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Data-driven railway maintenance scheduling based on track condition prediction
Serie: International Heavy Haul STS Conference 2019. June 10-14, 2019. The Arctic University of Norway, NarvikUtgivningsinformation: uo : International Heavy Haul Association IHHA, 2019Beskrivning: 1 sÄmnen: Onlineresurser: Abstrakt: 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.Inga fysiska exemplar för denna post
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.