制造系统分布式联合动态维护与生产调度：基于模型预测控制和Benders分解的框架
Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition
摘要：
根据状态和系统的退化程度来安排维护，可以提高系统的可靠性，同时使维护成本最小化。由于退化水平动态变化，在系统的操作，我们面临着一个动态的维护调度问题。在本文中，我们解决了制造系统的动态维护调度的基础上，其退化水平。制造系统由几个单元组成，这些单元具有定义的能力和单独的动态退化模型，寻求优化其回报。这些单位出售其生产能力，同时根据降级状态维护系统以防止故障。制造单位共同负责满足系统的需求。这引起了代理之间的耦合约束。因此，我们面临着一个大规模的混合整数动态维修调度问题。为了处理系统的动态模型和大规模优化，我们提出了一种分布式算法，使用模型预测控制（MPC）和Benders分解方法。在该算法中，首先，主问题获得所有代理的维修计划，然后在此基础上，代理获得他们的最佳生产使用的分布式MPC方法，采用对偶分解的方法来解决代理之间的耦合约束。最后通过实例验证了该方法的有效性。
英文摘要：
Scheduling the maintenance based on the condition, respectively the degradation level of the system leads to improved system's reliability while minimizing the maintenance cost. Since the degradation level changes dynamically during the system's operation, we face a dynamic maintenance scheduling problem. In this paper, we address the dynamic maintenance scheduling of manufacturing systems based on their degradation level. The manufacturing system consists of several units with a defined capacity and an individual dynamic degradation model, seeking to optimize their reward. The units sell their production capacity, while maintaining the systems based on the degradation state to prevent failures. The manufacturing units are jointly responsible for fulfilling the demand of the system. This induces a coupling constraint among the agents. Hence, we face a large-scale mixed-integer dynamic maintenance scheduling problem. In order to handle the dynamic model of the system and large-scale optimization, we propose a distributed algorithm using model predictive control (MPC) and Benders decomposition method. In the proposed algorithm, first, the master problem obtains the maintenance scheduling for all the agents, and then based on this data, the agents obtain their optimal production using the distributed MPC method which employs the dual decomposition approach to tackle the coupling constraints among the agents. The effectiveness of the proposed method is investigated on a case study.
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