[HTML][HTML] Maintenance optimization in industry 4.0
This work reviews maintenance optimization from different and complementary points of
view. Specifically, we systematically analyze the knowledge, information and data that can …
view. Specifically, we systematically analyze the knowledge, information and data that can …
Deep reinforcement learning for Internet of Things: A comprehensive survey
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …
communication, computing, caching and control (4Cs) problems. The recent advances in …
Challenges to IoT-enabled predictive maintenance for industry 4.0
The Industry 4.0 paradigm is boosting the relevance of predictive maintenance (PdM) for
manufacturing and production industries. PdM strongly relies on Internet of Things (IoT) …
manufacturing and production industries. PdM strongly relies on Internet of Things (IoT) …
Reinforcement learning for predictive maintenance: A systematic technical review
The manufacturing world is subject to ever-increasing cost optimization pressures.
Maintenance adds to cost and disrupts production; optimized maintenance is therefore of …
Maintenance adds to cost and disrupts production; optimized maintenance is therefore of …
Applications of Reinforcement Learning for maintenance of engineering systems: A review
AP Marugán - Advances in Engineering Software, 2023 - Elsevier
Nowadays, modern engineering systems require sophisticated maintenance strategies to
ensure their correct performance. Maintenance has become one of the most important tasks …
ensure their correct performance. Maintenance has become one of the most important tasks …
Reinforcement learning-driven maintenance strategy: A novel solution for long-term aircraft maintenance decision optimization
Abstract A novel Reinforcement Learning (RL) driven maintenance strategy is proposed in
this paper for solving the problem of aircraft long-term maintenance decision optimization …
this paper for solving the problem of aircraft long-term maintenance decision optimization …
A model-based reinforcement learning approach for maintenance optimization of degrading systems in a large state space
Scheduling maintenance tasks based on the deteriorating process has often been
established on degradation models. However, the formulas of the degradation processes …
established on degradation models. However, the formulas of the degradation processes …
Operation scheduling in a solar thermal system: A reinforcement learning-based framework
Reinforcement learning (RL) provides an alternative method for designing condition-based
decision making in engineering systems. In this study, a simple and flexible RL tabular Q …
decision making in engineering systems. In this study, a simple and flexible RL tabular Q …
Condition-based maintenance with reinforcement learning for refrigeration systems with selected monitored features
Worldwide, buildings are responsible for almost 30% of energy consumption, and those
buildings that intensively use refrigeration systems, such as supermarkets and grocery …
buildings that intensively use refrigeration systems, such as supermarkets and grocery …
Dynamic maintenance strategy with iteratively updated group information
Maintenance grouping methods such as the rolling horizon approach are effective in
reducing maintenance costs of multi-component systems. Despite the theoretical …
reducing maintenance costs of multi-component systems. Despite the theoretical …