembly[J]. Computers & Industrial Engineering, 2019, 138: 106115.
[3] Zhuang Z, Lv H, Xu J, Huang Z, and Qin W*. A Deep Learning Method for Bearing Fault Diagnosis through Stacked Residual Dilated Convolutions [J]. Applied Sciences, 2019, 9(9), 1823.
[4] Zhuang Z, Lu Z, Huang Z, Liu C, and Qin W*. A novel complex network based dynamic rule selection approach for open shop scheduling problem with release dates [J]. Mathematical Biosciences and Engineering, 2019, 16(5): 4491-4505.
2018年
[1] Qin W*, Zha D, Zhang J. An effective approach for causal variables analysis in diesel engine production by using mutual information and network deconvolution[J]. Journal of Intelligent Manufacturing, 2020, 31(7): 1661-1671.
[2] Qin W*, Zhang J, and Song D.L. An improved ant colony algorithm for dynamic hybrid flow shop scheduling with uncertain processing time [J]. Journal of Intelligent Manufacturing. 2018, 29(4): 891-904.
[3] Jahanshahi P, Qin W*, Zhang J, and Erfan Z. Designing a non-invasive surface acoustic resonator for ultra-high sensitive ethanol detection for an on-the-spot health monitoring system [J]. Biotechnology and Bioprocess Engineering. 2018, 23(4), 394-404.
[4] Lv Y, Qin W, Yang J and Zhang J*. (2018). Adjustment mode decision based on support vector data description and evidence theory for assembly lines. Industrial Management & Data Systems, 118(8), 1711-1726.
[5] Wang J, Zheng P, Qin W, et al. A novel resilient scheduling paradigm integrating operation and design for manufacturing systems with uncertainties[J]. Enterprise Information Systems, 2019, 13(4): 430-447.
2017年
[1] W.Qin*, Ray.Y.Zhong, H.Y.Dai, and Z.L.Zhuang. An Assessment Model for RFID Impacts on Prevention and Visibility of Inventory Inaccuracy Presence [J]. Advanced Engineering Informatics. 2017, 34: 70-79.
[2] Lv Y, Zhang J, Qin W. A genetic regulatory network-based method for dynamic hybrid flow shop scheduling with uncertain processing times[J]. Applied sciences, 2017, 7(1): 23.
[3] Lv Y, Zhang J*, Qin W. A genetic regulatory network-based sequencing method for mixed-model assembly lines [J]. Advances in Production Engineering & Management. 2017, 12(1): 62-74.
[4] Pan C, Zhang J*, Qin W. Real-time OHT Dispatching Mechanism for the Interbay Automated Material Handling System with Shortcuts and Bypasses [J]. Chinese Journal of Mechanical Engineering. 2017, 30(3): 663-675.
2016年及之前
[1] P.Jahanshahi*, W.Qin, J.Zhang, M.Ghomeishi, S.D.Sekaran, and F.R.Mahamd Adikan. Kinetic analysis of IgM monoclonal antibodies for determination of dengue sample concentration using SPR technique [J]. Bioengineered. 2015, 8(3): 239-247.
[2] J.Zhang*, W.Qin, and L.H.Wu. A performance analytical model of automated material handling system for semiconductor wafer fabrication system [J]. International Journal of Production Research. 2015, 54(6): 1650-1669.
[3] J.Zhang*, W.Qin, L.H.Wu, and W.B.Zhai. Fuzzy neural network-based rescheduling decision mechanism for semiconductor manufacturing [J]. Computers in Industry. 2014, 65:1115-1125.
[4] W.Qin, J.Zhang*, and Y.B.Sun. Multiple-objective scheduling for interbay AMHS by using genetic-programming-based composite dispatching rules generator [J]. Computers in Industry. 2013, 64(6): 694-707.
[5] W.Qin, J.Zhang*, and Y.B.Sun. Dynamic dispatching for interbay material handling by using modified Hungarian algorithm and fuzzy-logic-based control [J]. International Journal of Advanced Manufacturing Technology. 2013, 67(1): 295-309.
[6] Qu, T., Yang, H. D., Huang, G. Q., Zhang, Y. F., Luo, H., & Qin, W. (2012). A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers. Journal of Intelligent Manufacturing, 23(6), 2343-2356.
[7] W.Qin, and Geroge.Q.Huang*. A Two-Level Genetic Algorithm for Scheduling in Assembly Islands with Fixed-Position Layouts [J]. Journal of System Science and System Engineering. 2010, 19(2): 150-161.
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