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

Waldomiro Alves Ferreira Neto, Virgínio Cavalcante, Cristiano Alexandre and Phuc Do

Reliability Engineering and System Safety, 2024, vol. 249, issue C

Abstract: This paper presents a Deep Reinforcement Learning (DRL)-based optimization approach for determining the optimal inspection and maintenance planning of a scrap-based steel production line. The DRL-based optimization maintenance recommends the adequate time for inspections and maintenance activities based on the monitoring conditions of the production line, such as machine productivity, buffer level, and production demand. Some practical aspects of the system, such as such uncertainty of the maintenance duration and the variable production rate of the machines, were considered. A scrap-based steel production line was modeled as a multi-component system considering components dependencies. A simulation model was developed to simulate the dynamics of the system and assist with the development of the DRL maintenance approach. The proposed DRL-based maintenance is compared with traditional maintenance policies, such reactive maintenance, time-based maintenance, and condition-based maintenance. In addition, different DRL algorithms such as PPO (Proximal Policy Optimization), TRPO (Trust Region Policy Optimization), and DQN (Deep Q-Network) are investigated in the case-based scenario. The findings indicated the potential for significant financial savings. Therefore, the proposed maintenance approach demonstrates system adaptability and has the potential to be a powerful tool for industrial competitiveness.

Keywords: Deep reinforcement learning; Inspections and maintenance optimization; Scrap-based steel production line; Multi-component system modelling (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832024002722
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:249:y:2024:i:c:s0951832024002722

DOI: 10.1016/j.ress.2024.110199

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().