Developing a time scheduling algorithm for maintenance tasks: a case study at Hai Thach - Moc Tinh fields
Abstract
Using dataset sourced from the maintenance management application of Bien Dong Petroleum Operating Company (Bien Dong POC), the authors studied to employ genetic algorithms to schedule maintenance tasks, thereby shortening planning time, optimizing the involved resources, ensuring the consistency of the maintenance planning and implementation. Findings indicate that genetic algorithms effectively generate schedules with a high degree of accuracy, addressing multiple constraints related to time, priority, and resources for each task code, while significantly reducing computation time compared to manual scheduling methods. The study manifests the potential for implementing tools that automatically deploy such algorithms to support engineers, enhancing the efficiency and precision of maintenance planning and management process, especially at large-scale production facilities.
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