Abstract Concepts and expectations of cyber-physical production systems (CPPSs) underscore their advantages over the present bespoke manufacturing systems. However, transitioning from traditional manufacturing to its CPPS counterpart remains a challenge. Although a CPPS can be realized, a gap between theory and practice exists considering the response of a CPPS to system disturbances, such as machine breakdowns and change in customer orders. Furthermore, the CPPS environment is stochastic; therefore, planning and control algorithms to reduce the discrepancy between the planned and actual system levels in real time is essential. In this paper, we present a CPPS prototype and a reactive production planning algorithm. Consistent with the literature on CPPS, we developed a moderately automated CPPS and a decentralized coordination mechanism that harnesses the inherent decentralized structure of the CPPS. Moreover, we have described the design and technologies used in building this CPPS. Through a production planning mathematical model, we proposed a control mechanism and measured the efficiency of the proposed algorithm under dynamic events based on work-in-progress inventories, throughput, and delayed demand. The decentralized algorithm determines a plan prior to start of production, which is re-optimized in case any dynamic events occur subsequent to the course of the production horizon. The results of the numerical investigation indicated that the proposed decentralized coordination algorithm outperforms other centralized planning algorithms on more than 50 % of the performance measures considered.

中文翻译：

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一种用于事件驱动生产计划和控制的反应分散协调算法：一个信息物理生产系统原型案例研究

摘要 网络物理生产系统 (CPPS) 的概念和期望强调了它们相对于当前定制制造系统的优势。然而，从传统制造向其 CPPS 对应物的转变仍然是一个挑战。尽管可以实现 CPPS，但考虑到 CPPS 对系统干扰（例如机器故障和客户订单变化）的响应，理论与实践之间存在差距。此外，CPPS 环境是随机的；因此，实时减少计划和实际系统级别之间差异的规划和控制算法至关重要。在本文中，我们提出了 CPPS 原型和反应式生产计划算法。与关于 CPPS 的文献一致，我们开发了一个适度自动化的 CPPS 和一个利用 CPPS 固有的分散结构的分散协调机制。此外，我们还描述了用于构建此 CPPS 的设计和技术。通过生产计划数学模型，我们提出了一种控制机制，并在基于在制品库存、吞吐量和延迟需求的动态事件下测量了所提出算法的效率。分散算法在生产开始之前确定计划，如果在生产范围的过程之后发生任何动态事件，则重新优化该计划。数值调查的结果表明，所提出的分散协调算法在超过 50% 的性能指标上优于其他集中式规划算法。