[HTML][HTML] Maintenance optimization in industry 4.0

L Pinciroli, P Baraldi, E Zio - Reliability Engineering & System Safety, 2023 - Elsevier
This work reviews maintenance optimization from different and complementary points of
view. Specifically, we systematically analyze the knowledge, information and data that can …

[HTML][HTML] Monte carlo tree search-based deep reinforcement learning for flexible operation & maintenance optimization of a nuclear power plant

Z Hao, F Di Maio, E Zio - Journal of Safety and Sustainability, 2024 - Elsevier
Nuclear power plants (NPPs) are required to operate on a flexible profitable production plan
while guaranteeing high safety standards. Deep reinforcement learning (DRL) is an effective …

[HTML][HTML] A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for …

Z Hao, F Di Maio, E Zio - Reliability Engineering & System Safety, 2023 - Elsevier
Abstract The Operation & Maintenance (O&M) of Cyber-Physical Energy Systems (CPESs) is
driven by reliable and safe production and supply, that need to account for flexibility to …

[HTML][HTML] Flexible operation and maintenance optimization of aging cyber-physical energy systems by deep reinforcement learning

Z Hao, F Di Maio, E Zio - Nuclear Engineering and Technology, 2024 - Elsevier
Abstract Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware
components to ensure a reliable and safe physical power production and supply …