香港大學(xué) 工業(yè)及制造系統(tǒng)工程 博士
清華大學(xué) 自動化 碩士
上海交通大學(xué) 船舶與海洋工程 控制科學(xué)與工程 學(xué)士

2019.12-今 上海交通大學(xué)，工業(yè)工程與管理系，系副主任（分管科研）
2017.12-今 上海交通大學(xué)，機械與動力工程學(xué)院，副教授，博士生導(dǎo)師

復(fù)雜系統(tǒng)建模、控制與優(yōu)化；機器智能理論、方法與應(yīng)用

招收博士后、博士、碩士研究生，歡迎聯(lián)系報讀！

[1] Journal of Intelligent Manufacturing，副主編
[2] 工業(yè)工程與管理期刊，編委
[3] 中國機械工程學(xué)會工業(yè)大數(shù)據(jù)與智能系統(tǒng)分會，副總干事
[4] 中國機電一體化技術(shù)應(yīng)用協(xié)會工業(yè)大數(shù)據(jù)分會，秘書長
[5] Journal of Intelligent Manufacturing：“Operations Research in Machine Intelligence”—— Lead Guest Editor
[6] International Journal of Computer Integrated Manufacturing：“Data-Driven Modeling and Analytics for Optimization of Complex Manufacturing Systems”—— Lead Guest Editor
[7] Journal of Cleaner Production：“Sustainable product lifecycle management based on smart enabling technologies”—— Special Issue Organizer

2023-2026 科技創(chuàng)新2030——“新一代人工智能”重大項目課題：“數(shù)據(jù)驅(qū)動的超大型碼頭智能分析與運籌優(yōu)化理論研究”，負責(zé)人
2022-2023 商用飛機系統(tǒng)工程中心聯(lián)合基金項目：“大數(shù)據(jù)驅(qū)動的飛機裝配大綱精準執(zhí)行方法”，負責(zé)人。
2020-2022 上海市“科技創(chuàng)新行動計劃”：“飛機移動對接位姿追蹤與精確測量技術(shù)研究”，負責(zé)人。
2020-2021 國防基礎(chǔ)科研計劃：“基于大數(shù)據(jù)的航空復(fù)雜結(jié)構(gòu)件加工車間決策優(yōu)化技術(shù)”，單位負責(zé)人。
2019-2022 國家重點研發(fā)計劃課題：“業(yè)務(wù)驅(qū)動的超大型集裝箱碼頭智能化作業(yè)規(guī)劃與決策技術(shù)”，負責(zé)人。
2018-2021 國家自然科學(xué)基金面上項目：“基于復(fù)雜網(wǎng)絡(luò)理論的晶圓制造自動化物料運輸系統(tǒng)動態(tài)調(diào)度方法”，負責(zé)人。
2017-2020 航天先進制造技術(shù)聯(lián)合基金重點項目：“面向智慧工廠的XXXX結(jié)構(gòu)件混線生產(chǎn)實時優(yōu)化協(xié)同管理”，單位負責(zé)人。
2017-2019 工信部智能制造新模式與新標準項目：“空心膠囊智能制造新模式應(yīng)用項目”，單位負責(zé)人。
2017-2018 上海航天科技創(chuàng)新基金：“基于三維設(shè)計模型的航天復(fù)雜艙體結(jié)構(gòu)制造特征網(wǎng)絡(luò)模型構(gòu)建方法”，負責(zé)人。
2016-2018 工信部智能制造新模式與新標準項目：“中醫(yī)藥產(chǎn)品智能制造新模式應(yīng)用項目”，單位負責(zé)人。
2016-2018 臨港地區(qū)智能制造產(chǎn)業(yè)專項：“圓柱形電芯動力電池組智能化生產(chǎn)車間”，單位負責(zé)人。
2016-2017 微軟委托項目：“微軟制造執(zhí)行系統(tǒng)”，負責(zé)人。
2016-2017 玉柴委托項目：“數(shù)據(jù)驅(qū)動的柴油發(fā)動機功率一致性分析與多參數(shù)控制方法“，負責(zé)人。
2015-2017 國家科技支撐計劃：“食品無菌紙盒包裝機器人自動化生產(chǎn)線”，單位負責(zé)人。
2014-2016 國家自然科學(xué)基金青年項目：“狀態(tài)參數(shù)驅(qū)動的晶圓制造系統(tǒng)建模與性能預(yù)測方法研究”，負責(zé)人。
2013-2015 中國博士后基金：“基于無尺度網(wǎng)絡(luò)和系統(tǒng)動力學(xué)的晶圓制造系統(tǒng)建模方法”，負責(zé)人。
2012-2014 上海市“科技創(chuàng)新行動計劃”:“面向復(fù)雜產(chǎn)品制造過程的精確控制技術(shù)研究”，單位負責(zé)人。

SCI論文：
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.
[2] Zhu J Y, Qin W*,  Hu J H, et al. Influential process nodes identification strategy for aircraft assembly system based on complex network and improved PageRank[J]. Advanced Engineering Informatics, 2023:1-14.
[3] Qin W*, Zhuang Z, Sun Y, et al. An available-to-promise stochastic model for order promising based on dynamic resource reservation policy[J]. International Journal of Production Research, 2023, 61(16): 5525-5542.
[4] Qin W*, Hu Q, Zhuang Z*, et al. IPPE-PCR: a novel 6D pose estimation method based on point cloud repair for texture-less and occluded industrial parts[J]. Journal of Intelligent Manufacturing, 2023, 34(6): 2797-2807.
[5] Sun Y N, Chen Q L, Hu J H, Qin W*, et al. An integrated CRN-SVR approach for the quality consistency improvement in a diesel engine assembly process[J]. International Journal of Computer Integrated Manufacturing, 2023: 1-16.
[6] Sun Y N, Qin W, Hu J H, et al. A causal model-inspired automatic feature-selection method for developing data-driven soft sensors in complex industrial processes[J]. Engineering, 2023, 22: 82-93.


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.

專著：
[1] 秦威. 面向智能制造的機器智能理論與方法 [M]. 電子工業(yè)出版社, 2020. （已簽約，撰稿中）
[2] 張潔, 秦威, 高亮. 大數(shù)據(jù)驅(qū)動的智能車間運行分析與決策方法 [M]. 華中科技大學(xué)出版社. 2020.
[3] 張小紅, 秦威. 智能制造導(dǎo)論 [M]. 上海交通大學(xué)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] 張潔, 秦威. 制造系統(tǒng)智能調(diào)度方法與云服務(wù) [M]. 華中科技大學(xué)出版社, 2018.
[6] 張潔, 秦威, 鮑勁松. 制造業(yè)大數(shù)據(jù) [M]. 上海科學(xué)技術(shù)出版社, 2016.
[7] 張潔, 秦威, 吳立輝. 晶圓制造自動化物料運輸系統(tǒng)調(diào)度 [M]. 華中科技大學(xué)出版社, 2015.

專利：
[1] 基于堆疊殘差因果卷積神經(jīng)網(wǎng)絡(luò)的鋰電池健康狀態(tài)檢測方法，專利號：ZL202010689054.9
[2] 基于注意力機制的高爐熱負荷異常狀態(tài)監(jiān)測方法，公開號：CN114015825A
[3] 工業(yè)軟測量中考慮因果效應(yīng)的輔助變量選擇方法，公開號：CN113821982A
[4] 可解釋集成學(xué)習(xí)的間歇過程質(zhì)量在線預(yù)測方法，公開號：CN113807606A
[5] 基于超啟發(fā)式算法的自動化碼頭出口箱箱位分配優(yōu)化方法，公開號：CN112598255A
[6] 兩階段的面向復(fù)雜約束下的鋼鐵企業(yè)設(shè)備檢修調(diào)度方法，公開號：CN111950786A
[7] 自動化集裝箱碼頭全域集成網(wǎng)絡(luò)調(diào)度方法，公開號：CN115130316A
[8] 自動化集裝箱碼頭泊位和岸橋優(yōu)化分配方法，公開號：CN115713170A
[9] 基于動態(tài)規(guī)劃的集裝箱船舶配載箱位預(yù)留方法，公開號：CN115271140A
[10] 數(shù)據(jù)驅(qū)動的中醫(yī)藥制造過程工藝參數(shù)優(yōu)化方法，公開號：CN116414095A
[11] 數(shù)據(jù)驅(qū)動的基于不平衡裝配數(shù)據(jù)的發(fā)動機質(zhì)量預(yù)測方法，公開號：CN116541987A
[12] 一種發(fā)動機信息處理方法、裝置及設(shè)備，公開號：CN115496119A
[13] 一種圖像識別方法、裝置及電子設(shè)備，公開號：CN115719507A
軟著：
[1] New Master 智能制造執(zhí)行系統(tǒng)，登記號：2016SR323633
[2] New Master制造執(zhí)行系統(tǒng)，登記號：2016SR107234
[3] 面向多制造過程的調(diào)度算法庫與插件平臺，登記號：2014SR026660
[4] 混流裝配生產(chǎn)線工藝發(fā)布和質(zhì)量自檢系統(tǒng)，登記號：2013SR114322
[5] 航空復(fù)雜結(jié)構(gòu)件加工工藝與生產(chǎn)調(diào)度優(yōu)化軟件，登記號：2021SR1694944
[6] 三維工序模型數(shù)控程序快速生成系統(tǒng)， 登記號：2020SR0968323
[7] 自動化集裝箱碼頭車輛動態(tài)自適應(yīng)調(diào)配優(yōu)化軟件,  登記號：2022SR0965154
[8] 考慮船舶配積載和泊位配置的岸橋作業(yè)仿真系統(tǒng)，登記號：2023SR0340863