作为一类先进自动化制造系统，自动化制造单元（Robotic cell）在半导体和印刷电路板制造等行业有着广泛的应用。本项目从事前和事后两个角度来应对自动化制造单元所面临的不确定事件，提出不确定环境下自动化制造单元前摄式/反应式（Proactive/reactive）调度方法。首先，对自动化制造单元所面临的不确定事件进行识别和分类，并分析其影响机理和程度；其次，提出自动化制造单元前摄式/反应式调度框架以及事件驱动式局部重调度与周期性完全重调度相结合的重调度模式。在此基础上，研究局部重调度中快速修复算法以及完全重调度中基于多种群文化基因算法（Memetic algorithm）的前摄式调度方法。最后，以集束型半导体制程设备和印刷电路板电镀生产线为对象，对提出的调度方法进行验证和应用。研究成果将为不确定环境下自动化制造单元调度问题提供解决思路，并在半导体和印刷电路板制造等行业具有重要的应用价值。

As a kind of advanced automated manufacturing systems, robotic cells have widespread applications in semiconductor and printed circuit board (PCB) manufacturing industries. A proactive/reactive scheduling approach for robotic cells under uncertainties is proposed in this project, which handles uncertain events from pre-event and post-event perspectives. Firstly, the uncertain events in robotic cells are identified and categorized, along with an analysis of their impact. Secondly, a framework of proactive/reactive scheduling approach for robotic cells under uncertainties is proposed, as well as a rescheduling mode integrating the event-driven partial rescheduling with the periodic complete rescheduling. Thirdly, a fast repair algorithm for partial rescheduling and a proactive scheduling method, based on multi-population memetic algorithms, for complete rescheduling are developed. Finally, the proposed scheduling approaches are tested and applied using cases from cluster tools in semiconductor manufacturing and PCB electroplating production lines. The research results of this project will not only provide a solution to scheduling problems in robotic cells under uncertainties, but also have important practical value in semiconductor and PCB manufacturing industries.