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Data-Driven Study on the Sustainable Log Movements: Impact of Rail Car Fleet Size on Freight Storage and Car Idling

Author

Listed:
  • Sangpil Ko

    (Innovative Transport Policy Division, Korea Railroad Research Institute, 176 Railroad Museum Road, Uiwang-Si, Gyeonggi-do 16105, Korea)

  • Pasi Lautala

    (Department of Civil and Environmental Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA)

  • Kuilin Zhang

    (Department of Civil and Environmental Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA)

Abstract

Rail car availability and the challenges associated with the seasonal dynamics of log movements have received growing attentions in the Lake Superior region of the US, as a portion of rail car fleet is close to reaching the end of its service life. This paper proposes a data-driven study on the rail car peaking issue to explore the fleet of rail cars dedicated to being used for log movements in the region, and to evaluate how the number of cars affects both the storage need at the sidings and the time the cars are idled. This study is based on the actual log scale data collected from a group of forest companies in cooperation with the Lake State Shippers Association (LSSA). The results of our analysis revealed that moving the current log volumes in the region would require approximately 400–600 dedicated and shared log cars in ideal conditions, depending on the specific month. While the higher fleet size could move the logs as they arrive to the siding, the lower end would nearly eliminate the idling of rail cars and enable stable volumes throughout the year. However, this would require short-term storage and additional handling of logs at the siding, both elements that increase the costs for shippers. Another interesting observation was the fact that the reduction of a single day in the loading/unloading process (2.5 to 1.5 days) would eliminate almost 100 cars (20%) of the fleet without reduction in throughput.

Suggested Citation

  • Sangpil Ko & Pasi Lautala & Kuilin Zhang, 2020. "Data-Driven Study on the Sustainable Log Movements: Impact of Rail Car Fleet Size on Freight Storage and Car Idling," Sustainability, MDPI, vol. 12(11), pages 1-15, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4563-:d:366806
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    References listed on IDEAS

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    1. Hanif D. Sherali & Lawrence W. Maguire, 2000. "Determining Rail Fleet Sizes for Shipping Automobiles," Interfaces, INFORMS, vol. 30(6), pages 80-90, December.
    2. Kallrath, J. & Klosterhalfen, S.T. & Walter, M. & Fischer, G. & Blackburn, R., 2017. "Payload-based fleet optimization for rail cars in the chemical industry," European Journal of Operational Research, Elsevier, vol. 259(1), pages 113-129.
    3. Ruhollah Heydari & Emanuel Melachrinoudis, 2017. "A path-based capacitated network flow model for empty railcar distribution," Annals of Operations Research, Springer, vol. 253(2), pages 773-798, June.
    4. Martin Joborn & Teodor Gabriel Crainic & Michel Gendreau & Kaj Holmberg & Jan T. Lundgren, 2004. "Economies of Scale in Empty Freight Car Distribution in Scheduled Railways," Transportation Science, INFORMS, vol. 38(2), pages 121-134, May.
    5. Amar Kumar Narisetty & Jean-Philippe P. Richard & David Ramcharan & Deby Murphy & Gayle Minks & Jim Fuller, 2008. "An Optimization Model for Empty Freight Car Assignment at Union Pacific Railroad," Interfaces, INFORMS, vol. 38(2), pages 89-102, April.
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