一、个人信息
姓名：周通
职称：讲师
电子邮箱：t.zh@njtech.edu.cn
二、教育背景及工作经历
2022.09-至今 南京工业大学智能制造研究院 讲师
2017.09-2022.06 南京航空航天大学 机械电子工程专业 工学博士
2019.10-2020.10 美国宾夕法尼亚州立大学 工业与制造工程专业 访问学者
2014.09-2017.06 江苏科技大学 机械制造及其自动化专业 工学硕士
2010.09-2014.06 江苏科技大学 机械设计制造及其自动化专业 工学学士
三、研究方向
智能制造系统; 深度强化学习; 智能生产决策; 工业物联网
四、主要项目经历
1. 面向自组织物联制造的复合智能体及其使能技术研究, 国家自然科学基金-面上项目, 2021.01-2024.12, 参与
2. 面向云定制的分布式智能产线协同智能集成技术, 国家重点研发计划项目, 中华人民共和国科学技术部, 2020.11-2023.11, 参与
3. 基于敏捷流程管理的自适应模块化生产系统, 国家重点研发计划项目, 中华人民共和国科学技术部, 2020.04-2023.03, 参与
五、主要研究成果
1. Tong Zhou, Dunbing Tang, Haihua Zhu, et al. Multi-agent reinforcement learning for online scheduling in smart factories [J]. Robotics and Computer-Integrated Manufacturing, 2021, 72: 102202. (SCI)
2. Tong Zhou, Dunbing Tang, Haihua Zhu, et al. Reinforcement learning with composite rewards for production scheduling in a smart factory [J]. IEEE Access, 2020, 9: 752-766. (SCI)
3. Tong Zhou, Haihua Zhu, Dunbing Tang, et al. Reinforcement learning for online optimization of job-shop scheduling in a smart manufacturing factory [J]. Advances in Mechanical Engineering, 2022, 14(3): 1-19. (SCI)
4. Yi Zhang, Haihua Zhu, Dunbing Tang, Tong Zhou, et al. Dynamic job shop scheduling based on deep reinforcement learning for multi-agent manufacturing systems [J]. Robotics and Computer-Integrated Manufacturing, 2022, 78: 102412. (SCI)
5. Changchun Liu, Haihua Zhu, Dunbing Tang, Qingwei Nie, Tong Zhou, et al. Probing an intelligent predictive maintenance approach with deep learning and augmented reality for machine tools in IoT-enabled manufacturing [J]. Robotics and Computer-Integrated Manufacturing, 2022, 77: 102357. (SCI)
6. Zequn Zhang, Dunbing Tang, Haihua Zhu, Tong Zhou, et al. A practical approach for multiagent manufacturing system based on agent computing nodes [J]. Part C: Journal of Mechanical Engineering Science, 2020: 0954406220908626. (SCI)
7. Liping Wang, Dunbing Tang, Hongwei Sun, Liangchuang Liao, Zequn Zhang, Tong Zhou, et al. Enabling technology of multiagent manufacturing system: a novel mode of self-organizing IoT manufacturing [J]. Transactions of Nanjing University of Aeronautics & Astronautics, 2021, 38(5): 876-892. (EI)
