Delft University of Technology
FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl
Specialization: Transport Engineering and Logistics
Report number: 2016.TEL.7999
Title: Technologies of Automation
and Control for Container Terminals
Author: K. Li
Title Technologies of Automation and Control for Container Terminals
Assignment: literature Confidential: no
Supervisor: Dr. Ir. Y. Pang Date: February 2, 2016
This report consists of 48 pages. It may only be reproduced literally and as a whole. For commercial purposes, only with written authorization of Delft University of Technology is allowed. Requests for consult should be under the condition that the applicant denies all legal rights on liabilities concerning the contents of the advice.
Delft University of Technology
FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl
Student: Ke Li Assignment type: Literature
Supervisor: Y. Pang Report number: 2016.TEL.7999
Specialization: TEL Confidential: No
Creditpoints (EC): 10
Subject: Technologies of Automation and Control for Container Terminals
Modern container handling concerns improving the processes from ship arrival through container hinterland distribution by means of the technologies of automation and control. Worldwide the technologies can be found in the operations of ship loading/unloading, onsite transportation, storage, and so on. Together with integrated system control, container handling processes and operations can improved with respect to handling speed, safety and efficiency.
This literature assignment is to survey the state of the art automated equipment and technologies applied in container terminals. The control and management system for container handling will also be investigated. The survey of this assignment should cover the following:
To review the general container handling process including the description of sub-processes and involved equipment;
To summarize the functions and operations that can be automated;
To investigate the technologies to achieve automation and to describe relative applications; To survey the existing and feasible concepts, methods and principles for the control and
management of container handling systems.
This report should be arranged in such a way that all data is structurally presented in graphs, tables, and lists with belonging descriptions and explanations in text.
The report should comply with the guidelines of the section. Details can be found on the website. The mentor,
Abstract
The current decades see a considerable growth of container transportation. The increasing containers require promoted the development of automated container terminals. This survey decomposes the container terminal process into several sub processes and addresses the automation of different container handling equipment used in these sub processes. For all of sub processes, a theoretical background of equipment is illustrated as well as the specific technology that implements the automation. Some applications of existing automated container terminals or equipment manufacturers are enumerated as examples. Finally, control systems with a focus on particular processes or optimization are introduced.
List of Figures
Figure 1 Layout of Hamburg automated container terminal ... 3
Figure 2 Rotterdam ECT Terminal ... 4
Figure 3 unloading and loading processes of containers ... 4
Figure 4 Quay crane ... 7
Figure 5 HHLA dual-trolley cranes ... 7
Figure 6 Simplification of trolley model ... 8
Figure 7 A smart cameras on an automated anti-sway system ... 8
Figure 8 Diagram of anti-sway control ... 9
Figure 9 Absolute positioning for trolley and gantry ... 10
Figure 10 Optimum path for container crane positioning system ... 10
Figure 11 Application of 3-D scanner, scanning modes ... 11
Figure 12 Vision system for detecting chassis ... 12
Figure 13 An image taken from camera mount on crane ... 12
Figure 14 An overview of AGVs in an automated container terminal ... 13
Figure 15 AGV model by state transition ... 14
Figure 16 ALV model by state transition ... 15
Figure 17 Automated guided vehicle ... 16
Figure 18 Automated lifting vehicle ... 16
Figure 19 Road network on automated container terminal ... 17
Figure 20 Types of vehicle guide-paths ... 18
Figure 22 Overview of the DGPS system ... 20
Figure 23 Infrastructure of the system’s automatic context capture devices. ... 20
Figure 24 Average total waiting times of quay cranes in seconds ... 21
Figure 25 Unloading time of container carriers ... 21
Figure 26 Average occupancy degrees of QCs, ASCs and vehicles ... 22
Figure 27 Buffer size of quay cranes ... 22
Figure 28 Storage yard block ... 23
Figure 29 two layout of storage yard ... 24
Figure 30 storage yard for straddle carrier ... 24
Figure 31 Passing Stacking Cranes of in CTA ... 25
Figure 32 Two non-passing automated stacking cranes ... 26
Figure 33 Rail Mounted Gantry Crane for Automatic Container Stacking ... 27
Figure 34 incremental encoder and working principle ... 27
Figure 35 Container profile scanning with scanning laser 2-D ... 28
Figure 36 Laser Range Finder based Scanning System, one of Two Axes ... 28
Figure 37 Automated stacking crane with guiding beam ... 29
Figure 38 Simplistic graph for KALMAR ASCs ... 30
Figure 39 Two examples of KALMAR ASCs ... 30
Figure 40 A partial example of a stowage plan ... 32
Figure 41 An overall procedure of the B & B method ... 33
Figure 42 An Example of a Working Sequence List ... 34
Figure 43 An example of a simplified guide-path network ... 35
Figure 45 The procedure of the simulation-based learning for one vehicle ... 36
Figure 46 Routing strategies (loop routing, mesh routing and cross-over) ... 37
Figure 47 Flow chart showing feedback for integrated iterative algorithm ... 38
Figure 48 Non-passing collaborating ASCs system... 40
Content
Abstract ... I List of Figures ... II Content ... V
1. Introduction ... 1
Scope of literature survey ... 1
1.1. Report objective ... 1
1.2. Method and result ... 2
1.3. Report structure ... 2
1.4. 2. Container terminal ... 3
Terminal function and structure ... 3
2.1. Container handling process ... 4
2.2. Automation in terminal ... 5
2.3. 3. Unloading of the ship ... 6
Process introduction ... 6 3.1. Equipment ... 6 3.2. Automation technology ... 7 3.3. 3.3.1. Anti-sway system ... 7 3.3.2. Anti-collision system ... 9
3.3.3. Optimum path control ... 10
4. Container transport ... 13
Process introduction ... 13
4.1. AGVs and ALVs ... 16
4.2. Automation technology ... 18 4.3. 4.3.1. Multiple cross-lanes ... 18 4.3.2. Navigation system ... 18 4.3.3. Real-time monitoring ... 19
Comparison of AGVs and ALVs ... 20
4.4. 5. Storage yard ... 23
Process introduction ... 23
5.1. Stack structure and equipment ... 23
5.2. Automation technology ... 26
5.3. Application in reality... 30
5.4. 6. Control of container terminal ... 31
Quay crane management ... 31
6.1. Internal transport management ... 34
6.2. Storage and stacking logistics ... 37
6.3. 7. Conclusion and future research ... 43
Conclusion ... 43
7.1. Recommendations and future research ... 43
7.2. Bibliography ... 44
1. Introduction
The standardized steel shipping container was wildly considered to be used for the first time in 1950s [1]. Through the years, container transportation has steadily increased and marine container industry has grown into the most important mode of inter-continental cargo traffic. As a result of growth, the capacity of ships has been extended from 58 metal containers to 19000 TEU (twenty-foot equivalent unit) and more [2]. The increasing containers require higher demands of container terminals, as well as technical equipment. So the competition between terminals especially between geographically ones increased. The core advantages of competition are the rapid turnover of containers, namely a reduction of the berth time of container ships and of the costs of transshipment [3]. As a result, automated container terminals become more and more popular. This survey will introduce the equipment and automation of the container terminals.
Scope of literature survey
1.1.
This literature survey will give an overview of container handling in an import automated container terminal. Different pieces of equipment which are used in the handling process will be introduced. The focus is on the automation technologies applied on the equipment and applications of these automation technologies. The survey scope will be limited concerning operations in automated container terminals which mean vessel arrival and berth assignment will not take into account.
Report objective
1.2.
The objective of this survey is to provide an overview of containers handling process in an automated import container terminal, and how the equipment is automated by using the specific technologies and control methods. Furthermore, some control systems of automated terminal will be introduced (e.g. optimization of vehicles scheduling).
Method and result
1.3.
The theoretical knowledge is based on academic literature such as thesis, books, and papers on periodicals. The tools used for searching reference are academic searching engine such as Scopus, google scholar and digital repository like TU Delft library. The application of different processes or automation technology is mostly from documents provided by manufacturers, container terminals (i.e. ECT Delta Terminal in Rotterdam) and periodicals. These references are found from official homepages of specific company as well as papers found by academic searching engine.
Report structure
1.4.
Each chapter begins with an introduction of the corresponding process in an import container terminal. Then equipment are introduced with automation technologies as well as theoretical background and application in reality.
The survey is structured as follows. Chapter 2 shows the structure of import container terminals and container handling process. In the end, we give a definition of automation in container terminals. Chapter 3 illustrates equipment used in unloading process (from vessel to quayside) of containers as well as automation technologies on them. Chapter 4 introduces the container transportation in import container terminals. Two major kinds of handling equipment, AGVs and ALVs, are introduced in this chapter and a comparison is given in the end. Chapter 5 illustrates different storage yard layouts and stacking cranes. Then the automation technologies of equipment are illustrated. Different from other chapter, chapter 6 introduce the control and management instead of equipment. Some art in container terminal optimizations and operation research will be introduced.
2. Container terminal
Before diving into the actual automation of container terminal and equipment, some background of container terminal will be provided. An overview will be given about the functions and interior structure of container terminals. An explanation will be given about the different processes in import maritime container terminals. In the end, a definition of automation in terminals environment will be given.
Terminal function and structure
2.1.
Container terminals are generally believed to be described as open systems of material flow with two external interfaces. The interfaces are the loading/unloading of container ships from/to the quayside, and loading/unloading of the containers to/from trucks or trains. Containers are stored in terminal stacks in order to facilitate decoupling between quayside and landside operation. It is generally considered that container flows from landside to seaside called export and called import when reverse [4].
An automated import seaport container terminal can be divided into several parts which contain berthing area, AGV area, storage area and hinterland operation area. The berthing area is equipped with quay cranes for loading and unloading of vessels. The storage area consists of blocks that are serviced by one or more automated stacking cranes. The transport of containers between berthing areas and storage area is realized by AGVs or ALVs which move in AGV area. The layout of automated container terminals is illustrated as Figure 1 [5] and Figure 2 [6].
Figure 2 Rotterdam ECT Terminal
Container handling process
2.2.
Figure 3 [7] shows that the container handling process starts at vessel berths assignment. Once the vessel has moored, one or more quary cranes will begin unload the ship follow unload plan. The quary cranes retrieve outbound containers from ship and deposit them on transport vehicles. Then the containers are transported to the respective stocks in the yard where they are temporarily stored until they are either transported inland (by external trucks or rail) or transported to another vessel (by AGVs or ALVs). The transport beween stack and other modalities is performed either by trucks with trailers, muti-trailers or straddle carriers [8].
Automation in terminal
2.3.
The definition of automation used within this survey is the use of various technologies for container operating and transportation with minimal or reduced human intervention [9]. The focus is on automation technologies of container handling equipment and control systems in automated container terminals. Consequently, on one hand, automation technologies are applied on equipment to reduce human labor. On the other hand, automation technologies improve the performance of equipment as well as the logistics of terminals. In unloading processes, quay cranes can be automated by sensors like laser scanning and camera cooperate with control systems. As for transportation in terminals, for example, automated guided vehicles can be used as container carriers. In storage, automation can be realized either by stacking cranes or straddle carriers. Finally, automation technologies are also embodied in the management of terminals.
3. Unloading of the ship
The first step of container handling in an import automated container terminal would be the automatic unloading containers from container ship. In this chapter, the quay crane will be shortly introduced and key technologies of automation in this sub process will be highlighted. The technologies consist of Anti-sway crane control, Anti-collision system, optimum path control, chassis alignment system, power supply and converters. After providing a theoretical background, current applications will be illustrated.
Process introduction
3.1.
When a container ship arrives at the port, quay cranes begin to unload the containers. Firstly, cranes scan the ship profile and detect containers on the deck. The spreader use positioning system locates twist locks and lock automatically. When lifting the containers, crane need calculate the lifting height and movement trajectory in case crashing to other containers or cranes. At last, cranes deposit containers on AGVs by using The Chassis Alignment System. Also some optimizing algorithm will be used for improving the equipment performance.
Equipment
3.2.
Concerning cranes, there are two kinds of crane used at quayside, single-trolley crane and dual-trolley crane. Trolley moves along the arm of a crane and equipped with spreader. Single-trolley crane can move containers either to the quayside or on a vehicle while dual-trolley crane need moves container to a platform by a main trolley and use a second trolley move the container from platform to the shore. Figure 4 [6] give an example of single-trolley crane. Dual-trolley crane are heavy and expensive which in practice, are not economic. But with modern technology and automation, the productivity of dual-trolley cranes could be improved [10]. The HHLA terminal in Hamburg, Germany purchased dual-trolley cranes, see Figure 5 [11].
Figure 4 Quay crane
Figure 5 HHLA dual-trolley cranes
Automation technology
3.3.
3.3.1. Anti-sway system
The actual crane system is complex, in addition to the nonlinear factors (e.g. acceleration and breaking) of the transmission components, some external disturbances, such as wind, hit or motion of the crane support unit can cause the oscillation. The oscillation may bring damage to surrounding equipment and the payload itself; also, swing makes precision positioning time consuming and inefficient to transporting operation [12].
Firstly, we provide some basic principles of anti-sway systems. A simplified rope-towed trolley model is shown as Figure 6 [13], consisting of a weight suspended on a long string. When the weight is offset from vertical, it might have pendular movement along horizon directions. Accordingly, when the weight is motionless and the trolley begins to move, then the sway occurs. And when trolley suddenly stops, there will be residual sway. However, if the motion of trolley is controlled properly, the sway can be eliminated from the accelerations. So, anti-sways system make the trolley accelerate in several pulses, allowing the load to catch up with the trolley. The deceleration is also in several pulses, letting the load get first ahead of the trolley and then the trolley catches up with the load. The load is being lowered rapidly at the
end of the move [13]. However, an actual crane is not as simple as model. The crane dynamics is highly nonlinear, and due to external disturbance.
Figure 6 Simplification of trolley model
The sensor consists of a camera mounting on the crane trolley. The input to the camera comes from an infrared light mounting on the spreader, see Figure 7 [14]. Near-infrared (NIR) markers are mounted onto the crane spreader to make sure the system can operate in variant weather conditions [15]. A smart camera is mounted on the crane’s trolley to image these markers. Generally, the working distance from the camera to the NIR markers is between 3 and 50 m, so the camera is fitted with a 12-mm lens which provides a viewing angle of 28°, allowing the spreader to always remain in the camera's field of view. As the camera digitizes the images, the center position of the tow markers is calculated in real time, providing an accurate position of the spreader. For example, when the working distance between the camera and the spreader is 50 m, the error range of calculation is within 10 mm. The data are then transferred to a PLC by a fiber-optic data link. This PLC is interfaced to an electronic control system that regulates the movement of the crane's trolley, effectively reducing any container sway that may occur [16] [17].
Figure 7 A smart cameras on an automated anti-sway system
to another) without causing an excessive swing motion of the payload. The mathematical model of the crane system including the characteristic of oscillation is required to generate the modified reference input. The control diagram is shown in Figure 8 [18]. For each control loop, position controller modifies the trolley position according to trajectory made by reference modifier and reality position measured by position sensor. Reference modifier is dynamically changing because of external disturbances [18].
Figure 8 Diagram of anti-sway control
Another application is realized by PAR Systems. PAR Systems is a system engineering company headquartered in Shoreview, Minnesota, specializing in automated manufacturing and material handling equipment [19]. AUTOMOVE is an automatic position system developed by PAR allowing for automatic and precise payload positioning. Automatic motion can be initiated and monitored by an operator. AUTOMOVE use bridge and trolley laser realize detection and motor controller for automatic position system and smart camera installed on headblock for sideload & snag detection. As for Anti-sway technology, AUTOMOVE choose the sway sensor cooperating with motor controller [16] [20].
3.3.2. Anti-collision system
In practice, collision may happen between two quay cranes or between trolley and main beam of quay crane. Positioning for cranes and trolley are based on integrating of speed, positioning system utilizing the motor with software and position measuring [21]. Anti-collision system ensures safe operations by continuous supervision of the speed feedback together with position check at calibration points. For crane trolley and gantry position, absolute position sensors are used, see Figure 9 [21]. A series of limit switches indicate the location of the trolley. The trolley firstly reaches a position prior to the final location detected by reading head. At this point the deceleration program is initiated. As it approaches the final stop position, location inputs further reduce the speed until a position just before or at the final stop. The final positioning accuracy is now dependent upon the sophistication of the
crane drive, see first photo in Figure 9. Encoders coupled to the motor, running off a drive or idler wheel, provide another method for determining hoist and trolley location. The encoder counted the revolutions or increments of a revolution, and the controller determines position from this information [22], see second photo of Figure 9. Rather than using counting or address positioning, infrared laser could be used for measuring distance. The devices must be connected to a PLC or PC for calculations and control. Packaged systems contain their own microprocessor or software to allow them to determine the location from a fixed point. This location information must be interfaced to a PLC or PC so that information is useful to the rest of the control system [22].
Figure 9 Absolute positioning for trolley and gantry
3.3.3. Optimum path control
The optimum path control system adds a trolley and hoist positioning function to the basic sway control. The optimum path controller calculates the most efficient combination of horizontal and vertical motion instead of hoisting along maximum height path. This optimizes the crane performance and minimizes the cycle time, see Figure 10 [21].
The profiling detection is done by 3-D laser scanning. The 3-D laser scanning consists of a 3-D laser mounted on the spreader and a data processing unit. Laser is arranged aims at desired position providing edge detection and accurate profiling. Typical application of 3-D scanning laser is shown in Figure 11 [21]. The sensors detect the obstacle and stack during the traveling process of the trolley. In hoisting down process, the sensors provide precise position of under container and bilateral containers [21].
Figure 11 Application of 3-D scanner, scanning modes
The ship profile scanning based on 2-D laser scanning, measure the container stack height and also the distance to land in the ship cell [21].
3.3.4. Chassis Alignment System
The container crane position over several parallel traffic lanes where container carriers enter with loaded or empty chassis. The carrier travels in the gantry direction perpendicular to trolley movement. As the trolley’s movement ability is extremely limited in this direction, the carrier need to position the chassis very accurately [23]. The Chassis Alignment System (CAS) guides the terminal chassis to stop in a proper position aligned to the crane enabling faster loading and unloading cycles. CAS consists of 3D-laser scanners, traffic lights and communication interface. The laser is placed on the beam between landside and waterside legs. The height allows the scanner covering all lanes and full length of chassis; see Figure 12 [24]. In discharging process, the operator decides the load position and lane number. CAS then receives an order from crane control system. The operation type is decided by twistlocks on spreader. If the twistlocks are locked, the operation is discharging and CAS starts measuring for an empty chassis. The laser scanner then scans the active lane. When
the rear part of chassis is detected, the laser sends a signal to the traffic lights to alert the driver [23].
Figure 12 Vision system for detecting chassis
The CAS also can be done by vision-based system instead of laser scanner. The laser scanner is expensive and has a limitation that the laser measure one lane same time. The image took by camera is shown in Figure 13 [25]. Due to different environment condition, it is hard to use the grayscale information in the images. The system uses the edges of object for recognition. The corresponding features of chassis and containers are represented by CAD-models loaded in system at the start. The system detects the chassis, containers by matching algorithm [25].
Figure 13 An image taken from camera mount on crane
ABB provide an automation solution which consists of Chassis Alignment System, Electronic Load Control (similar to anti-sway system) and Ship Profiling System [26] [27].
4. Container transport
A variety of vehicles is employed for the ship-to-shore transportation and the landside operation. The transport vehicles can be classified into two types. First class is ‘passive’ vehicles because of inability of lifting containers by themselves. Loading and unloading of these vehicles is done by cranes. AGVs (automated guided vehicle) belong to this type [28]. Transport vehicles in second type are able to lifting containers by themselves and straddle carriers are the most common vehicles. Because of the ability of lifting containers, automated straddle carriers also be called ALV (automated lifting vehicle). Both AGV and ALV are able to automatically drive on terminal road which consist of electric wire or transponders in order to control AGV’s or ALV’s position.
Process introduction
4.1.
Figure 14 [28] provides a layout of automated container terminal with AGV’s movements. AGVs need to be loaded or unloaded by quay cranes or automated stacking cranes. In an automated container terminal, the control system assigns an idle AGV to unloading quay crane. After unloading the container on AGV, the crane activates the AGV which moves to destination. At the destination the AGV activate the automated transfer crane (or called automated stacking crane) and wait until unloading is completed. Then the AGV becomes idle again and repeat the cycle [29].
As shown in Figure 15 [28], the AGV model uses a state transition which consists of six states. It also contains two conditions in order to check the availability of the buffer zone. At the end of the AGV’s task, the state of AGV transitions from a moving state to an idle state. The time interval between the start time and the end time of a relevant event is defined as the transition time of a state.
Figure 15 AGV model by state transition
TP: Transfer Point
ATC: Automated Transfer Crane
The ALV model also utilizes state transition, as shown in Figure 16 [28]. It includes eight conditions: the upper four conditions represent situations of the yard and the lower four conditions represent situations of the apron. From those conditions, we know that the ALV model is different from the AGV model. In addition, the ALV model divides the waiting time of the operation into loading and unloading periods.
Figure 16 ALV model by state transition
TP: Transfer Point
ATC: Automated Transfer Crane
CC: Container crane
AGVs and ALVs
4.2.
In automated logistic systems, automated guided vehicles (AGVs) are used for transportation tasks. To deal with the interaction in such an AGV system one needs efficient and intelligent routing on one hand and collision avoidance on the other hand. Additionally, the route computation has to be done in real-time, which means answer the requests online and in appropriate time. Each request consists of the source, the target and the starting time of a transportation task. Figure 17 [6], Figure 18 [30] and Figure 19 [6] give an example of AVGs, ALVs and road network respectively.
Figure 17 Automated guided vehicle
Figure 19 Road network on automated container terminal
AGVs applied earlier than ALVs, most automated container terminals use AGVs as the automation carrier solution. For example, AGV is used by Container Terminal Altenwerder (CTA) [11] which is one of the most modern Container Terminal. Patrick Terminal in Australia is one of advanced container terminals uses ALVs as container carriers [31].
Automation technology
4.3.
4.3.1. Multiple cross-lanes
Closed-loop and crosslane are two types of guide-path networks in automated container terminal. The closed-loop guide-path allows a simplified control that is composed by a large circle path for automated vehicles; see Figure 20 (a) and (b). However, closed-loop guide-path will increase the travel time of vehicles. Most automated container terminal use the second scheme to speed up the unloading process namely crosslane path; see Figure 20 (c) and (d). The crosslane consist of parallel paths with several crossing and automated vehicles will choose the shortest path when traveling between quayside and storage yard. The crosslane guide-path needs more complex traffic control for the terminal management [28].
Figure 20 Types of vehicle guide-paths
4.3.2. Navigation system
Automated container terminal use inertial navigation systems as AGV navigation system. Transponders (often magnets) are embedded in the ground at certain x, y coordinates in a map of the system. Transponders are detected by a sensor on the vehicle as it passes over the reference point; see Figure 21 [32]. A gyroscope on the vehicle measures/maintains vehicle’s heading. A wheel encoder on the vehicle calculates the distance traveled. Vehicle uses feedback from all three devices to determine location [33]. And control center uses the AGV location information mapping every AGV in the terminal.
Figure 21 AGV navigation system
4.3.3. Real-time monitoring
As automated container terminal need real-time system to achieve flexible terminal management, tracking and tracing of AGVs become the key issues. Differential Global positioning system (DGPS) and radio frequency identification (RFID) can be a solution for tracking and tracing [34]. Ngai el al. provide an intelligent context-aware system using ZigBee, DGPS receivers, and infrared (IR) sensors, see Figure 22 [35]. DGPS uses a network of fixed, ground-based reference stations to broadcast the difference between the positions indicated by the GPS (satellite) systems and the known fixed positions. The digital correction signal is typically broadcast locally over ground-based transmitters of shorter range. This system can improve accuracy from the 15-meter to about 10 cm in best implementation [36]. In RFID system, it use ‘context’ to represent the information that can be used to characterize an entity. The author description [37]: Context is any information that can be used to characterize the situation of an entity. And context-aware computing is defined as the use of context to provide task-relevant information and/or services to a user [37]. In the system, the contexts are automatically captured by ZigBee, DGPS receivers, and infrared (IR) sensors. ZigBee tag is a small RFID tag that uses the ZigBee protocol to communicate and can be integrated with various sensors to detect environmental conditions [38]. ZigBee coordinators (ZC) are on quay cranes (QCs) and Rail transfer gantry cranes (RTGCs), while ZigBee routers (ZR) are on AGVs or ALVs. IR sensors were installed on the AGVs to detect whether any container is loaded. The ZR will join the network initiated by the ZC on the QC or RTGC when the AGV approaches a QC or RTGC, see Figure 23 [35]. Therefore, the QC and RTGC can recognize each AGV, and by the data send by Zigbees, the control system on QC and RTGC receive the AGV’s situation like loading status detected by IR. The DGPS receivers on the QCs and RTGCs receive AGV’s latitude coordinates continuously and send them to the server using Wi-Fi.
Figure 22 Overview of the DGPS system
Figure 23 Infrastructure of the system’s automatic context capture devices.
Comparison of AGVs and ALVs
4.4.
In automated import container terminals, containers are transshipped from quay cranes to stack. This procedure can be done either by AGVs or ALVs. Both AGVs and ALVs transport containers over fixed paths. The difference is ALV could lift container itself. Here a comparison between AGVs and ALVs will be made by using simulation models.
Some criteria must be used before choosing a certain type of equipment. The criteria are waiting time of cranes, occupancy degrees of quay cranes, automated stack cranes and vehicles, unloading time of the ship and the number of vehicles required at terminal [3].
Waiting time of quay cranes
It can be noticed that waiting time of AGV is much longer than ALVs. However, this can be solved by adding AGV and ALV numbers; see Figure 24 [3].
Figure 24 Average total waiting times of quay cranes in seconds Unloading time of the ship
Using either AGVs or ALVs does not impact the unloading time of a ship. However, 38% more AGVs need to be used than ALVs. If using purchasing costs of vehicles as criteria, ALVs should be chosen as the transport equipment, see Figure 25 [3].
Figure 25 Unloading time of container carriers
Occupancy degrees of vehicles and quay cranes
In the unloading process, the quay cranes are the bottleneck [3]. As a result, the occupancy degrees of quay cranes are higher than that of various automated stack cranes; see Figure 26 [3]. So the transport modality does not affect occupancy of cranes.
Figure 26 Average occupancy degrees of QCs, ASCs and vehicles Size of buffer
The size of buffer area at quay cranes influences the number of vehicles required to minimize unloading times of the ship. Buffer size do not affect AGVs due to AGVs need crane to load and unload containers, see Figure 27 [3].
Figure 27 Buffer size of quay cranes
In addition, the layout of the terminal (buffer size at the quay crane) and technical aspects of equipment (quay crane and vehicles) influence the choice of equipment, when considering purchasing costs as decision criteria.
5. Storage yard
The container terminal has a key function to provide a buffer between quayside operations and hinterland operations which is achieved by storage yard. The function of storage yard is to provide space for containers staying in the terminal until forward transportation. This chapter will give an overview of the stacking process as well as key technology used in automation of both equipment and process management. In the end, some applications of automated storage yard will be illustrated.
Process introduction
5.1.
Storage yard is connecting the quayside and landside in container terminals. No matter importing, exporting or transshipment, containers will be stacked in storage yard for the time staying in the terminal between being imported or exported again [39]. In an importing process, stacking cranes take the container from an AGV or on ground in an I/O point at the quayside of the lane, and then drop the container at specific position in yard. After the storage, stacking cranes take the container in yard, and then discharge it onto a truck or train that is going to inland. Sometimes reshuffles are needed when the target container is under another container.
Stack structure and equipment
5.2.
A typical yard is composed of multiple rectangular blocks, and each of the blocks consists of several rows of containers, see Figure 28 [39].
Figure 28 Storage yard block
There are two kinds of yard layout for gantry cranes. The main difference is in the location of the input/output (I/O) point (i.e. the place for the transfer vehicles and the stacking cranes exchanging containers).
The first configuration (see Fig. 29a [39]), typically used in non-automated storage yards, has one or more rows in each block as truck lanes. Transfer vehicles (e.g., trucks) travel in the truck lane(s) until they reach the operation position request by
stacking cranes. In this configuration, the gantry crane travels to the truck lane for container operating. Relatively, the second configuration (see Fig. 29b [39]) that are used in automated yards, has blocks positioned perpendicular to the quay. The I/O points are located at both ends of the storage blocks to respectively. Automated guided vehicles (AGVs) are used to pick up and deposit containers at the seaside I/Os, while external trucks are used at the landside I/Os [39].
Figure 29 two layout of storage yard
The yard layout will be different when terminal use straddle carrier, see Figure 30 [39]. There are separations between rows so the straddle carrier can moves into rows. In this layout, containers are stacked with a height between 1 to 5. The I/O points are at the end of the blocks, and lanes are positioned in parallel to the quay. Moreover, also the layouts for straddle carrier similar to gantry crane layouts that lanes can be positioned perpendicular to the quay.
Frequently used container handling equipment in storage yard is gantry crane. There also two kinds of gantry crane in container terminals namely rail-mounted cranes and rubber-tyred cranes. Rubber-tyred cranes are not automated as they have flexibility to travel freely. The automated rail-mounted gantry cranes need keep a minimal distance from each other for safety reason. To improve the throughput of the storage yard, dual passing cranes can be used in collaboration. Figure 31 [11] shows a dual passing crane used in CTA in Hamburg. There are also non-passing cranes used in automated container terminal (see Figure 32 [39]), which need priority rules and optimizing algorithm.
The dual passing crane system is composed of two ASCs, show in Figure 31, a large one and a small one. This configuration allows each ASC to access I/O points on both sides of the stack. There are two type of interference between the ASCs. When the larger ASC is lifting or putting down a container, the smaller ASC is not able to pass. And interference also occurs when the two ASCs are performing a request in the same bay. However, prioritizing the ASCs under this configuration is not too detrimental to the performance of the system as after the interruption (however it is resolved) the ASCs may pass each other and continue with their schedules [39].
Figure 31 Passing Stacking Cranes of in CTA
In the non-passing configuration, shown in Figure 32, ASCs cannot reach both ends of the block. Instead, ASCs are operated independently or collaborate by an exchange zone. Once the cranes operate independently, the requests must be assigned to the corresponding crane serving the corresponding I/O point. In this case, any potential interference between the ASCs is easily handled by carefully scheduling the cranes. However, the ASC prioritization problem becomes much important and more complex for two reasons: (1) an inefficient priority rule could have a potentially detrimental impact on the system since the ASCs cannot pass each other; and (2) the priority rules need to consider the dynamics of the exchange zone which are non-existent in the other multi-crane configurations [39].
Figure 32 Two non-passing automated stacking cranes
Automated stacking cranes (ASCs) allow fully automated management of container storage yards which are the efficient link between quayside and landside equipment such as ship loading and unloading cranes, vehicles for horizontal container transport and road trucks.
Automation technology
5.3.
Sophisticated sensors are mounted on the crane to detect the position of the moving parts, the load, and target destination. These sensing systems include encoders and scanning laser rangefinders as shown in Figure 33 [40].
The positioning system uses laser scanner to make direct measurement of the distance between gantry, trolley and spreader. The laser rangefinders can works unaffected by factors like rope stretch and wheel slippage. The theory of laser scanner is using laser beam to determine the distance to an object which can be calculated by the returning time of laser. And 3D laser scanners on trolley can construct digital 3D model of lifting spreader and target container. With these measurements the crane can automated operating containers with yard management system collaboration.
Figure 33 Rail Mounted Gantry Crane for Automatic Container Stacking Incremental encoder
Displacement can be measured by incremental encoder (Fig. 34 [41]) which is an electrical mechanical device that converts linear or rotary displacement into digital or pulse signals. The most popular type of encoder is the optical encoder, which consists of a rotating disk, a light source, and a photo detector (light sensor). The disk, which is mounted on the rotating shaft, has patterns of opaque and transparent sectors coded into the disk. As the disk rotates, these patterns interrupt the light emitted onto the photo detector, generating a digital or pulse signal output; see second grapg of Figure 34. The gantry position can be automatically calibrated via signal from transporter embedded on ground and incremental encoder. The most common type of incremental encoder uses two output channels (A and B) to sense position. Using two code tracks with sectors positioned 90° out of phase; the two output channels of the quadrature encoder indicate both position and direction of rotation [41].
Lasers sensors
The scanning laser 2-D consists of a two-dimensional laser scanner together with a data processing unit in an enclosure for mounting on the crane. Fast two-direction scanning arrangement aims laser at desired position providing edge detection, surveillance and accurate profiling; see Figure 35 [21].
Figure 35 Container profile scanning with scanning laser 2-D
Advanced automation system uses laser scanners which measure the distance and angle to any surfaces, such as the container, the lifting spreader, and target container, as shown in Figure 36 [40]. A second axis scanner picks up the ends of the containers. With these measurements the crane control can automatically pick and land containers in the stacks, based on instructions issued by the yard management system [40].
Rigid Guiding Beam
There is also some new concept for anti-sway except those introduced in chapter 3. Gottwald automated stacking crane uses a guiding beam instead of rope field. The guiding beam are moved by powerful four-rope hoists and guided by rollers. The guiding beam is faster, accurate positioning under all condition such as wind. Then multiple rope deflection and rope adjustment no longer needed, see Figure 37 [42].
Application in reality
5.4.
Kalmar offers cargo handling solutions and services to ports, terminals, distribution centers and to heavy industry. One in four container movements around the world is handled by Kalmar solution. In 1990, the ASCs of ECT Delta Terminal in Rotterdam are first introduced by Kalmar [43]. Figure 38 [44] and 39 [43] show the stacking in automated container terminals designed by Kalmar.
The ALVs put containers in corresponding I/O area of stack. Typically, I/O area has buffering capacity to realize decoupled operations. AGVs do not need to wait an ASC for loading or unloading. ALVs are controlled remotely by wireless connecting. ASCs and landside cranes connect to operator’s room by wired connection [44].
Figure 38 Simplistic graph for KALMAR ASCs
6. Control of container terminal
In an automated container terminal, automation technologies are not only reflected in equipment but also in the art of operations. In this chapter, some researches with a focus on particular processes or subsystems in an automated terminal will be discussed.
Quay crane management
6.1.
Quay crane scheduling
The productivity of a container terminal relate to two types of operations. One is the ship operations, in which containers are discharged from a ship. The other one is delivery operations, in which containers are transferred to trucks [45]. Quay crane scheduling problem is pertinent to ship operation planning, the discharge and load sequence of individual containers are determined based on a QC schedule.
Figure 40 [45] illustrates a stowage plan for a ship. This plan consists of four cross-sectional views, each corresponding to a ship-bay and labeled with an odd number from 1 to 7. Each small square represents a slot. Shaded squares correspond to slots that containers must be discharged from or loaded onto in this container terminals. The shaded pattern in each slot represents a specific group of containers to be loaded into or picked up from the corresponding slots. Therefore, the figure shows that four groups of containers should be discharged from five clusters (a cluster is defined to be a collection of adjacent slots into which containers of the same group are planned to be loaded) of slots and then four groups of containers should be loaded into five clusters of slots [45]. The characteristics of the operation are:
Discharging and loading are performed at the same ship-bay; the discharging operation must before the loading operation.
When discharging, upper containers are performed before nether containers. Thus, there are precedence relationships among containers.
Certain pairs of tasks cannot be performed simultaneously when the locations of the two clusters corresponding to the tasks are too close to each other
Figure 40 A partial example of a stowage plan
Kim et al. [45] used a branch-bound algorithm with a greedy randomized search procedure to solve the quay crane scheduling as well as load sequencing. The objective is to minimize the weighted sum of makespan of container vessel and completion time of all quay crane which work on the vessel. They separated the crane scheduling problem from berth scheduling problem and the research is restricted to one single vessel.
Branch and bound (B&B) method process, see Figure 41 [45]:
Select the next branching node until the first feasible solution is found
Select the next branching node after the first feasible solution is found
Make feasible children nodes from the branching node
Delete dominated nodes
Calculate the lower bound of children nodes
Figure 41 An overall procedure of the B & B method Greedy randomized adaptive search procedure (GRASP):
Solution construction phase: an element of a solution is added iteratively to an incomplete solution, and the value of the element is selected by using a random number and a greedy function.
Solution improvement phase: the constructed solution is locally improved until no more improvement is possible. Iterations are repeated a prespecified number of times. Then, the best solution is selected among all the obtained solutions.
The B&B method will obtain the optimal solution while GRASP will find near-optimal solutions to the problem. The final objective values found by GRASP exceed that by the B&B method by less than 10% when the parameters of GRASP have values within specified ranges. In addition, on the average, GRASP reduced the computational times to 3% of those of the B & B method when the number of QCs and the number of tasks exceeded 3 and 20, respectively. From a practical perspective, the computation time of GRASP was satisfactory [45].
Moccia et al. [46] compared the difference between time precedence with route precedence quay cranes scheduling problem. They strengthen the model of Kim and Park by taking crane interference into account. They use Branch-and-Cut Algorithm that adds several families of valid inequalities into the Kim and Park’s B&B model. All of the inequalities are redundant for model but can strengthen its LP (linear programming) relaxation. In addition, they modify the subtour-elimination constraints by taking into account the precedence relationships. Finally, Moccia et al. develop an improved model of solving small and medium-size instances [46].
Internal transport management
6.2.
Dispatching Method for AGVs
Automated guided vehicles (AGVs) play an important role for synchronizing operations of quay cranes with stacking cranes. For AGVs, Kim and Bae [47] proposed an extended model for AGV dispatching based on previous models [48] [49]. The objective is to minimize the idle time of AGVs.
Problem description:
Loading operations by a container crane (CC) begin with picking up a container in yard location (from an AGV), while a discharging operation cycle ends with discharging a container onto yard location (onto an AGV). Figure 42 [47] shows an example of sequence lists of ship operations for two CCs (CC 1 and CC 2) in a dual-cycle manner. 𝑠𝑖𝑘 represent the earliest possible event time of operation by CC (k) for ith container. For there is no buffer space at discharging or loading points, an
AGV must wait at the pickup and drop-off point until a CC (or an AYC) completes a corresponding operations. So it is important to simultaneously minimize the delay time of CCs and the travel time of AGVs. In the scheduling, the operation time of CC is an uncertainly factor, therefore, the dispatching algorithm need provide a dynamic situation for AGV dispatching time [47] [50].
Figure 42 An Example of a Working Sequence List
The Look-Ahead dispatching method uses a mixed-integer programming model for assigning optimal delivery tasks to 0AGVs. The author also makes a comparison of performances between their algorithm and popular dispatching rules. According to a numerical experiment, it is found that their algorithm has advantages over conventional dispatching rules in both deterministic and stochastic environments [47].
Routing function and strategy of the AGVs
The routing function plays a big role in an AGV control system of automated container terminals. The routing function selects a specific path for AGV to move from present position to destination. In static routing systems, an AGV is given a predetermined route. Usually, shortest-distance routes are provided t. This results in an easy control method, but it does not guarantee for the efficiency of the AGV operations due to mutual influence between the vehicles and waiting times. Jeon et. al. [51] adopt a Q-learning technique to determine the shortest-time routes for internal transport using AGVs.
Figure 43 [51] illustrates a simplified guide-path network with nine nodes and given travel times on the arcs. Figure 44 [51] show a route matrix R for this network indicating a path between any two nodes. For a path from a starting node i to the destination node j, the immediate successor of i is given by R(i,j), the next successor is given by R(R(i,j),j), and so on until the final destination j is reached.
Figure 43 An example of a simplified guide-path network
Figure 45 [51] describe the simulation-based learning procedure by a single AGV. Note that the Q-table is updated during the simulation, and Q-table is calculated by matrix R. Q-table records the expected discounted travel time of a vehicle from starting node and destination node. As a dynamic method, whenever the AGV get to a node, the Q-table is again calculated according temporal situation. In the learning process, traffic control rules are needed as dead-lock for the routing. Finally, as a result of using the learning algorithm, the travel time of AGV can be reduced by 17.3% comparing to shortest-distance routes [51].
Figure 45 The procedure of the simulation-based learning for one vehicle
The routing system in automated container terminals can be either fixed layout or free ranging. However, with fixed layout routing system, the flexibility is limited and often the infrastructure is not optimally used. A dynamic free ranging approach for AGV routing system is introduced by Duinkerken. Duinkerken et al. [52] use simulations analyzing different trajectory planning strategies for AGVs. As shown in Figure 46 [52], the first graph illustrates the loop routing strategy, the average trajectory length will be the sum of the stack length and the terminal width; the second graph illustrates the mesh routing, the minimum distance will be the sum of the absolute difference in x- and y-direction (Δx and Δy respectively); the third graph illustrates the cross-over strategy which result a straight like connection, and this is the shortest path.
Figure 46 Routing strategies (loop routing, mesh routing and cross-over)
A 2D collision detection algorithm, based on TRAVIS [53], is used on the planning. The algorithm works with every 0.05 second to check the collision of AGVs. Trajectory planning uses time windows to calculate the start-time for a safe crossing and safety margins. In addition, safety time is added in the calculation. However, safety is not guaranteed in case of disturbances. The result of simulation shows that free ranging algorithm get is safety, require less transport distance and less AGVs.
Storage and stacking logistics
6.3.
Storage strategy
The containers must be stored in a manner so as to minimize the amount of operations that are needed to place a container in the storage area and to remove it when needed. Therefore the problem being investigated is minimizing the total throughput time which is the handling time for all the containers from ships at berth and the transferring time of the containers to the storage area. It is useless optimizing either container transfer or container location isolated. Kozan and Preston [54] develop a cycle-fashioned model to determine the storage strategy and container handling schedule simultaneously. The model intergrade a container transfer model with a container location model to solve the problem.
Two iterative algorithms are applied to speed up the process. The first algorithm (non-increasing algorithm) has the same number of generations in each iteration while the second has the number of generations within each iteration increasing. The first iteration uses a random initial handling schedule, and there seems little point finding the best storage locations for this obviously sub-optimal schedule only for it to change dramatically after the first iteration. Rather this technique searches for smaller improvements that gradually increase in each iteration to save needless fine-tuning of solutions in early iterations. This procedure is shown in Figure 47 [54].
The reserved locations (File A), best transfer solution (File B) and all transfer solutions, i.e. chromosomes, (File C) are saved after iteration 0th. During the iterative procedure
CLM saves the best location solution (File D) and all location chromosomes (File E), and CTM saves best transfer solution (File B) and all transfer chromosomes. In the every iteration, CLM reads and uses files A, B (as the fixed transfer schedule) and E (to continue with the same chromosomes after iteration 1 and for subsequent iterations). Conversely CTM reads and uses Files A, D (as the fixed storage locations), and C; if using GA, (to continue with the same chromosomes for subsequent iterations) or B, if using TS, to continue with the same solution string for subsequent iterations [54].
Figure 47 Flow chart showing feedback for integrated iterative algorithm After simulations, it shows that [54]:
The iterative techniques generally provided better solutions than those found using the only individual models, and the solutions were much more stable with less variation in the results.
Overall the GA technique produced better results than the TS/GA hybrid and in most cases the non-increasing algorithm performed better than the increasing algorithm.
Reducing the maximum storage height resulted in a reduction in the turnaround time, although the non-increasing algorithm performed worse for two level storages.
CTM: container transfer model
CLM: container location model
GA: genetic algorithm
A polynomial reduction in average throughput time resulted when the number of yard machines increased.
Overall it is recommended the non-increasing GA algorithm (NIIS_GA) be used as it provided the best solutions for a wide range of infrastructure configurations.
Hong et al. [55] suggest two methods for determining the container location in a block stacking. One is a branch-and-bound (B&B) algorithm, the other is a decision rule is proposed by using an estimator for an expected number of additional relocations for a stack. The expected number of additional relocations (ENAR) is the expected number of relocations to be added, considering expected future relocations of blocks from the other stacks in the same bay to the empty spaces of the corresponding stack.
After a numerical experiment, the total number of relocations calculated by ENAR exceeded that found by the B&B algorithm by an average of approximately 7.3% for the case with precedence relationships among individual blocks and 4.7% for the case with precedence relationships among groups of blocks. However, the calculation time of ENAR is 2 seconds. The computational time of the B&B algorithm exceeded 100 seconds for the case with precedence relationships among individual blocks and 1000 seconds for the case with precedence relationships among groups—which exceed the levels that can be used in real time [55].
Automated stacking cranes collaborating
Figure 48 [56] depicts the system under study, which is composed of two collaborating non-passing ASCs, C1 and C2, who serve storage and retrieval requests from both the landside and seaside. C1 is the ASC closer to the seaside, while C2 is the one closer to the landside. The I/O points for the ASCs are in opposite ends of the block. Since the ASCs are unable to pass each other there is an exchange zone that serves as a temporary storage location so that one crane can start a request and leave it to the other crane to complete it. The ASCs are allowed to operate using a dual-command (dual-cycle) strategy. A minimum safety distance between the ASCs must be observed at all times [56].
Figure 48 Non-passing collaborating ASCs system
Hector et al. give a comparison of 12 different algorithms for nun-passing automated stacking cranes (ASCs). The following twelve priority rules (P1-P12) are proposed for handling interferences between the ASCs [56]:
P1. (PriC1): Crane 1 (C1) always has priority. This priority rule was considered in Carlo and Vis [57] to prioritize two non-passing lifts with a single I/O point. This priority could be advantageous if most of the requests are either associated with the seaside or assigned to C1.
P2. (PriC2): Crane 2 (C2) always has priority. This priority rule was also considered in [57]. This priority could be advantageous if most of the requests are associated with the landside or assigned to C2.
P3. (AdvFun): Favor the ASC whose respective function f(t) or g(t) has a higher index. This priority rule was designed to favor the crane closest to completing a request (in terms of the number of movements remaining).
P4. (ShoOri): Favor the ASC with the shortest travel time to the origin of the next request (upon completion of the current request). This priority rule seeks to minimize the empty travel time to the next request.
P5. (LonOri): Favor the ASC with the longest travel time to the origin of the next request (upon completion of the current request). This priority rule was designed recognizing that a long unproductive (i.e. empty) unavoidable move needs to be performed, which is less likely to re-interfere with the non-prioritized ASC.
P6. (ShoFin): Favor the ASC with the shortest time to finish the current request. The idea behind this priority rule is to minimize the wait time for the non-prioritized crane.
P7. (LonFin): Favor the ASC with the longest time to finish the current request. The idea behind this priority rule is to allow longer requests to be prioritized.
P8. (AbsDis): Favor the ASC with the shortest distance to the exchange zone. This priority rule seeks to favor the crane that is furthest away from its I/O point. Notice that in order for the ASCs to interfere one must be past the exchange zone.
P9. (TotReq): Favor the ASC to which most requests have been assigned. This priority rule is based on the premise that the more requests a crane has to serve, the most likely it is to be the bottleneck crane.
P10. (RemReq): Favor the ASC that has more requests left to serve. The spirit of this priority rule is to identify the bottleneck crane and give it priority.
P11. (LonTot): At the beginning of the problem, determine the total time each ASC needs to complete its requests (considering all assigned requests) without considering the other crane (i.e. no interference). Give priority to the crane that requires the most time to finish all the assigned requests. Similar to P9 and P10, this priority rule seeks to give priority to the bottleneck crane.
P12. (LonRem): Whenever there is interference between the ASCs, determine the time each ASC would need to complete the remaining requests without considering the other crane (i.e. no interference). This is equivalent to the Priority Longest rule in Carlo and Vis [57].
Figure 49 [56] presents the percent difference between the makespan for each priority rule and the best makespan found by any of the priority rules for our twelve experiments. The average, standard deviation, and corresponding rank (based on the average) of the percent differences are included at the bottom of Figure 49. Lastly, the percent of times the priority rule found the best makespan is presented in the row labeled %Best.
Figure 49 Experimental results of 12 algorithms
On average, ‘RemReq’ perform best while ‘LonOri’ and ‘LonTot’ have more possibility to get best solution (%Best is 58.33%). Since the priority rules run extremely fast, two different priority rules could be run. Then choose the one that yields the best makespan. In the case two priority rules can be used, priority rules ‘AdvFun’ and ‘LonRem‘ seems to complement each other the best. When these two priority rules are combined, the best found solution was obtained in 11 of the 12 instances (91.67%).
7. Conclusion and future research
Conclusion
7.1.
This survey decomposes the container terminal process into several sub processes to identify the automation technology used in automated container terminals. For each sub process, it illustrates the equipment with some key technologies of automation. Then some applications of these technologies are introduced as examples. Finally, control systems with a focus on particular processes or optimization are introduced. Nowadays, automated container terminals have fully developed. The use of automated technologies has played a big role of cost reduction and operational efficiency improvement. The main part of container handling process is performed fully automatically by control system that cooperating with sensors, when the operator only supervising the process remotely. With new application of technology (e.g. differential GPS system used in AGVs control), the performance of automated container terminal will become better in the future.
Recommendations and future research
7.2.
The objective of this survey is to provide an overview of containers handling process in automated container terminals, and how the equipment are automated by using specific technologies and control methods. However, narrowing the scope on sub processes by surveying individually with the specific environment could provide a more detailed result for recommendations (e.g. which automation technology should be chose in a specific case).
Future research could focus on the cooperation of logistics between container terminal and whole supply chain. For example, the automation of vessel berths and container handling with landside transport.
