Capacity optimization of industrial railway systems

a case study at Tata Steel IJmuiden

Master thesis (2018)

Authors

C.W.P. van der Linden Mechanical Engineering

Contributors

M.B. Duinkerken (supervisor 1)
R.R. Negenborn (supervisor 1)
Faculty
Mechanical Engineering
Copyright: © 2018 Coen van der Linden
Railway Industrial railway systems Capacity optimization
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Published Date

18-01-2018

Language

English

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Faculty

Mechanical Engineering

Abstract

Industrial railway systems can be found within companies where the production and processing of goods require large quantities to be transported. These underdeveloped systems are often privately owned and are characterized by short to cover distances, many locations, inefficient layout due to historical expansion and bidirectional driving. Local optimization in such a system does not directly lead to a global improvement. This research suggest a new model to define and measure the performance of the system as a whole by using customer value from the theory of lean thinking combined with prioritization of transport tasks. In order to test the model and to optimize the capacity of an industrial railway system a case study is performed at the railway system of Tata Steel IJmuiden, the Netherlands. Through implementing the new customer value model into a discrete event simulation, a set of improvements in the field of locomotive assignment strategy, work schedule, network configuration and fleet size resulted in a global 10.7 percent improvement in performance.