Reinforcement and deep reinforcement learning-based solutions for machine maintenance planning, scheduling policies, and optimization

O Ogunfowora, H Najjaran - Journal of Manufacturing Systems, 2023 - Elsevier
Abstract Systems and machines undergo various failure modes that result in machine health
degradation, so maintenance actions are required to restore them back to a state where they …

A multi-objective bi-level optimization framework for dynamic maintenance planning of active distribution networks in the presence of energy storage systems

SAA Matin, SA Mansouri, M Bayat, AR Jordehi… - Journal of Energy …, 2022 - Elsevier
Improving the reliability of microgrids as well as satisfying technical and economic
constraints are very important challenges for distribution system operators (DSOs), which …

A stochastic tri-layer optimization framework for day-ahead scheduling of microgrids using cooperative game theory approach in the presence of electric vehicles

AZG Seyyedi, E Akbari, MH Atazadegan… - Journal of Energy …, 2022 - Elsevier
This study provides a tri-layer optimization framework in which the microgrid strategy for day-
ahead market participation is determined by considering the uncertainties of load, RESs and …

Condition-based maintenance with reinforcement learning for refrigeration systems with selected monitored features

CF de Lima Munguba, GNP Leite, AAV Ochoa… - … Applications of Artificial …, 2023 - Elsevier
Worldwide, buildings are responsible for almost 30% of energy consumption, and those
buildings that intensively use refrigeration systems, such as supermarkets and grocery …

Importance measure-based maintenance strategy optimization: Fundamentals, applications and future directions in AI and IoT

H Dui, X Wu, S Wu, M Xie - Frontiers of Engineering Management, 2024 - Springer
Numerous maintenance strategies have been proposed in the literature related to reliability.
This paper focuses on the utilization of reliability importance measures to optimize …

Modelling the operation process of light utility vehicles in transport systems using Monte Carlo simulation and semi-markov approach

M Oszczypała, J Ziółkowski, J Małachowski - Energies, 2023 - mdpi.com
This research paper presents studies on the operation process of the Honker 2000 light
utility vehicles that are part of the Polish Armed Forces transport system. The phase space of …

A stochastic dynamic programming approach for the machine replacement problem

A Forootani, MG Zarch, M Tipaldi, R Iervolino - Engineering Applications of …, 2023 - Elsevier
This paper addresses both the modeling and the resolution of the replacement problem for a
population of machines. The main objective is the computation of a minimum cost …

Knowledge-enhanced reinforcement learning for multi-machine integrated production and maintenance scheduling

J Hu, H Wang, HK Tang, T Kanazawa, C Gupta… - Computers & Industrial …, 2023 - Elsevier
Abstract Machines deteriorate as they perform production operations, leading to increased
production cost rates. When the deterioration reaches a certain level, the machine may …

Application of Reinforcement Learning to Dyeing Processes for Residual Dye Reduction

W Lee, SMM Sajadieh, HK Choi, J Park… - International Journal of …, 2024 - Springer
Sustainability has become a prominent theme in the manufacturing industry, with an
emphasis on optimal process configurations that enable environmentally friendly and …

Blockchain design with optimal maintenance planning

A Al-Refaie, A Al-Hawadi, N Lepkova - Buildings, 2022 - mdpi.com
Rapid advancement of data management and sharing technology has urged organizations
to develop effective maintenance management systems. This research, therefore, proposes …