Keywords

1 Introduction

Container terminal operation systems are complex and large and are designed to provide customers with high-quality service. United Terminal IMSs have been introduced to control operations and to accumulate real-time tracking data on containers and transporters at container terminals in ports. There is a potential need for logistics managers to have an intelligent tool, which should be developed to analyze these highly complex and dynamic logistics systems, making use of accumulated real-time tracking data.

2 Brief Literature Review

There are many studies focused on various issues concerned with container terminals. Several studies have used computer simulation to schedule cargo-handling equipment at container terminals (Kim and Kim 1999; Ng 2005; Guo et al. 2008). The issues of storage and stacking in the planning of ships and container yards can be addressed using simulation, which has been studied in recent years (van Asperen et al. 2010; Dekker et al. 2006; Zeng et al. 2010).

A current review of the literature indicates that few studies have been reported on the modeling of a whole container terminal system with a simulation based approach using electronic real-time tracking data. In this paper, a simulation approach is employed at all of the operations of real container terminals in Nagoya, Japan, specifically at the Nabeta Pier container terminal, to analyze the performance. The procedures of analyzing the operations performance is described, especially by using electronic real-time tracking data accumulated from the United Terminal IMS.

3 Simulation Modeling Steps

This section presents a brief overview of the steps of simulation modeling for materials handling systems of a container terminal.

Figure 1 represents a series of steps for applying simulation to container terminal systems. The first step, Raw Data Collected from United Terminal IMSs, helps to acquire a series of raw data, including handling instructions and handling completion information for transfer cranes, straddle careers, and top lifters, inbound vessel information. At Step 2, a series of raw data is processed and input data for simulation is extracted from the processed data based on the operation flows. During the simulation model-building step, system design configurations are developed based on the essential operation flows (i.e. importing process and exporting process). At Step 4, verification and validation of the simulation model is performed to determine whether the simulation model adequately describes the actual system performance. At the last step, simulation experiments are performed to analyze statistical parameters.

Fig. 1
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General simulation modeling steps

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4 An Example

4.1 Nabeta Pier Container Terminal

The Nabeta Pier Container Terminal in this study sustains the central Japan economic arena with a focus on multi-frequency small-sum cargo. A general view of the container terminal is shown in Fig. 2. Responding to the increasing amounts of container cargoes, the efficiency of materials handling operations are becoming a vital problem. Although the advanced United Terminal IMS has contributed to tracking the situations of containers and cargo-handling equipments to make operation control easier than before, it is still difficult for logistics managers to resolve the problem of ship inbound and outbound delays which can only be accomplished with real-time tracking data. Logistics managers need a sophisticated tool to integrate the electronics real-time tracking data with the advanced United Terminal IMS to analyze the bottleneck of operation flows, the processing time of different cargo-handling equipment and the average waiting time of the inbound and outbound ships.

Fig. 2
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A general view of a container terminal

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4.2 United Terminal IMS

The Nagoya United Terminal IMS is a computer-aided information management system used for planning for vessels, cargo-handling equipment and yard storage planning. Figure 3 shows the flow for the container operations and the data flows via the Nagoya United Terminal IMS. When a ship berths at the container terminal, a container is discharged by a quay crane and is unloaded onto an inside tractor that is waiting to transfer material to the yard storage blocks. Once the container is unloaded onto the bed of the tractor, the information on the loading completion will be transferred to the IMS. Nearly at the same time, handling instruction for containers-storage spots will be sent to cargo-handling equipment at the yard, including transfer cranes, straddle careers, and top lifters. It is possible to send these information to the next job in advance of the actual tractor arrival. In addition, it is valuable for the cargo-handling equipment at the yard to choose the next job in helping to make the proper decisions. In the meantime, the Nagoya United Terminal IMS will record the exact time when instructions are sent out as well as the time that handling completion information is accepted.

Fig. 3
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Container operation flows and data flows in the Nagoya United Terminal IM

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4.3 Data Collection and Processing

The overall flow of the data processing in this study is shown in Fig. 4. The electronic real-time information regarding the operation processes is designed for performing simulations repeatedly and effectively. Selected resultant input data for a real container terminal simulation is summarized in Table 1. A similar idea for creating experimental data for simulation experiments appears in the simulation of hospital wards (Takakuwa and Katagiri 2007; Wijewickrama and Takakuwa 2006). The simulation can be performed automatically, using a model together with the input data. Therefore, a judicious integration of real-time data into the simulation model will reduce the work load of specification, coding, validation, and verification of the simulation.

Fig. 4
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Overall flow of data processing

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Table 1 Selected resultant input data for the simulation of an actual container terminal
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4.4 Simulation Logic

Computer simulation is a methodology that can be used to describe, analyze and predict the performance of a complex business process without the limiting assumptions. In this paper, the simulation model is conducted with the Simio modeling software, version 3.48 (Kelton et al. 2010; Pegden and Sturrock 2010).

The fundamental operation processes in a typical terminal including importing and exporting processes are shown in Figs. 5 and 6. The importing process means that an inbound container is discharged from an inbound vessel by a quay crane and is unloaded onto an inside tractor that transfers material to the yard storage blocks.

Fig. 5
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Exporting process for a typical terminal

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Fig. 6
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Importing process for a typical terminal

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The exporting process is that an outbound container is loaded onto a tractor by cargo-handling equipment at the yard, such as transfer cranes, straddle careers, and top lifters, then transferred to an outbound vessel by quay crane. By using Simio modeling software, dynamic 3D animated models of container terminals can be built efficiently.

4.5 Analysis

The simulation model can be run to examine the overall operation processes for all of the cargo for the coming day, based on the exact electronic real-time data of the day. By performing the simulation, a number of performance measurement variables can be recorded and output. A part of the simulation results about tracking the outgoing containers is shown in Fig. 7. The average or maximum total time in this system can be analyzed and outputted by performing simulation. This result can be used to improve the performance of materials handling at the container terminals.

Fig. 7
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A part of the simulation result about total time of containers in system

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5 Conclusions

In this paper, by making use of electronic real-time tracking data that is accumulated from united terminal IMSs, a procedure is proposed to aid materials handling management for container terminals.

The proposed procedure is applied to an actual container terminal in Japan in order to confirm its effectiveness. It is found that the information obtained by performing simulation is effective for analyzing the performance of the materials handling operations at container terminals. In addition, the procedure is generic and can easily be expanded to model other ports.