Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …

Engineering infrastructure incorporate complex systems, hazardous materials and often
operated by human beings, making them prone to catastrophic accidents. Continuously …

Abstract In Prognostic Health and Management (PHM) literature, the predictive maintenance
studies can be classified into two groups. The first group focuses on the prognostics step but …

Decision-making for engineering systems management can be efficiently formulated using
Markov Decision Processes (MDPs) or Partially Observable MDPs (POMDPs). Typical …

The difficulty in quantifying the benefit of Structural Health Monitoring (SHM) for decision
support is one of the bottlenecks to an extensive adoption of SHM on real-world structures …

Determination of inspection and maintenance policies for minimizing long-term risks and
costs in deteriorating engineering environments constitutes a complex optimization problem …

Aircraft maintenance is undergoing a paradigm shift towards predictive maintenance, where
the use of sensor data and Remaining-Useful-Life prognostics are central. This paper …

The increasing competition among industries has leveraged the emergence of various tools
and methods for maintenance decision-making support. This paper identifies in literature the …

In the context of modern engineering, environmental, and societal concerns, there is an
increasing demand for methods able to identify rational management strategies for civil …

Abstract Prognostic Health Management aims to predict the Remaining Useful Life (RUL) of
degrading components/systems utilizing monitoring data. These RUL predictions form the …