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Abstract
One of the most important performance measurements in a container terminal is the productivity of the container handling system. This productivity is highly dependent, not only on the mechanical cycle time of each piece of handling equipment, but also on the idle time experienced by a piece of equipment when waiting for another piece of equipment during the handover of containers. This paper suggests a method to estimate the cycle time of an entire container handling system in a container terminal by using the normally distributed mechanical cycle time for each loading and unloading process performed by quay cranes, transporters, and the handling equipment in the yard storage system. This study presents a method that analyzes container handling systems in which containers are moved through multiple stages; there may be buffer spaces between adjacent stages for temporarily storing containers. The numerical results obtained through the analytic procedure are then compared to those obtained by simulation studies.
Keywords: Cycle time, Container terminal, Handling operation, Statistical model, Simulation
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1.Introduction
Container terminals play an important role in global trading and international business. Container terminal operations usually involve a complex set of handling processes operated using a combination of the various types of equipment found in container terminals. Therefore the synchronization between these different equipment types within the container handling system is very important.
The handling systems in container terminals are multi-stage systems. When the time needed for each operation is considered as a statistical variable, the correct estimation of the cycle time regarding the entire handling system can become very complicated. The process time of a stage affects the waiting or idle time of the equipment in the adjacent stages. In addition, this idle time is mutually dependent on the distributions of the cycle times of both adjacent stages.
Numerous mathematical models have been developed in other to estimate the performance of a single equipment type in a terminal. However, due to the complexity and the large scale of terminal operations, few models that cover the overall terminal operation have been developed. In order to remedy this drawback, this paper presents a statistical model that estimates the cycle time of the entire container handling operation in a terminal.
We start with...