Developing data-driven O&M policy through sequential pattern mining: A case study

RGN Paiva, YR Melo, CAV Cavalcante… - Computers & Industrial …, 2024 - Elsevier
This study focuses on utilizing data mining techniques to extract valuable insights from
discrete industrial data, crucial for Operations and Maintenance (O&M) decision-making. We …

[HTML][HTML] Deep reinforcement learning for optimal planning of assembly line maintenance

M Geurtsen, I Adan, Z Atan - Journal of Manufacturing Systems, 2023 - Elsevier
Discovering the optimal maintenance planning strategy can have a substantial impact on
production efficiency, yet this aspect is often overlooked in favor of production planning. This …

Energy-oriented opportunistic maintenance optimization of continuous process manufacturing systems with two types of stochastic durations

Z Chen, Z Chen, D Zhou, E Pan - Reliability Engineering & System Safety, 2023 - Elsevier
For continuous process manufacturing systems (CPMSs) where the production process
cannot be stopped, the “opportunities” for maintenance can only occur within the specified …

Opportunistic maintenance optimization of continuous process manufacturing systems considering imperfect maintenance with epistemic uncertainty

Z Chen, Z Chen, D Zhou, T Xia, E Pan - Journal of Manufacturing Systems, 2023 - Elsevier
Due to the production process for continuous process manufacturing system (CPMS) cannot
be stopped, the “opportunities” for maintenance can only occur within the specified time …

A multicriteria model to support the selection of inspection service providers based on the delay time model

AJS Rodrigues, CAV Cavalcante… - International …, 2023 - Wiley Online Library
This paper proposes a multicriteria model based on the delay time concept and the
FITradeoff method to support the choice of a service provider who inspects isolation valves …

[HTML][HTML] Deep reinforcement learning for maintenance optimization of a scrap-based steel production line

WAF Neto, CAV Cavalcante, P Do - Reliability Engineering & System Safety, 2024 - Elsevier
This paper presents a Deep Reinforcement Learning (DRL)-based optimization approach
for determining the optimal inspection and maintenance planning of a scrap-based steel …

Carbon emission reduction in China's iron and steel industry through technological innovation: a quadrilateral evolutionary game analysis under government …

T Xinfa, L Shuai, W Yonghua, W Youwei… - Frontiers in …, 2025 - frontiersin.org
The steel industry is notable for its significant environmental impact, highlighting the
pressing need to promote technological innovation within the sector in order to reduce …

[HTML][HTML] Study of chlorine removal from shredder residue: Thermal dechlorination and water leaching

C Manera, D Perondi, D Restelatto, M Godinho… - … Chemistry for the …, 2024 - Elsevier
Shredder residue (SR) is an inevitable waste in the production of steel by scrap melting, and
the presence of chlorine is the main responsible for its non-use of energy. This study aimed …

Revisión sistemática del uso de tecnologías inteligentes enfocadas en los procesos de las industrias sostenibles

K Baltazar Alcaraz - 2024 - 51.143.95.221
En la actualidad, las industrias a nivel mundial están constantemente actualizando su
infraestructura tecnológica. Este proceso implica la búsqueda y adquisición de nuevas …

[PDF][PDF] Joint Optimization of Condition-Based Operation and Maintenance for Continuous Process Manufacturing Systems Under Imperfect Maintenance

Z Chen, Z Chen, D Zhou, E Pan - 2023 - rpsonline.com.sg
For continuous process manufacturing systems (CPMSs) where the production process
cannot be stopped, two popular performance evaluation metrics are production efficiency …