DocumentCode :
2250734
Title :
Modeling and analysis of harbor crane work efficiency using work cycle recognition
Author :
Aulanko, Samuel ; Tervo, Kalevi
Author_Institution :
Autom. & Syst. Technol. Control Eng. Group, Aalto Univ. Sch. of Sci. & Technol., Espoo, Finland
fYear :
2010
fDate :
6-9 July 2010
Firstpage :
61
Lastpage :
66
Abstract :
In harbor environment, the logistic chain consists of different types of cranes working either at the container yard or at the dock. In addition, there are separate vehicles for transferring the containers between the container yard and the dock. The work cycles of the cranes consist mostly of different types of container handling, catching and waiting tasks. Typically, it is not known beforehand which tasks are the most important in terms of the efficiency of the whole logistic chain. This paper utilizes the work cycle recognition method to analyze the work of the container cranes. In addition to the analysis of a single crane, the method can be used to analyze indirectly the efficiency of the whole logistic chain, when combined with the expert knowledge of the harbor operators. The method is implemented in two ship to shore (STS) container cranes from different harbors, and four rubber tired gantry cranes (RGT)s from three different harbors including altogether over 39000 work cycles from normal operation.
Keywords :
cranes; logistics; sea ports; container handling; container yard; dock; expert knowledge; harbor crane work efficiency; harbor environment; harbor operators; logistic chain; rubber tired gantry cranes; ship to shore container cranes; work cycle recognition; Analytical models; Containers; Cranes; Hidden Markov models; Logistics; Marine vehicles; Optical wavelength conversion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2010 IEEE/ASME International Conference on
Conference_Location :
Montreal, ON
Print_ISBN :
978-1-4244-8031-9
Type :
conf
DOI :
10.1109/AIM.2010.5695907
Filename :
5695907
Link To Document :
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