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Lean Transportation in Science is no Longer “Terra Incognita”

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VIII International Scientific Siberian Transport Forum (TransSiberia 2019)

Abstract

The purpose of research is to determine the areas and justify why the use of the lean concept in these areas can provide improved performance of road transport at industrial enterprises. The research methods included: observation, collection, and analysis of statistical data, expert survey, modeling a transportation system, developing indicators for evaluating the efficiency of transportation losses elimination. An analytical review showed that in lean transportation, the first steps in scientific research aimed at adapting the principles of lean production to road transport operation are being taken. The research revealed the existence of at least sixteen types of transportation losses. This fact differs significantly from the results of the losses research in the industry. An expert survey to analyze the losses is used. The Delphi method is used to identify the causal chains of factors leading to the loss generation. To evaluate the mutual impact of causes, a quantitative assessment is performed. This leads to a significant acceleration in the work aimed at improving the operations of road transport that provides services to industrial enterprises. The “black box” model of the transportation system allowed identifying the resources of the transportation process participants as inputs. There are two other groups of input factors: cargo characteristics and external environment impact. The output characteristics of the model include transportation volume and its quality indicators. A differentiation of the spent resources into useful costs, which are used for cargo transportation, and losses, which are proposed to estimate using cost indicators, was provided.

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Correspondence to Valeriy Kurganov .

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Kurganov, V., Say, V., Dorofeev, A., Mukaev, V. (2020). Lean Transportation in Science is no Longer “Terra Incognita”. In: Popovic, Z., Manakov, A., Breskich, V. (eds) VIII International Scientific Siberian Transport Forum. TransSiberia 2019. Advances in Intelligent Systems and Computing, vol 1116. Springer, Cham. https://doi.org/10.1007/978-3-030-37919-3_70

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  • DOI: https://doi.org/10.1007/978-3-030-37919-3_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37918-6

  • Online ISBN: 978-3-030-37919-3

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