The analysis of system reliability has often benefited from graphical tools such as fault trees and Bayesian networks. In this article, instead of conventional graphical tools, we apply a probabilistic graphical model called the chain event graph (CEG) to represent the failures and processes of deterioration of a system. The CEG is derived from an event tree and can flexibly represent the unfolding of asymmetric processes. For this application we need to define a new class of formal intervention we call remedial to model causal effects of remedial maintenance. This fixes the root causes of a failure and returns the status of the system to as good as new. We demonstrate that the semantics of the CEG are rich enough to express this novel type of intervention. Furthermore through the bespoke causal algebras the CEG provides a transparent framework with which guide and express the rationale behind predictive inferences about the effects of various different types of remedial intervention. A back-door theorem is adapted to apply to these interventions to help discover when a system is only partially observed.

翻译：系统可靠性分析通常受益于故障树和贝叶斯网络等图形化工具。本文摒弃传统图形化工具，采用一种称为链事件图（CEG）的概率图模型来表示系统故障与退化过程。CEG源于事件树，能够灵活刻画非对称过程的演化。针对该应用场景，我们定义了一类新型形式化干预——补救性干预，用于对补救性维护的因果效应进行建模。这种干预能够消除故障根本原因，使系统状态恢复如新。我们证明CEG的语义足以表达这种新型干预类型。通过定制化因果代数，CEG提供了一个透明框架，可指导并表达关于不同类型补救性干预效果的预测推理逻辑。我们改写了后门准则定理，使其适用于此类干预，从而帮助识别系统仅被部分观测的情况。