The increasing complexity of engineering systems presents significant challenges in
addressing intricate reliability and maintenance optimization problems. Advanced …

Risk management often involves retrofit optimization to enhance the performance of
buildings against extreme events but may result in huge upfront mitigation costs. Existing …

After a city-scale natural hazard, policymakers should plan sound decisions on the repair
sequence to ensure the resilient recovery of the community, which consists of …

In the process industries, where orders arrive at irregular intervals, inappropriate
maintenance frequency often leads to unplanned shutdowns of high-speed parallel …

This paper investigates an extended replacement policy for a two-unit system subject to
shocks and cumulative damage. As a shock occurs, the system suffers two types of effects …

Motivation Deep learning (DL) has revolutionized condition monitoring (CoM) in mechanical
systems by reducing manual signal processing. However, DL's industrial integration is …

Maintenance and production scheduling are intertwined activities that should be addressed
simultaneously to uphold production systems' reliability and production efficiency. The digital …

The utilization of prognostic information in practical engineering is increasing with the
development of technology and predictive modeling. Current research on maintenance …

This paper develops a data-driven approach to dynamically integrate tactical production and
predictive maintenance planning for a multi-state system composed of several series …

This paper presents a Deep Reinforcement Learning (DRL)-based optimization approach
for determining the optimal inspection and maintenance planning of a scrap-based steel …