A framework for quantifying the value of vibration-based structural health monitoring
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 …
support is one of the bottlenecks to an extensive adoption of SHM on real-world structures …
Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints
CP Andriotis, KG Papakonstantinou - Reliability Engineering & System …, 2021 - Elsevier
Determination of inspection and maintenance policies for minimizing long-term risks and
costs in deteriorating engineering environments constitutes a complex optimization problem …
costs in deteriorating engineering environments constitutes a complex optimization problem …
Inference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learning
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 …
increasing demand for methods able to identify rational management strategies for civil …
[HTML][HTML] Knowledge engineering for wind energy
Y Marykovskiy, T Clark, J Day, M Wiens… - Wind Energy …, 2024 - wes.copernicus.org
With the rapid evolution of the wind energy sector, there is an ever-increasing need to create
value from the vast amounts of data made available both from within the domain and from …
value from the vast amounts of data made available both from within the domain and from …
[HTML][HTML] Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems
Abstract Structural Health Monitoring (SHM) describes a process for inferring quantifiable
metrics of structural condition, which can serve as input to support decisions on the …
metrics of structural condition, which can serve as input to support decisions on the …
Selective maintenance and inspection optimization for partially observable systems: An interactively sequential decision framework
Y Liu, J Gao, T Jiang, Z Zeng - IISE Transactions, 2023 - Taylor & Francis
Selective maintenance is an important condition-based maintenance strategy for multi-
component systems, where optimal maintenance actions are identified to maximize the …
component systems, where optimal maintenance actions are identified to maximize the …
POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance
Abstract Partially Observable Markov Decision Processes (POMDPs) can model complex
sequential decision-making problems under stochastic and uncertain environments. A main …
sequential decision-making problems under stochastic and uncertain environments. A main …
Improving industrial maintenance efficiency: A holistic approach to integrated production and maintenance planning with human error optimization
V Bafandegan Emroozi, M Kazemi… - Process Integration and …, 2024 - Springer
Integrated production and maintenance planning optimizes efficiency and productivity by
coordinating schedules. Investigating this planning can improve operational efficiency …
coordinating schedules. Investigating this planning can improve operational efficiency …
Quantifying the value of structural health monitoring information with measurement bias impacts in the framework of dynamic Bayesian Network
Abstract Structural Health Monitoring (SHM) information contributes substantially to
Structural Integrity Management (SIM), which can be achieved through reducing epistemic …
Structural Integrity Management (SIM), which can be achieved through reducing epistemic …
Dynamic joint sensor selection and maintenance optimization in partially observable deteriorating systems
We consider a degrading system with costly but silent failures. The system can be partially
observed using a set of heterogeneous noisy sensors at a given cost, where each sensor …
observed using a set of heterogeneous noisy sensors at a given cost, where each sensor …