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Data-driven railway maintenance scheduling based on track condition prediction
Series: International Heavy Haul STS Conference 2019. June 10-14, 2019. The Arctic University of Norway, NarvikPublication details: uo : International Heavy Haul Association IHHA, 2019Description: 1 sSubject(s): Online resources: Abstract: Despite the importance and complexity of maintenance planning, modern data-driven approaches are underutilized in the management of railway assets. We here propose an approach for improved maintenance planning and scheduling based on predictive analytics and linear integer programming. The approach is currently being developed in collaboration with the Swedish Transportation Administration (Trafikverket) using real data.No physical items for this record
Despite the importance and complexity of maintenance planning, modern data-driven approaches are underutilized in the management of railway assets. We here propose an approach for improved maintenance planning and scheduling based on predictive analytics and linear integer programming. The approach is currently being developed in collaboration with the Swedish Transportation Administration (Trafikverket) using real data.