当前缺乏利用生产信息进行复杂生产系统的可持续性动态建模分析，并以此找出优化、控制方案的研究。本项目针对复杂生产系统的实时性建模，计划进行如下研究：(1)结合基于事件的研究方法，构建一个数据驱动的综合系统模型，利用生产信息监测并分析生产系统的生产和可持续性动态，实时将生产信息转化为有用的管理和控制信息；(2)研究复杂动态系统的能耗效率提升机会窗口理论，利用马尔科夫模型预测机会窗口，结合动态控制方案，构建实时生产控制系统，为生产控制，能耗效率提升决策提供支持；(3)针对系统生产和能耗效率提升，结合约束理论(Theory of Constraints, TOC)，构建基于事件的动态连续提高优化模型。该项目所形成的生产与控制模型能够为复杂生产系统的实时性分析，控制和优化提供一种新的理论与实用工具，拓展基于静态分析的现有理论，提高系统的意识性与响应性。研究成果可以有效提升生产系统的可持续性。

The advent of intelligent manufacturing technology has enabled manufacturing systems to distribute sensors across the systems, which makes production information to become transparent, detailed and in real-time. However, the utilization of the production information for the modeling and improvement of system production and sustainability has been largely lagged behind. Therefore, this research proposes a comprehensive method, which will (1) establish an integrated event-based system modeling method (EBM) to capture system dynamics in real time. The EBM method can transfer the production information into useful control and managerial information; (2) establish an energy saving opportunity window theory in complex production systems and formulate a real-time control strategy to improve system production and sustainability by taking the opportunity windows; (3) establish an event-based bottleneck identification and mitigation method to continuously improve system performance. The research will result in a fundamental understanding of the complex multistage manufacturing system transient behaviors and a significant improvement in system awareness, responsiveness, and overall system sustainability.