Optimising quay crane operations based on data-driven cycle time prediction

A case study at APM Terminals MVII

Master thesis (2022)

Authors

L.V. Gerlach Civil Engineering & Geosciences

Contributors

B. Atasoy Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (supervisor 2)
J Vleugel Transport and Planning - CEG (supervisor 2)
R.R. Negenborn Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (supervisor 2)
F.A. Dekker (supervisor 2)
Faculty
Civil Engineering & Geosciences
Copyright: © 2022 Laurens Gerlach
Container terminal Quay crane Tandem
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Published Date

31-10-2022

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

Quay cranes on modern container terminals have the possibility to lift two 40ft. containers side by side. In order to be able to perform this type of lift, the crane must be equipped with a tandem spreader. As this type of spreader cannot be used for performing certain lifts, such as the handling of hatch covers, switches between single spreader and tandem spreader are inevitable. However, there is no method in current literature nor in practice to determine when the spreader changes should be performed. Therefore, the aim of this research is to develop a model that calculates the optimal moments to switch spreaders. As the performance of tandem lifting depends on the cycle times, a cycle time prediction model is developed first. This Artificial Neural Network model predicts the cycle time based on the type of lift, the actual position of the container(s) on the ship, the weight of the load and the current wind speed. The predictions yield a Mean Absolute Percentage Error of less than 11%. Afterwards, the cycle time prediction model is used to develop an optimal spreader switching strategy model in the form of a Mixed Integer Linear Programming model. A case study, in which several different bay layouts of a container ship need to be handled, shows a decrease in handling time of up to 22% compared to the traditional spreader switching strategy.