abstract-for-resubmission.txt

We propose a new condition-based maintenance policy for complex systems,
based on the status (working, defective) of all components within a system,
and the system's reliability block diagaram.
Via the survival signature,
we obtain a predictive distribution for the system survival time,
also known as residual life distribution,
based on which of the system's components currently function or not,
and the current age of the functioning components.

The time to failure of the system components
is modeled by a Weibull distribution with fixed shape parameter.
The scale parameter is iteratively updated in a Bayesian fashion
using the current (censored and non-censored) component lifetimes.
Each component type has a separate Weibull model that may also include test data.

The cost-optimal moment of replacement for the system is obtained by minimizing
the expected cost rate per unit of time.
The unit cost rate is recalculated when components fail
or at the end of every (very short) fixed inter-evaluation interval,
leading to a dynamic maintenance policy,
since the ageing of components and possible failures will change the cost-optimal moment of replacement over time.
Numerical experiments provide some insight into the performance of the policy.