Dynamic Rerouting of Cyber-Physical Production Systems in Response to Disruptions Based on SDC Framework

Dynamic Rerouting of Cyber-Physical Production Systems in Response to Disruptions Based on SDC Framework
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DOI:
10.23919/acc.2019.8814412
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发表时间:
2019-07
期刊:
2019 American Control Conference (ACC)
影响因子:
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通讯作者:
Yassine Qamsane;Efe C. Balta;J. Moyne;D. Tilbury;K. Barton
Yassine Qamsane;Efe C. Balta;J. Moyne;D. Tilbury;K. Barton
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其他
文献类型:
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作者:
Yassine Qamsane;Efe C. Balta;J. Moyne;D. Tilbury;K. Barton

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世界正处于一场由智能制造(SM)驱动的新工业革命之中。尽管这种新模式有望提高灵活性、产品定制化、改进质量、高效能耗和提高生产率,但SM系统更容易受到小故障的影响,这些故障可能会引发大故障,甚至进入工厂的网络攻击。灵活性和反应性/主动性是提高SM系统可靠性、效率和对故障的鲁棒性响应的重要手段。在这种情况下,本文关注的是响应故障或攻击的部件的动态重新路由,这些故障或攻击可以改变系统的行为。该方法基于我们最近提出的软件定义控制(SDC)框架[1]的使用,该框架整合了来自自动化金字塔不同层次的数据,以提供整个SM系统的全局视图。为了解决重路由问题,重路由应用程序通过SDC中央控制器中的一组数字双胞胎访问系统的全局视图,并为决策者提供新的路由选择,决策者根据优化功能对这些路由进行优先级排序。然后将新的备选路线作为重新配置建议发送给运营商,以部署到工厂车间。并以一个小型制造系统为例进行了说明。
The world is in the midst of a new industrial revolution driven by Smart Manufacturing (SM). Though this new paradigm promises increased flexibility, product customization, improved quality, efficient energy consumption, and improved productivity, SM systems are more susceptible to small faults that could cascade into major failures or even cyber-attacks that enter the plant. Flexibility and reactivity/proactivity represent important means to enhance SM systems' reliability, efficiency, and robust response to faults. Within this context, this paper focuses on dynamic rerouting of parts in response to a fault or attack that can change the system's behavior. The method is based on the use of our recently proposed Software-Defined Control (SDC) framework [1], which consolidates data from the different levels of the automation pyramid to provide a global view of the entire SM system. To solve the rerouting problem, a rerouting application accesses the global view of the system through a set of digital twins hosted in the SDC central controller, and provides new route alternatives to a decision maker that prioritizes these routes based on an optimization function. The new route alternatives are then sent to the operator as reconfiguration recommendations to be deployed to the plant floor. The proposition is illustrated using a small manufacturing system example.