  This paper reviews current literature in the field of predictive maintenance
from the system point of view. We differentiate the existing capabilities of
condition estimation and failure risk forecasting as currently applied to
simple components, from the capabilities needed to solve the same tasks for
complex assets. System-level analysis faces more complex latent degradation
states, it has to comprehensively account for active maintenance programs at
each component level and consider coupling between different maintenance
actions, while reflecting increased monetary and safety costs for system
failures. As a result, methods that are effective for forecasting risk and
informing maintenance decisions regarding individual components do not readily
scale to provide reliable sub-system or system level insights. A novel holistic
modeling approach is needed to incorporate available structural and physical
knowledge and naturally handle the complexities of actively fielded and
maintained assets.
