南京航空航天大学学报（英文版）2025，Vol.42Issue(3)：297-309,13.DOI:10.16356/j.1005-1120.2025.03.003
考虑动态扰动的自组织制造系统调度优化与自适应决策方法
Scheduling Optimization and Adaptive Decision-Making Method for Self-organizing Manufacturing Systems Considering Dynamic Disturbances
摘要
Abstract
The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are difficult to achieve efficient and real-time production management under dynamic disturbance.In order to improve the intelligence and adaptability of production scheduler,a novel distributed scheduling architecture is proposed,which has the ability to autonomously allocate tasks and handle disturbances.All production tasks are scheduled through autonomous collaboration and decision-making between intelligent machines.Firstly,the multi-agent technology is applied to build a self-organizing manufacturing system,enabling each machine to be equipped with the ability of active information interaction and joint-action execution.Secondly,various self-organizing collaboration strategies are designed to effectively facilitate cooperation and competition among multiple agents,thereby flexibly achieving global perception of environmental state.To ensure the adaptability and superiority of production decisions in dynamic environment,deep reinforcement learning is applied to build a smart production scheduler.Based on the perceived environment state,the scheduler intelligently generates the optimal production strategy to guide the task allocation and resource configuration.The feasibility and effectiveness of the proposed method are verified through three experimental scenarios using a discrete manufacturing workshop as the test bed.Compared to heuristic dispatching rules,the proposed method achieves an average performance improvement of 34.0%in three scenarios in terms of order tardiness.The proposed system can provide a new reference for the design of smart manufacturing systems.关键词
智能制造/自适应调度/自组织制造系统/强化学习Key words
intelligent manufacturing/adaptive scheduling/self-organizing manufacturing system/reinforcement learning分类
机械制造引用本文复制引用
张毅,乔森雨,殷磊磊,孙权,谢富鹏..考虑动态扰动的自组织制造系统调度优化与自适应决策方法[J].南京航空航天大学学报（英文版）,2025,42(3):297-309,13.基金项目
This work was supported by the Scien-tific Research Foundation of Nanjing Institute of Technology(No.YKJ202425)and the National Natural Science Founda-tion of China(No.72301130). （No.YKJ202425）
