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Application of Extended Coloured Stochastic Petri Nets for Modelling and Analysis of RAMS+C of Production Systems

机译:扩展彩色随机培养网应用于生产系统RAMS + C的建模与分析

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Modern production systems are characterized by numerous conjoint and interacting production machines each with sophisticated maintenance and logistic processes. To remain competitive, it is necessary to reduce the system downtimes by applying the optimal maintenance strategy and therefore reducing life cycle costs. Condition monitoring often is a very effective way to minimize downtimes of crucial system components such as ball screws, ball bearings and drives. But sometimes condition monitoring is not cost-effective or even reduces the system's operational availability. The decision whether it's reasonable to implement condition based maintenance or not requires a detailed analysis of the system's behavior. Since many analytical models of technical systems have significant limitations and simplifications, simulation techniques are applied very often In our paper we will present an improved comprehensive methodology for the modeling and analysis of production systems which has been basically introduced at the RAMS-Symposium in 2008. The model incorporates an extended colored stochastic Petri net (ECSPN) and a reliability block diagram (RBD) in a conjoint modeling procedure which allows a close-to-reality representation of a complex production system's behavior.
机译:现代生产系统的特点是许多联合和交互生产机器,每个连接和互动生产机器都具有复杂的维护和逻辑流程。为了保持竞争力,有必要通过应用最佳维护策略来减少系统停机时间,从而降低生命周期成本。状态监测通常是一种非常有效的方法,可以最大限度地减少滚珠螺钉,滚珠轴承和驱动器等关键系统部件的下降时间。但有时条件监测并不具有成本效益甚至降低系统的运行可用性。决定是否合理地实现基于条件的维护或不需要对系统行为进行详细分析。由于技术系统的许多分析模型具有显着的局限性和简化,因此我们的论文中经常应用仿真技术,我们将在2008年的RAMS-Symposium上基本引入的生产系统建模和分析,提高了一种改进的综合方法。该模型包含一个扩展的彩色随机Petri网(ECSPN)和可靠性框图(RBD),其在联合建模过程中,允许复杂的生产系统的特写依赖性表示。

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