摘要
随着制造业向智能化转型,自动化装配线面临瓶颈工序的挑战。传统方法难以快速定位瓶颈工序,影响生产效率。因此,基于数字孪生驱动对自动化装配线瓶颈工序检测与优化进行了深入研究。通过构建虚拟与物理系统的实时同步模型,结合瓶颈得分和动态瓶颈强度指标,实现瓶颈工序的精准识别与优化。实验结果表明,通过资源再分配与缓冲区调整,优化后的生产线产能显著提升,瓶颈工序的加工周期缩短,整体生产效率得到提高。
As the manufacturing industry transforms towards intelligence,automated assembly lines face challenges from bottleneck processes.Traditional methods struggle to swiftly locate these bottleneck processes,adversely affecting production efficiency.Therefore,in-depth research is conducted on the detection and optimization of bottleneck processes in automated assembly lines driven by digital twins.By constructing a real-time synchronization model between virtual and physical systems,and incorporating bottleneck scores and dynamic bottleneck intensity indicators,precise identification and optimization of bottleneck processes are achieved.Experimental results demonstrate that,through resource redistribution and buffer adjustment,the optimized production line significantly enhances capacity,shortens the processing cycle of bottleneck processes,and improves overall production efficiency.
作者
王佳楠
WANG Jianan(Harbin Zhongkai Automation Technology Co.,Ltd.,Harbin,Heilongjiang 150078,China)
出处
《自动化应用》
2025年第22期107-109,113,共4页
Automation Application
关键词
数字孪生
自动化装配线
瓶颈工序
智能制造
digital twin
automated assembly line
bottleneck process
intelligent manufacturing
