  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.
