人本智造单元中人-智能系统协同双智能体工作机制研究

doi:10.3901/JME.2025.03.105

机械工程学报 ›› 2025, Vol. 61 ›› Issue (3): 105-118.doi: 10.3901/JME.2025.03.105

• 特邀专栏：人机联合认知赋能的高端装备设计、制造与运维 • 上一篇

扫码分享

人本智造单元中人-智能系统协同双智能体工作机制研究

李嘉佳¹, 易茜¹, 冯毅雄², 朱鹏兴^1,3, 易树平¹

1. 重庆大学机械与运载工程学院重庆 400044;
2. 浙江大学流体动力基础与机电系统全国重点实验室杭州 310027;
3. 重庆大学高端装备机械传动全国重点实验室重庆 400044

收稿日期:2024-02-16 修回日期:2024-04-26 发布日期:2025-03-12
作者简介:李嘉佳，女，1992年出生，博士研究生。主要研究方向为数字化人因工程、人机交互行为模式、智能制造等。E-mail:lijiajia@cqu.edu.cn;易茜(通信作者)，女，1986年出生，博士，副教授。主要研究方向为绿色制造，智能制造系统，用户行为模式与可信交互等。E-mail:yiqian@cqu.edu.cn;冯毅雄，男，1975年出生，博士，教授，博士研究生导师。主要研究方向为人机交互与创新设计，人-信息-物理系统(HCPS)与数字孪生等。E-mail:fyxtv@zju.edu.cn;朱鹏兴，男，1993年出生，博士研究生。主要研究方向为人机交互、智能网联、智能制造等。E-mail:zhupengxing@cqu.edu.cn;易树平，男，1960年出生，博士，教授，博士研究生导师。主要研究方向为数字化人因工程、工业工程理论与技术、智能制造等。E-mail:yshuping@cqu.edu.cn
基金资助:
国家自然科学基金(52005062)、重庆市自然科学基金(CSTB2023NSCQ-MSX0390)和国家重点研发计划(2020YFB1711700)资助项目。

Research on Dual-agent Work Mechanism with Human-smart System Collaboration in Human-centric Smart Manufacturing Cell

LI Jiajia¹, YI Qian¹, FENG Yixiong², ZHU Pengxing^1,3, YI Shuping¹

1. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044;
2. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027;
3. State Key Laboratory of Mechanical Transmission for Advanced Equipment, Chongqing University, Chongqing 400044

Received:2024-02-16 Revised:2024-04-26 Published:2025-03-12

摘要/Abstract

摘要： 以技术驱动为主的智能制造单元面临着动态环境应对灵活性不足、非典型生产干扰应对困难、多场景集成决策受限等一系列挑战，为此，提出一种人本智造单元中人-智能系统协同的双智能体工作机制。分析以人为本的智能制造理念下制造单元的发展和演变过程，探索人与智能系统的有效协同途径，提出由增强感知、沟通交互、动态反馈、协同智能决策、持续学习和自适应构建的双智能体工作机制，并将其应用于故障诊断与排除这一非典型场景中，包括状态监测、故障诊断、故障排除、恢复与验证、持续学习与改进。以某重载车辆变速箱箱体智能制造单元的故障排除为案例，展示双智能体工作机制的有效性。

关键词: 人本智造, 人与智能系统协同, 智能制造, 制造单元, 故障诊断与排除

Abstract: The technology-driven smart manufacturing cell faces a series of challenges such as insufficient flexibility to cope with dynamic environments, difficulty in dealing with atypical production disturbances, and limited decision-making for multi-scenario integration. To this end, a dual-agent work mechanism for human-smart system collaboration in human-centric smart manufacturing cells is proposed. The development and evolution of the manufacturing cell under the concept of human-centric smart manufacturing is analyzed, and the effective ways of human-smart system collaboration are explored. A dual-agent work mechanism constructed by enhanced perception, communication and interaction, dynamic feedback, collaborative smart decision-making, continuous learning, and self-adaptation is proposed and applied to the atypical scenario of fault diagnosis and self-healing, which includes condition monitoring, fault diagnosis, fault repair, recovery and validation, and continuous learning and improvement. The fault repair of a smart manufacturing cell for a transmission case of a heavy-duty vehicle is used as a case study to demonstrate the effectiveness of the dual-agent work mechanism.

Key words: human-centric smart manufacturing, human-smart system collaboration, smart manufacturing, manufacturing cell, fault diagnosis and troubleshooting

中图分类号:

李嘉佳, 易茜, 冯毅雄, 朱鹏兴, 易树平. 人本智造单元中人-智能系统协同双智能体工作机制研究[J]. 机械工程学报, 2025, 61(3): 105-118.

LI Jiajia, YI Qian, FENG Yixiong, ZHU Pengxing, YI Shuping. Research on Dual-agent Work Mechanism with Human-smart System Collaboration in Human-centric Smart Manufacturing Cell[J]. Journal of Mechanical Engineering, 2025, 61(3): 105-118.

参考文献

[1] XU X，LU Y，VOGEL-HEUSER B，et al. Industry 4.0 and Industry 5.0—Inception，conception and perception[J]. Journal of Manufacturing Systems，2021，61:530-535.
[2] DIRECTORATE-GENERAL FOR RESEARCH AND INNOVATION (EUROPEAN COMMISSION)，BREQUE M，DE NUL L，et al. Industry 5.0:towards a sustainable，human centric and resilient European industry[M]. LU:Publications Office of the European Union，2021.
[3] WANG B，ZHENG P，YIN Y，et al. Toward human- centric smart manufacturing:A human-cyber-physical systems (HCPS) perspective[J]. Journal of Manufacturing Systems，2022，63:471-490.
[4] 王柏村，黄思翰，易兵，等. 面向智能制造的人因工程研究与发展[J]. 机械工程学报，2020，56(16):240-253. WANG Baicun，HUANG Sihan，YI Bing，et al. State-of-art of human factors/ergonomics in intelligent manufacturing[J]. Journal of Mechanical Engineering，2020，56(16):240-253.
[5] 张超，周光辉，李晶晶，等. 新一代信息技术赋能的数字孪生制造单元系统关键技术及应用研究[J]. 机械工程学报，2022，58(16):329-343. ZHANG Chao，ZHOU Guanghui，LI Jingjing，et al. Research on key technologies and application of new it-driven digital twin manufacturing cell system[J]. Journal of Mechanical Engineering，2022，58(16):329-343.
[6] 王跃飞，王超，许于涛，等. 边-云协同下智能制造单元作业的数字孪生任务调度方法[J]. 机械工程学报，2024，60(6):137-152. WANG Yuefei，WANG Chao，XU Yutao，et al. Digital twin task scheduling method for jobs of intelligent manufacturing unit under edge-cloud collaboration[J]. Journal of Mechanical Engineering，2024，60(6):137-152.
[7] SAVSAR M. Reliability analysis of a flexible manufacturing cell [J]. Reliability Engineering & System Safety，2000，67(2):147-152.
[8] LU Y，ZHENG H，CHAND S，et al. Outlook on human- centric manufacturing towards Industry 5.0[J]. Journal of Manufacturing Systems，2022，62:612-627.
[9] 黄思翰，王柏村，张美迪，等. 面向人本智造的新一代操作工:参考架构、使能技术与典型场景[J]. 机械工程学报，2022，58(18):251-264. HUANG Sihan，WANG Baicun，ZHANG Meidi，et al. Operator 4.0 towards human-centric smart manufacturing:Framework，enabling technologies and typical scenarios[J]. Journal of Mechanical Engineering，2022，58(18):251-264.
[10] HE W，LI Z，CHEN C L P. A survey of human-centered intelligent robots:Issues and challenges[J]. IEEE/CAA Journal of Automatica Sinica，2017，4(4):602-609.
[11] MUSIĆ S，HIRCHE S. Control sharing in human-robot team interaction[J]. Annual Reviews in Control，2017，44:342-354.
[12] LI M，CAO H，SONG X，et al. Shared control driver assistance system based on driving intention and situation assessment[J]. IEEE Transactions on Industrial Informatics，2018，14(11):4982-4994.
[13] LIU T，LIU H，YANG B，et al. LDCNet:Limb direction cues-aware network for flexible human pose estimation in industrial behavioral biometrics systems[J]. IEEE Transactions on Industrial Informatics，2023，20(6):1-11.
[14] 宗长富，代昌华，张东. 智能汽车的人机共驾技术研究现状和发展趋势[J]. 中国公路学报，2021，34(6):214-237. ZONG Changfu，DAI Changhua，ZHANG Dong. Human- machine interaction technology of intelligent vehicle:Current development trends and future directions[J]. China Journal of Highway and Transport，2021，34(6):214-237.
[15] RUSSELL H E B，HARBOTT L K，NISKY I，et al. Motor learning affects car-to-driver handover in automated vehicles[J]. Science Robotics，2016，1(1):eaah5682.
[16] SALEH L，CHEVREL P，CLAVEAU F，et al. Shared steering control between a driver and an automation:stability in the presence of driver behavior uncertainty[J]. IEEE Transactions on Intelligent Transportation Systems，2013，14(2):974-983.
[17] GUO C，SENTOUH C，POPIEUL J C，et al. MPC-based shared steering control for automated driving systems[C] // 2017 IEEE International Conference on Systems，Man，and Cybernetics (SMC). Banff，AB:IEEE，2017:129-134.
[18] GUO C，SENTOUH C，POPIEUL J C，et al. Predictive shared steering control for driver override in automated driving:A simulator study[J]. Transportation Research Part F:Traffic Psychology and Behaviour，2019，61:326-336.
[19] LI M，SONG X，CAO H，et al. Shared control with a novel dynamic authority allocation strategy based on game theory and driving safety field[J]. Mechanical Systems and Signal Processing，2019，124:199-216.
[20] HUANG C，NAGHDY F，DU H，et al. Shared control of highly automated vehicles using steer-by-wire systems[J]. IEEE/CAA Journal of Automatica Sinica，2019，6(2):410-423.
[21] KADIR B A，BROBERG O. Human-centered design of work systems in the transition to Industry 4.0[J]. Applied Ergonomics，2021，92:103334.
[22] LU Y，ADRADOS J S，CHAND S S，et al. Humans are not machines-Anthropocentric human-machine symbiosis for ultra-flexible smart manufacturing[J]. Engineering，2021，7(6):734-737.
[23] ROMERO D，STAHRE J，TAISCH M. The Operator 4.0:Towards socially sustainable factories of the future[J]. Computers & Industrial Engineering，2020，139:106128.
[24] BAROROH D K，CHU C H，WANG L. Systematic literature review on augmented reality in smart manufacturing:Collaboration between human and computational intelligence[J]. Journal of Manufacturing Systems，2021，61:696-711.
[25] WANG B，ZHOU H，LI X，et al. Human digital twin in the context of Industry 5.0[J]. Robotics and Computer-Integrated Manufacturing，2024，85:102626.
[26] LI S，WANG R，ZHENG P，et al. Towards proactive human-robot collaboration:A foreseeable cognitive manufacturing paradigm[J]. Journal of Manufacturing Systems，2021，60:547-552.
[27] NOOHI E，ZEFRAN M，PATTON J L. A model for human-human collaborative object manipulation and its application to human-robot interaction[J]. IEEE Transactions on Robotics，2016，32(4):880-896.
[28] LI Y，TEE K P，CHAN W L，et al. Continuous role adaptation for human-robot shared control[J]. IEEE Transactions on Robotics，2015，31(3):672-681.
[29] LI Y，TEE K P，YAN R，et al. A framework of human- robot coordination based on game theory and policy iteration[J]. IEEE Transactions on Robotics，2016，32(6):1408-1418.
[30] BENZI F，FERRAGUTI F，RIGGIO G，et al. An energy-based control architecture for shared autonomy[J]. IEEE Transactions on Robotics，2022，38(6):3917-3935.
[31] GUALTIERI L，RAUCH E，VIDONI R. Development and validation of guidelines for safety in human-robot collaborative assembly systems[J]. Computers & Industrial Engineering，2022，163:107801.
[32] CONTI C J，VARDE A S，WANG W. Human-robot collaboration with commonsense reasoning in smart manufacturing contexts[J]. IEEE Transactions on Automation Science and Engineering，2022，19(3):1784-1797.
[33] CHU C H，LIU Y L. Augmented reality user interface design and experimental evaluation for human-robot collaborative assembly[J]. Journal of Manufacturing Systems，2023，68:313-324.
[34] KUO Y，LIU C C. Operator assignment in a labor-intensive manufacturing cell considering inter-cell manpower transfer[J]. Computers & Industrial Engineering，2017，110:83-91.
[35] LIN S W，YING K C. Makespan optimization in a no-wait flowline manufacturing cell with sequence-dependent family setup times[J]. Computers & Industrial Engineering，2019，128:1-7.
[36] YANG B，ZHANG J，SHI H. Interactive-imitation-based distributed coordination scheme for smart manufacturing[J]. IEEE Transactions on Industrial Informatics，2021，17(5):3599-3608.
[37] 王柏村，薛塬，延建林，等. 以人为本的智能制造:理念、技术与应用[J]. 中国工程科学，2020，22(4): 139-146. WANG Baicun，XUE Yuan，YAN Jianlin，et al. Human- centered intelligent manufacturing:Overview and perspectives[J]. Strategic Study of CAE，2020，22(4): 139-146.

人本智造单元中人-智能系统协同双智能体工作机制研究

Research on Dual-agent Work Mechanism with Human-smart System Collaboration in Human-centric Smart Manufacturing Cell

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	张党, 赵永宣, 王振军, 张映锋. 数据-知识混合驱动的离散制造系统智能控制体系构架研究[J]. 机械工程学报, 2024, 60(6): 1-10,20.
[2]	狄子钧, 袁东风, 李东阳, 梁道君, 周晓天, 信苗苗, 曹凤, 雷腾飞. 基于多尺度-高效通道注意力网络的刀具故障诊断方法[J]. 机械工程学报, 2024, 60(6): 82-90.
[3]	王跃飞, 王超, 许于涛, 孙睿, 肖锴, 王凯林. 边-云协同下智能制造单元作业的数字孪生任务调度方法[J]. 机械工程学报, 2024, 60(6): 137-152.
[4]	苏建涛, 董绍华, 朱诗敏. 多目标混合流水车间机器故障重调度问题研究[J]. 机械工程学报, 2024, 60(4): 438-448.
[5]	蒋周明矩, 熊异, 王柏村. 面向工业5.0的人机协作增材制造[J]. 机械工程学报, 2024, 60(3): 238-253.
[6]	王耀南, 谢核, 邓晶丹, 毛建旭, 李文龙, 张辉. 智能制造测量机器人关键技术研究综述[J]. 机械工程学报, 2024, 60(16): 1-18.
[7]	王文波, 张映锋, 顾寄南, 张耿, 完严. 数据驱动的离散制造系统性能退化机理建模与预测控制方法研究[J]. 机械工程学报, 2024, 60(16): 400-411.
[8]	文旋豪, 曹华军, 李洪丞, 葛威威, 黄子轩. 离散制造单元生产扰动识别模型及其自适应节能控制方法[J]. 机械工程学报, 2023, 59(7): 252-264.
[9]	郑湃, 李成熙, 殷悦, 张荣, 鲍劲松, 王柏村, 谢海波, 王力翚. 增强现实辅助的互认知人机安全交互系统[J]. 机械工程学报, 2023, 59(6): 173-184.
[10]	丁明娜, 刘献礼, 岳彩旭, 范梦超, 顾浩. 面向智能制造过程的刀具设计、制备与管控技术[J]. 机械工程学报, 2023, 59(19): 429-459.
[11]	汪俊亮, 高鹏捷, 张洁, 王力翚. 制造大数据分析综述：内涵、方法、应用和趋势[J]. 机械工程学报, 2023, 59(12): 1-16.
[12]	周祖德, 姚碧涛, 谭跃刚, 刘明尧, 李天梁, 魏勤. 光纤传感在制造领域应用的分析与思考[J]. 机械工程学报, 2022, 58(8): 3-26.
[13]	臧冀原, 刘宇飞, 王柏村, 苗仲桢, 薛塬, 李培根. 面向2035的智能制造技术预见和路线图研究[J]. 机械工程学报, 2022, 58(4): 285-304.
[14]	兰箭, 钱东升, 邓加东, 华林. 高性能环类零件绿色智能轧制的研究进展[J]. 机械工程学报, 2022, 58(20): 186-197.
[15]	姚锡凡, 马南峰, 张存吉, 周佳军. 以人为本的智能制造：演进与展望[J]. 机械工程学报, 2022, 58(18): 2-15.