Performance prediction model for a Ship-to-shore crane

Productiviteit predictie model van een schip tot wal kraan

Master Thesis (2020)
Author(s)

A. Nuur (TU Delft - Mechanical Engineering)

Contributor(s)

V. Reppa – Mentor (TU Delft - Transport Engineering and Logistics)

Niek Jongbloed – Mentor (Siemens Netherlands N.V., The Hague)

Douwe Wagenaar – Mentor (Siemens Netherlands N.V., The Hague)

Faculty
Mechanical Engineering
Copyright
© 2020 Ahmed Nuur
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Ahmed Nuur
Graduation Date
16-09-2020
Awarding Institution
Delft University of Technology
Programme
['Marine Technology | Transport Engineering and Logistics']
Faculty
Mechanical Engineering
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Abstract

This thesis presents the design of a performance prediction simulation model for an ship-to-shore crane. Current STS crane models do not take new trends in container terminal operations into account like automation. These models do not predict the performance accurately. This can lead to logistical and financial consequences. Automation systems that are present in the cranes should be taken into account when modelling. State-of-the-art models do not model the cycle path of the crane accurately, crane components are modeled in sequence while in real life the movements between the crane components are parallel. Moreover what is not included in these models are the accelerations/decelerations of these different components of the STS cranes. A new STS crane model is developed that consists of process blocks and all the lacking points. Data was used from a reference crane to verify and validate the new model. To evaluate the performance of the proposed prediction model, a comparison has been made with existing prediction models.

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