Abstract
There is extensive literature on scheduling approaches and scheduling in the area of maintenance. However, there is a lack of literature in using Artificial Intelligence (AI) approaches in the area of maintenance schedule, specifically, in offshore oil and gas platforms. This paper fills this gap by introducing AI-based maintenance scheduling.Maintenance scheduling in a large complex engineering system is hard as money is at stake due to the risk of failures. This is why companies use both computers and humans to make decisions and design executable schedules. This paper uses AI-based heuristic algorithms and a large neighborhood search (LNS) method for maintenance schedule in such an environment, where human interaction is required to make decisions. The successful implementation results show that the use of AI-based maintenance scheduling is a viable option for maintenance scheduling. The paper shows that the use of heuristic algorithms combined with LNS can perform maintenance scheduling tasks in a much more time efficient than a human-based planning. Hence, this has large industrial implications in the future.
Original language | English |
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Title of host publication | 2021 Annual Reliability and Maintainability Symposium (RAMS) |
Number of pages | 6 |
Publisher | IEEE |
Publication date | 2021 |
ISBN (Electronic) | 978-1-7281-8017-5 |
DOIs | |
Publication status | Published - 2021 |
Event | Annual Symposium on Reliability and Maintainability - Rosen Plaza Hotel, Orlando, United States Duration: 24 May 2021 → 27 May 2021 |
Conference
Conference | Annual Symposium on Reliability and Maintainability |
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Location | Rosen Plaza Hotel |
Country/Territory | United States |
City | Orlando |
Period | 24/05/2021 → 27/05/2021 |
Keywords
- Large neighborhood search
- LNS
- Artificial intelligence
- AI
- Maintenance
- Scheduling