Discrete event simulation methods applied to advanced importance measures of repairable components in multistate network flow systems
Discrete event simulation methods applied to advanced importance measures of repairable components in multistate network flow systems
复制标题
DOI：
10.1016/j.ress.2013.05.025
复制
发表时间：
2013-11
期刊：
影响因子：
--
通讯作者：
A. Huseby;B. Natvig
中科院分区：
文献类型：
--
作者：
A. Huseby;B. Natvig
离散事件模型常用于仿真研究中，对纯跳跃过程进行建模和分析。离散事件模型可以被看作是一个由随机过程集合组成的系统，其中各个过程的状态由于在随机时间点发生的各种事件而发生变化。我们总是假设每个事件只影响其中一个过程。在这些事件之间，过程的状态被认为是恒定的。本文利用离散事件仿真方法对可修部件的多状态网络流系统进行了分析。为了研究不同的组件如何对系统做出贡献，有必要在系统级描述组件过程和过程之间通常复杂的交互。虽然分析考虑可能会对此有所启发，但模拟研究通常允许分析师探索更多细节。通过为各种过程的发展产生稳定的曲线估计，人们可以更好地了解这些系统如何随时间发展。这些方法在研究可修部件的先进重要性测度时特别有用。这些措施可以是非常复杂的，因此不可能分析计算。然而，通过使用离散事件模拟，这可以以非常自然和直观的方式完成。特别是显着的Barlow-Proschan措施和Natvig措施在多态网络流系统之间的差异可以探讨。
Discrete event models are frequently used in simulation studies to model and analyze pure jump processes. A discrete event model can be viewed as a system consisting of a collection of stochastic processes, where the states of the individual processes change as results of various kinds ofeventsoccurring at random points of time. We always assume that each event only affectsoneof the processes. Between these events the states of the processes are considered to be constant. In the present paper we use discrete event simulation in order to analyze a multistate network flow system of repairable components. In order to study how the different components contribute to the system, it is necessary to describe the often complicated interaction between component processes and processes at the system level. While analytical considerations may throw some light on this, a simulation study often allows the analyst to explore more details. By producing stable curve estimates for the development of the various processes, one gets a much better insight in how such systems develop over time. These methods are particulary useful in the study of advanced importancez measures of repairable components. Such measures can be very complicated, and thus impossible to calculate analytically. By using discrete event simulations, however, this can be done in a very natural and intuitive way. In particular significant differences between the Barlow–Proschan measure and the Natvig measure in multistate network flow systems can be explored.