Equipment In Container Terminals Research Articles

The influence of management functions on the productivity of yard cargo handling equipment in container terminals

PurposeThis empirical study explores the profound impact of management functions on the productivity of yard cargo handling equipment within container terminals.Design/methodology/approachBy closely examining crucial management aspects such as planning, organizing, leading, and controlling, a comprehensive managerial behavior framework was developed through focus group studies (FGS) and focal interviews. These qualitative methods were complemented by the distribution of questionnaires to practitioners in Vietnam. To validate the concept of management functions and analyze their influence on effective management practices for equipment efficiency, a structural equation model (SEM) technique was employed using partial least-squares estimation (PLS).FindingsThe findings of this study demonstrate that planning (PL), organizing (OR), and controlling (CT) significantly contribute to the productivity of yard cargo handling equipment, while leading (LD) does not exhibit a direct positive impact.Originality/valueTheoretically, this study contributes by providing clarity to the definition, purpose, and value of management functions in the field of cargo handling equipment management. Furthermore, these research findings offer valuable insights to terminal operators and managers, enabling them to optimize their management strategies and enhance productivity levels, ultimately resulting in improved operational outcomes.

Design and Implementation of a Digital Twin System for Monitoring Automated Container Terminal Equipment

Design and Implementation of a Digital Twin System for Monitoring Automated Container Terminal Equipment

Automated rail-water intermodal transport container terminal handling equipment cooperative scheduling based on bidirectional hybrid flow-shop scheduling problem

The importance of rail-water intermodal transport is becoming more and more prominent in recent years. As a key node of rail-water intermodal transportation, the operation efficiency of automated container terminal directly affects the overall transportation efficiency. However, there are few studies on the collaborative scheduling of automated container terminal equipment in rail-water intermodal transportation. Therefore, this paper focuses on the ‘Automated Quay Crane (AQC)-Automated Straddle Carrier (ASC)-Automated Rail Mounted Gantry Crane (ARMG)’ operation system and addresses the operational efficiency requirements of the Automated Rail-Water Intermodal Transport Container Terminal (ARWITCT), Based on the bidirectional Hybrid Flow-shop Scheduling Problem (HFSP), a scheduling optimization model for the ARWITCT is established with the objective of minimizing the maximum completion time. To solve this complex scheduling problem, Particle Swarm Optimization based on Adaptive Tent Chaos Mapping (PSO-ATCM) is designed. In this algorithm, a parameter adaptive adjustment strategy and a Tent Chaos Mapping Optimization Strategy are introduced to help PSO jump out of local optimum. Problem-feature-based encoding and decoding methods are designed for the problem. An ‘insertion-translation’ mechanism is used to judge and resolve the conflicts between import and export containers during the decoding process. The effect of proposed scheduling model and the performance of the proposed algorithm are validated via comprehensive comparison experiments. To validate the effectiveness of proposed scheduling model, we compare the unidirectional HFSP model with the bidirectional HFSP model. The proposed PSO-ATCM is compared with standard Genetic Algorithm, Particle Swarm Optimization algorithm and Adaptive Genetic Algorithm. Computational results demonstrate that the proposed model is effective and PSO-ATCM performs better than other three compared algorithms.

Deep reinforcement learning based optimization of automated guided vehicle time and energy consumption in a container terminal

The energy efficiency of port container terminal equipment and the reduction of CO2 emissions are among one of the biggest challenges facing every seaport in the world. The article presents the modeling of the container transportation process in a terminal from the quay crane to the stack using battery-powered Automated Guided Vehicle (AGV) to estimate the energy consumption parameters. An AGV speed control algorithm based on Deep Reinforcement Learning (DRL) is proposed to optimize the energy consumption of container transportation. The results obtained and compared with real transportation measurements showed that the proposed DRL-based approach dynamically changing the driving speed of the AGV reduces energy consumption by 4.6%. The obtained results of the research provide the prerequisites for further research in order to find optimal strategies for autonomous vehicle movement including context awareness and information sharing with other vehicles in the terminal.

Application of container terminal virtual reality in student education

The continuous emergence of digital technologies and the strong trend of digitization in numerous segments of human activity imposes the need to devote additional attention to better adaptation of the educational process. The special focus is on improving competencies of the new generation of employees through the modernization of educational methods. This article contributes to the wider debate of bigger involvement of virtual reality (VR) as modern pedagogical tool in student engineering education. VR as computer-generated environment allows its users better understanding of real or imaginary scenarios, processes and interaction like one in real conditions. Numerous research on the application of VR for educational purposes is devoted mainly to the detection of the final effects on the mental or physical performance of the examinee. However, insufficient attention is paid to the basic precondition for the successful application of VR technology in teaching, namely the way of its use and the credibility of the replicated content. Therefore, the article explains in more detail the process of creating realistic VR models for managing container terminal equipment designed using equipment technical data provided by Adriatic Gate Container Terminal in Rijeka, the strategically most important and largest seaport in the Republic of Croatia. In the end, potential directions of future research with the developed VR model among different interest groups and interviewees are listed.

Solving integrated problem of stowage planning with crane split by an improved genetic algorithm based on novel encoding mode

Stowage plan, which is planning for a reasonable movement of containers, plays an important role in enhancing the efficiency and competitiveness of container terminals. The time required for handling containerships also depends on the operations of quay cranes, which is one of the most expensive equipment in container terminals. Hence, this paper integrates stowage planning and crane split problem to minimize the total berthing time at each visiting port over the voyage. A new mathematical model is developed, which covers a wide range of operational and structural constraints for both stowage plan and crane operation. An improved genetic algorithm based on a novel encoding mode of assignment strategies, including container grouping and operation strategies, is designed to solve the problem, which also introduces penalty operations to solve the infeasible solutions. Finally, some computational experiments are carried out. Firstly, three small-sized experiments are implemented to verify the feasibility of the proposed model and algorithm. Secondly, large-sized experiments with 5 ports, 3385 containers, and 2 quay cranes show that the proposed approach can solve the integration problem with different productivity of quay cranes effectively and decrease the berthing time by 6.0%. Eventually, a comparison experiment with 5 ports, 5752 containers, and 2 quay cranes is conducted, and the results indicate that the proposed algorithm results in 62.3% and 87.7% decrease in the total number of rehandling times and computational time. Meanwhile, the results also show that the proposed algorithm can be convergent. So the proposed algorithm is effective and efficient in solving the integration problem and enhancing the efficiency of container terminals.

Truck-Lifting Prevention System Based on Vision Tracking for Container-Lifting Operation

Truck-lifting accidents are common in container-lifting operations. Previously, the operation sites are needed to arrange workers for observation and guidance. However, with the development of automated equipment in container terminals, an automated accident detection method is required to replace manual workers. Considering the development of vision detection and tracking algorithms, this study designed a vision-based truck-lifting prevention system. This system uses a camera to detect and track the movement of the truck wheel hub during the operation to determine whether the truck chassis is being lifted. The hardware device of this system is easy to install and has good versatility for most container-lifting equipment. The accident detection algorithm combines convolutional neural network detection, traditional image processing, and a multitarget tracking algorithm to calculate the displacement and posture information of the truck during the operation. The experiments show that the measurement accuracy of this system reaches 52 mm, and it can effectively distinguish the trajectories of different wheel hubs, meeting the requirements for detecting lifting accidents.

Energy efficiency and CO2 emissions of port container terminal equipment: Evidence from the Port of Valencia

Energy efficiency has emerged as a key point in port industry because of different factors such as the adoption of stronger environmental regulations and the increasing pressure of the local community on the surrounding ports. As gathering operational data from port terminals can be difficult due to privacy, studies on emissions and energy efficiency of these terminals are scarce. The following research provides key information about the real energy consumption and CO2 emissions of one of the most relevant container terminals in the Mediterranean area, located in Valencia, Spain. The results show that yard terminal tractors and rubber tyred gantry cranes (RTGs) are the main emission sources, accounting for 68.1% of the terminal's total CO2 emissions. After identifying the equipment responsible for the environmental problem, two solutions aimed at improving the energy efficiency of the terminal have been studied: the retrofitting of RTGs cranes and the replacement of terminal tractors powered by fuel for a new liquefied natural gas tractor, which contributed to a large reduction of CO2 emissions. Additionally, the present research explores the different policies at the disposal of port authorities in order to foster the implementation of solutions aimed at mitigating the environmental externalities by terminal operators.

Sensitivity Analysis for Ship-to-Shore Container Crane Design

Ship-to-shore (STS) container cranes are important pieces of equipment in container terminals for container handling, so they need to be properly designed to avoid damage or collapse due to natural hazards (i.e., storms or earthquakes). However, the dynamic analyses necessary for this can be cost- and time-consuming because of the need to consider the time history of ground motions and several sources of uncertainty. Thus, sensitivity analysis on the input parameters to the responses of the structures is needed to categorize which sources of uncertainty are significant enough to be considered as random variables. In this study, an investigation is carried out into the sensitivity of some sources of uncertainty to the seismic response of a Korean container crane structure. The input random variables studied include ground motion intensity, ground motion profiles, mass, damping, and elastic modulus of steel. Nonlinear dynamic analyses are conducted using a set of 20 natural ground motions scaled to three ground motion intensity levels, in compliance with the Korean Design Standard. The method of deterministic sensitivity analysis using the so-called tornado diagram is applied for the evaluation of structural systems. For the studied type of Korean container crane, it can be stated that the intensity of ground motions (i.e., spectral acceleration) is the most significant input parameter on the response of the structure, as measured in terms of portal drift, vertical reaction of the crane’s legs, and total base shear. The next most significant influencing factors are the mass of the structure and the characteristics of every ground motion. Damping plays a relatively important role on the total base shear, while it shows almost no impact on the axial reaction of the crane’s legs. Of the three engineering design parameters (portal drift, vertical reaction, and total base shear), the elastic modulus exhibits a low effect, but it should be considered a source of uncertainty in seismic analysis.

Life cycle assessment of Quayside Crane: A case study in China

China is an important Quayside Crane producer and exporter in the world. The Quayside Crane has been used as crucial equipment in container terminals and also in supporting towards the global trade momentum. However, it simultaneously impacts the environment negatively on air quality and in addition contributes adversely towards energy consumption. To reduce the deleterious environmental effects of the Quayside Crane so as to improve the sustainability of this industry, evaluation of its environmental impacts through life cycles is acute necessary. This research undertook a cradle-to-grave life cycle assessment for a Quayside Crane made in China. Its purpose was to identify the key processes that effected the environment, as well as, sought out opportunities for improving the environmental profiles of Quayside Cranes. The inventory data was obtained from on-site investigations of Quayside Crane producers in Shanghai, China. The environmental impacts were evaluated using the ReCiPe method at midpoint level and operating the GaBi 6.0 assessment software. The results showed that nearly all environmental impact categories and life cycle costs were relatively high in the utilization stage. Steel production stage was the most important driver to the categories that impact environmental degradation, such as freshwater ecotoxicity, metal depletion, freshwater eutrophication and ozone depletion. Accordingly recovery of materials, such as steel reuse after refurbishment in the end-of-life stage could notably diminish most of the environmental impacts. In addition, sensitivity analysis and economic analysis were employed to promote the reliability of the life cycle assessment results. Based on these findings, several improvements could be put forward, for instance, optimized design for motor efficiency of the Quayside Crane was recognized as the most effective way to reduce the environmental impacts which should be urgently amended. The life cycle assessment could help decision-makers to know the key points that should be streamlined to make the Quayside Crane more reliable, energy-efficient, technologically and environmentally sustainable.

Univariate Throughput Forecasting Models on Container Terminal Equipment Planning

Planning of Container Terminal equipment has always been uncertain due to seasonal and fluctuating throughput demand, along with factors of delay in operation, breakdown and maintenance. Many time-series models have been developed to forecast the unforeseen future of container throughput to project the needed amount of port equipments for optimum operation. Conventionally, a "ratio" method developed by port consultants at early port design stage is adopted for equipment planning, giving no consideration to the dynamic growth of the port in terms of improved layout and technological advancement in equipments. This study seeks first to enhance the empirical approach of the equipment planning at the end of planning time horizon by including assumed coefficient of port capacity parameters. The second is to compare the size of equipment purchase by receiving different terminal's future throughput demand from two univariate forecasting models at planning time horizon. The empirical method of equipment planning will be tested against the conventional yard equipment per quay crane ratio after deriving the throughput demand from forecasting models of Holt-Winter's exponential smoothing and seasonal ARIMA (autoregression integrated moving average) model. Results in the form of graphs and tables indicate similar forecasting pattern by two models and equipment estimation proofs to avail more redundancy for optimum operation. Suggestions for better estimation of equipments are also made for future models.

Impacts of electric rubber-tired gantries on green port performance

Motivated by the need to reduce operating costs and alleviate noise and exhaust pollution generated by cargo handling equipment in container terminals and container yards, this study compares the performance of rubber tired gantries (RTGs) and electric rubber tired gantries (E-RTGs) from the perspective of energy savings and CO2 reduction, and analyzes the impact of E-RTG use on the green port policies of international hub ports.This study discovered that (1) E-RTG cranes offer a significant performance improvement compared with RTGs, and can achieve 86.60% energy savings and a 67.79% reduction in CO2 emissions. (2) ERTG cranes are expected to have an individual payback period of 2.2years, and are not only friendly to the environment, but also ease the impact of diesel oil price hikes. (3) Government may formulate appropriate regulations or provide incentive measures to encourage terminal operators to upgrade their handling equipment or implement E-RTG conversion projects.

New Conceptual Handling Systems in Container Terminals

This paper introduces some of the developments related to the handling equipment in container terminals and various new conceptual handling systems that have been proposed during the last several decades. The basic ideas behind the previous equipment improvements are analyzed to identify future directions that can be used for devising new handling systems. The handling systems in the container terminals include a quayside handling system, transport system, and yard system. In response to the deployment of mega-sized vessels for container transportation systems, productivity improvement has become one of the most urgent issues in the container terminals. This paper analyzes the previous improvements made for achieving higher productivity in the three subsystems of container handling. Some conceptual handling systems are introduced including the linear motor conveyance system (LMCS), automated storage and retrieval systems (AR/RS), overhead grid rail (GRAIL), SPEEDPORT, SuperDock, the automated container system by ZPMC (ACS-ZPMC), and AUTOCON.

듀얼 트롤리형 컨테이너 크레인 버퍼공간 분석을 위한 시뮬레이션 연구

컨테이너 크레인은 컨테이너터미널에서 사용되는 주요 장비면서 컨테이너 크레인의 효율은 컨테이너터미널의 생산성을 결정한다. 컨테이너 크레인의 전형적인 유형은 싱글 트롤리를 가지고 있으며 진보된 유형들 중의 하나가 듀얼 트롤리형이다. 본 논문의 목적은 컨테이너 터미널에서 듀얼 트를리형 컨테이너 크레인의 버퍼 사이즈를 분석하는 것이다. 듀얼 트롤리형 컨테이너 크레인의 버퍼 공간을 분석하기 위한 시뮬레이션 모델을 소개한다. 버퍼 공간은 해측의 메인 트롤리와 야드측의 세컨 트롤리 사이에 위치한다. 요구 생산성을 추정하기 위해 다양한 시뮬레이션 실험을 수행하여 버퍼 사이즈를 분석한다. Container crane is main equipment in container terminals and it determines the productivity and the efficiency of container terminals. The typical type of container cranes has the single trolley and one among advanced types of them has the dual trolley. The objective of this paper is to analyze the buffer size of a container crane with the dual trolley in container terminals. We present a simulation model for analysing the buffer space of a container crane with the dual trolley. The buffer space is located between main trolley in sea-side and second trolley in yard-side. We performs various simulation experiments and analyze the buffer size to estimate the required productivity.