人-信息-物理互联环境下数字车间制造能力建模与自适应调度

doi:10.3901/JME.2025.03.023

机械工程学报 ›› 2025, Vol. 61 ›› Issue (3): 23-39.doi: 10.3901/JME.2025.03.023

• 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

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人-信息-物理互联环境下数字车间制造能力建模与自适应调度

胡炳涛¹, 钟锐锐¹, 冯毅雄^1,2, 杨晨^1,3, 王天跃^1,4, 洪兆溪¹, 谭建荣¹

1. 浙江大学流体动力与机电系统国家重点实验室杭州 310027;
2. 贵州大学公共大数据国家重点实验室贵阳 550025;
3. 联通(浙江)产业互联网有限公司杭州 311199;
4. 香港城市大学系统工程系香港 518057

收稿日期:2024-02-04 修回日期:2024-08-25 发布日期:2025-03-12
作者简介:胡炳涛，男，1992年出生，博士，副研究员。主要研究方向为产品设计理论与智能制造。E-mail:hubingtao@zju.edu.cn;钟锐锐，男，1998年出生，博士研究生。主要研究方向为智能制造与强化学习。E-mail:zhongruirui@zju.edu.cn;冯毅雄(通信作者)，男，1975年出生，博士，教授，博士研究生导师。主要研究方向为现代设计理论与方法。E-mail:fyxtv@zju.edu.cn;杨晨，男，1987年出生，博士研究生。主要研究方向为工业物联网与智能制造。E-mail:11925104@zju.edu.cn;王天跃，男，1997年出生，博士研究生。主要研究方向为智能制造与机器学习。E-mail:tianyue_wang@zju.edu.cn;洪兆溪，女，1990年出生，博士，助理研究员。主要研究方向为智能设计与不确定性优化决策。E-mail:hzhx@zju.edu.cn;谭建荣，男，1954年出生，博士，教授，博士研究生导师，中国工程院院士。主要研究方向为CAX方法学、工程图学、企业信息化。E-mail:egi@zju.edu.cn
基金资助:
中国博士后科学基金(2024T170795)、国家自然科学基金(52205288)、浙江省“尖兵”“领雁”研发攻关计划(2024C01029、2023C01214)、浙江省教育厅一般科研(Y202352877)和湖州市自然科学基金(2019YZ09)资助项目。

Digital Shop Floor Manufacturing Capability Modeling and Adaptive Scheduling in Human-cyber-physical Interconnected Environment

HU Bingtao¹, ZHONG Ruirui¹, FENG Yixiong^1,2, YANG Chen^1,3, WANG Tianyue^1,4, HONG Zhaoxi¹, TAN Jianrong¹

1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027;
2. State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025;
3. China Unicom (Zhejiang) Industrial Internet Co., Ltd., Hangzhou 311199;
4. Department of Systems Engineering, City University of Hong Kong, Hong Kong 518057

Received:2024-02-04 Revised:2024-08-25 Published:2025-03-12

摘要/Abstract

摘要： 工业5.0的发展对制造业的信息化、数字化和智能化提出了更高的要求。针对传统车间制造能力组织范式和智能调度技术缺乏的重要难题，提出人-信息-物理互联环境下数字车间制造能力建模与自适应调度技术，从而实现对复杂车间制造能力的高保真建模与生产资源的高效调度。为了有效管理数字车间中的生产要素，提出一种融合人-信息-物理系统的数字车间制造能力建模技术。此外，提出一种深度强化学习驱动的数字车间自适应调度(Deep reinforcement learning-driven adaptive scheduling，DRL-AS)算法，该算法将柔性作业车间调度问题以异构析取图的形式进行建模。考虑到工序与机器之间复杂的耦合关联性，设计一种基于分层自注意力机制的多要素表征方法以提取环境状态的全局特征和辅助智能体进行高质量决策。近端策略优化(Proximal policy optimization，PPO)算法被用于训练所提出自适应调度技术。试验结果表明所提出方法的调度性能和泛化性能显著优于对比算法。

关键词: 人-信息-物理系统, 柔性作业车间调度, 深度强化学习, 制造能力建模, 数字孪生

Abstract: The development of Industry 5.0 presents higher requirements for the informatization, digitization, and intelligence of the manufacturing industry. To address the important challenges of the lack of traditional workshop manufacturing capacity organizational paradigm and intelligent scheduling technology, a digital workshop manufacturing capacity modeling and adaptive scheduling technology in the human-cyber-physical interconnected environment is proposed to achieve high-fidelity modeling of complex workshop manufacturing capacity and efficient scheduling of production resources. In order to effectively manage the production elements in the digital workshop, a digital workshop manufacturing capacity modeling technology that integrates the human-cyber-physical system is proposed. In addition, a deep reinforcement learning-driven adaptive scheduling algorithm (DRL-AS) is devised for the digital workshop, which models the flexible job shop scheduling problem in the form of heterogeneous directed acyclic graphs. Considering the complex coupling relationship between operations and machines, a multi-factor representation method based on hierarchical self-attention mechanism is designed to extract global features of the environmental state and assist the agent in making high-quality decisions. Proximal policy optimization (PPO) algorithm is used to train the proposed adaptive scheduling technology. Experimental results show that the scheduling performance and generalization performance of the proposed method are significantly better than those of the comparison algorithms.

Key words: human-cyber-physical system, flexible job-shop scheduling, deep reinforcement learning, manufacturing capability modeling, digital twin

中图分类号:

TH165
TP18

胡炳涛, 钟锐锐, 冯毅雄, 杨晨, 王天跃, 洪兆溪, 谭建荣. 人-信息-物理互联环境下数字车间制造能力建模与自适应调度[J]. 机械工程学报, 2025, 61(3): 23-39.

HU Bingtao, ZHONG Ruirui, FENG Yixiong, YANG Chen, WANG Tianyue, HONG Zhaoxi, TAN Jianrong. Digital Shop Floor Manufacturing Capability Modeling and Adaptive Scheduling in Human-cyber-physical Interconnected Environment[J]. Journal of Mechanical Engineering, 2025, 61(3): 23-39.

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人-信息-物理互联环境下数字车间制造能力建模与自适应调度

Digital Shop Floor Manufacturing Capability Modeling and Adaptive Scheduling in Human-cyber-physical Interconnected Environment

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