Search Results (62)

Container terminals are facing significant challenges in meeting the increasing demands for volume and throughput, with limited space often presenting as a critical constraint. Key areas of concern at the quayside include the berth allocation problem, the quay crane assignment, and the scheduling problem. Effectively managing these issues is essential for optimizing port operations; failure to do so can lead to substantial operational and economic ramifications, ultimately affecting competitiveness within the global shipping industry. Optimization models, encompassing both mathematical frameworks and metaheuristic approaches, offer promising solutions. Additionally, the application of machine learning and reinforcement learning enables real-time solutions, while robust optimization and stochastic models present effective strategies, particularly in scenarios involving uncertainties. This study expands upon earlier foundational analyses of berth allocation, quay crane assignment, and scheduling issues, which have laid the groundwork for port optimization. Recent developments in uncertainty management, automation, real-time decision-making approaches, and environmentally sustainable objectives have prompted this review of the literature from 2015 to 2024, exploring emerging challenges and opportunities in container terminal operations. Recent research has increasingly shifted toward integrated approaches and the utilization of continuous berthing for better wharf utilization. Additionally, emerging trends, such as sustainability and green infrastructure in port operations, and policy trade-offs are gaining traction. In this review, we critically analyze and discuss various aspects, including spatial and temporal attributes, crane handling, sustainability, model formulation, policy trade-offs, solution approaches, and model performance evaluation, drawing on a review of 94 papers published between 2015 and 2024. Full article

To address distributed mass payload (DMP) anti-swing control problems typified by offshore wind turbine blades, this paper adopts multi-body dynamics and rigid-flexible coupling modelling approaches. It derives the geometric constraints and static equilibrium equations for marine crane multipoint lifting of DMP, and establishes a dynamic coupling model considering ship roll and pitch environmental excitations. Then, under the maximum environmental excitation set in the experiment, the flexible cable parallel anti-swing system achieves swing suppression rates of 41.0% and 58.0% for the in-plane and out-of-plane angles of the DMP with regular geometric shape and mass distribution, respectively. For the DMP with irregular geometry and mass distribution, the suppression rates are 48.4% and 39.3% for the in-plane and out-of-plane angles, respectively. It is found that, after adjusting the lifting method and increasing the distance between the lifting points, the maximum in-plane angle of the payload decreases by 2.3%, while the out-of-plane angle maximum decreases by 52.0%. These results demonstrate the effectiveness of adjusting lifting methods in suppressing swing for irregular DMPs, thereby verifying the reliability and applicability of the flexible cable parallel anti-swing system and providing a reference for improving anti-swing performance and lifting efficiency in offshore DMP operations. Full article

This study presents an automated docking block placement system developed for regular and emergency repairs of large ships and naval vessels. Traditional methods involve manually arranging heavy concrete docking blocks using cranes or forklifts, which can take several days and pose significant safety risks because of the heavy materials involved. The proposed system integrates an unmanned crane with a six-degree-of-freedom (6-DOF) robotic platform and a mobile robot-based 3D precision positioning system to automate block relocation. The use of a 3D laser tracker mounted on the mobile robot is the key to the system, which, when combined with environmental sensors such as LiDAR and RTK-GPS, provides millimeter-level positional feedback. To address the lack of clear reference points in conventional docking blocks, a precisely machined aluminum target block was attached to each block. An algorithm employing Density-Based Spatial Clustering of Applications with Noise (DBSCAN), KD-Tree, and Random Sample Consensus (RANSAC) techniques was used to detect and classify the vertex of the target block from the 3D point cloud data. The experimental results demonstrated a positional measurement error within 0.5 mm at an 8 m distance. This novel system reduces the setup time, enhances worker safety, and increases the overall efficiency and capacity of dry dock maintenance operations. Full article

Offshore cranes are widely used in important fields such as wind power construction and ship replenishment. However, large payloads such as wind turbine blades are hoisted by multiple steel wire ropes, which makes it difficult to directly control their movements; that is, the number of input degrees of freedom is less than that of the output degrees of freedom. In addition, compared with land cranes, offshore cranes are inevitably affected by waves, wind, etc. The transition from a fixed base to a dynamic base brings severe challenges to their oscillation suppression and precise positioning. At the same time, to improve operational efficiency, the hoisting operation of offshore cranes usually adopts velocity input control patterns that fit the habits of manual operation, and most of them are in the form of dual-axis linkage for pitch and hoisting. Therefore, this paper proposes a fast terminal sliding mode control method for double-pendulum offshore cranes with distributed-mass payloads (DMPs). First, a nonlinear dynamic model of offshore cranes considering DMPs is established, and a dynamic model based on acceleration input control patterns is acquired. Based on this, considering the variation in hoisting rope lengths, a novel adaptive control method is proposed. Finally, simulation results verify the effectiveness of the proposed method, and the robustness of the proposed method to DMP mass parameter uncertainty and disturbances is demonstrated. Full article

The high-pile beam slab structure is a commonly employed design for riverbank wharves; however, the wharf structure may incur damage due to various factors during long-term operation, resulting in potential safety concerns. To illustrate this, an investigation was conducted on a high-pile beam slab wharf, which included on-site examination, testing, and large-scale three-dimensional numerical simulation. The effects of gravity, ship impact, earthquake, lateral impact, water, and crane change were considered to explore the causes of cracking in the wharf concrete components. The results indicated that crane modification significantly augmented loads, precipitating notable deformation (92% increase in maximum vertical displacement), and the maximum tensile stress exceeded concrete tensile strength. The inadequate thickness of the steel reinforcement protective layer caused concrete carbonation, steel exposure, and corrosion, reducing structural capacity. The presence of defects in the pile foundation has been shown to result in high stress concentrations, which can lead to deformation and damage. There was a 58% increase in vertical displacement in the concrete components above the affected area compared to intact piles. Based on analysis of the results, appropriate measures for strengthening and correction have been proposed to ensure the safety and durability of the wharf. A comprehensive multifactor evaluation and 3D simulation of the actual dimensions are recommended to ensure the safety of wharf structures. Full article

Loading operations are a crucial part of container terminal activities and play a key role in influencing shoreline operation efficiency. To overcome the challenge of mismatched local ship decisions and global yard decisions during single-vessel operations, which often result in conflicts related to container retrieval in the yard, a novel intelligent decision-making model for stack-yard positioning in full shoreline loading operations is proposed. This model seeks to optimize the balance between yard operation instructions and quay crane operation instructions. An enhanced Constrained Optimization Genetic Algorithms-Greedy Randomized Adaptive Search (COGA-GRASP) algorithm is introduced to tackle this decision-making issue, and it is applied to identify the most optimal bay configuration for full shoreline loading operations. The proposed model’s effectiveness is validated through testing and solution outcomes. Full article

The operation process of double-pendulum ship-borne cranes with variable rope lengths is frequently complex, with numerous unpredictable circumstances, such as the swing of the load and external environmental interferences, which undoubtedly make the analysis of the swing characteristics of the system and the controller design more difficult. On this basis, an active disturbance rejection controller based on an energy coupling method is proposed to inhibit the double-pendulum swing angle. The controller can suppress the swing of the hook and load within 0.5 degrees under the conditions of continuous sea wave disturbances and external disturbances. Firstly, the energy function of the system is constructed by analyzing the dynamic model of the system. Then, an adaptive control method is designed by analyzing the energy function of the system. In addition, an overshoot limit term and an anti-swing term are added to limit the overshoot and swing of underactuated parts of the system. Then, the stability of the closed-loop system is strictly proven by using Lyapunov analysis. Finally, the simulation and experimental results indicate that the proposed controller ensures the accurate positioning of the jib and rope length without overshoot. Additionally, it effectively reduces the double-pendulum swing angle when there is an external interference such as waves, demonstrating strong robustness. Full article

The International Maritime Organization (IMO) aims for net zero emissions in shipping by 2050. Ports, key links in the supply chain, are embracing green innovation, focusing on efficient berth and quay crane scheduling to support green port development amid limited resources. Additionally, the energy consumption and carbon emissions from the port shipping industry contribute significantly to environmental challenges and the sustainable development of ports. Therefore, reducing carbon emissions, particularly those generated during vessel berthing, has become a pressing task for the industry. The increasing complexity of berth allocation now requires compliance to vessel service standards while controlling carbon emissions. This study presents an integrated model that incorporates tidal factors into the joint optimization of berth and quay crane operations, addressing both service standards and emissions during port stays and crane activities, and further designs a PSO-GA hybrid algorithm, combining particle swarm optimization (PSO) with crossover and mutation operators from a genetic algorithm (GA), to enhance optimization accuracy and efficiency. Numerical experiments using actual data from a container terminal demonstrate the effectiveness and superiority of the PSO-GA algorithm compared to the traditional GA and PSO. The results show a reduction in total operational costs by 24.1% and carbon emissions by 15.3%, highlighting significant potential savings and environmental benefits for port operators. Furthermore, the findings reveal the critical role of tidal factors in improving berth and quay crane scheduling. The results provide decision-making support for the efficient operation and carbon emission control of green ports. Full article

Considering the anti-swing control and output constraint problems of shipboard cranes, a nonlinear anti-swing controller based on asymmetric barrier Lyapunov functions (BLFs) is designed. First, model transformation mitigates the explicit effects of ship roll on the desired position and payload fluctuations. Then, a newly constructed BLF is introduced into the energy-based Lyapunov candidate function to generate nonlinear displacement and angle constraint terms to control the rope length and boom luffing angle. Among these, constraints with positive bounds are effectively handled by the proposed BLF. For the swing constraints of the unactuated payload, a carefully designed relevant constraint term is embedded in the controller by constructing an auxiliary signal, and strict theoretical analysis is provided by using a reductio ad absurdum argument. Additionally, the auxiliary signal effectively couples the boom and payload motions, thereby improving swing suppression performance. Finally, the asymptotic stability is proven using LaSalle’s invariance principle. The simulation comparison results indicate that the proposed method exhibits satisfactory performance in swing suppression control and output constraints. In all simulation cases, the payload swing angle complies with the 3° constraint and converges to the desired range within 6 s. This study provides an effective solution to the control challenges of shipboard crane systems operating in confined spaces, offering significant practical value and applicability. Full article

To investigate the influencing factors on the operation of an offshore wind turbine installation ship, a neural network, as a machine-learning method, is built to predict and analyze the motion response of a floating derrick in the process of a lifting operation under an external environmental load. The numerical method for the double floating body, from the software SESAM/SIMA, is validated against the experiments. The numerical method is used to establish the floating derrick-lifting impeller model to obtain the motions of the ship and impeller and the coupling effect. Based on the numerical results, the BP neural network model is built to predict the ship’s operation. The results show that the BP neural network model for the floating derrick and impeller motion prediction is very feasible. Combined with the Rules for Lifting Appliances of Ships and Offshore Installations and the Noble Denton Guidelines for Marine Lifting Operations, the operation of the floating crane system can be determined based on the environmental parameters. Full article

The maintenance of the surface of steel structures is crucial for ensuring the quality of shipbuilding cranes. Various types of wall-climbing robots have been proposed for inspecting diverse structures, including ships and offshore installations. Given that these robots often operate in outdoor environments, their performance is significantly influenced by wind conditions. Consequently, understanding the impact of wind loads on these robots is essential for developing structurally sound designs. In this study, SolidWorks software was utilized to model both the wall-climbing robot and crane, while numerical simulations were conducted to investigate the aerodynamic performance of the magnetic wall-climbing inspection robot under wind load. Subsequently, a MATLAB program was developed to simulate both the time history and spectrum of wind speed affecting the wall-climbing inspection robot. The resulting wind speed time-history curve was analyzed using a time-history analysis method to simulate wind pressure effects. Finally, modal analysis was performed to determine the natural frequency and vibration modes of the frame in order to ensure dynamic stability for the robot. The analysis revealed that wind pressure predominantly concentrates on the front section of the vehicle body, with significant eddy currents observed on its windward side, leeward side, and top surface. Following optimization efforts on the robot’s structure resulted in a reduction in vortex formation; consequently, compared to pre-optimization conditions during pulsating wind simulations, there was a 99.19% decrease in induced vibration displacement within the optimized inspection robot body. Modal analysis indicated substantial differences between the first six non-rigid natural frequencies of this vehicle body and those associated with its servo motor frequencies—indicating no risk of resonance occurring. This study employs finite element analysis techniques to assess stability under varying wind loads while verifying structural safety for this wall-climbing inspection robot. Full article

This paper presents a study on the modelling and estimation of stress concentration at the tips of leg stiffeners in ship-to-shore (STS) quay cranes, which is intensified in those on the sea-side leg extensions, which are more prone to crack formation, notably following structural heightening of the cranes. A computer-simulated database was generated, incorporating mechanical parameters and geometric features that impact stress concentration. These variables can then be integrated as inputs into a multiple linear regression model (MLR). This methodology offers an alternative to the finite element method (FEM) for the computation of stress concentration and deformations. At the same time, the statistical significance of the parameters influencing this scenario is determined, ensuring a comprehensive assessment of their impact on the studied phenomenon. The research underscores the importance of incorporating stress concentration and structural geometry considerations into crane design or modification, given their crucial role in preserving the remaining lifecycle of the structure. Crack initiation is significantly intensified in regions characterised by high stress concentrations, particularly in areas where there are geometric changes at the tips of the stiffeners, where local stiffness is altered. All of this is in combination with work cycles under the supported loads. Full article

Quay cranes (QCs) play a vital role in automated container terminals (ACTs), and once a QC malfunctions, it will seriously affect the operation efficiency of ships being loaded and unloaded by the QC. In this study, we investigate an integrated scheduling problem of quay cranes (QCs), yard cranes (YCs), and automated guided vehicles (AGVs) under QC faults, which is aimed at minimizing the loading and unloading time by determining the range of adjacent operational QCs of the faulty QCs and reallocating unfinished container handling tasks of QCs. A mixed integer programming model is formulated to dispatch QCs, YCs, and AGVs in ACTs. To solve the model, an adaptive two-stage NSGA-II algorithm is proposed. Numerical experiments show that the proposed algorithm can significantly reduce the impact of faulty QCs on productivity while maintaining its synchronous loading and unloading efficiency. The sensitivity analysis of ship scale, location, and number of faulty QCs indicates that the number of faulty QCs has a greater influence on the loading and unloading efficiency than their locations, and the impact of faulty QCs on the efficiency of small-scale ships is greater than that of large-scale ships. Full article

The use of wireless technology in common marine engineering applications as a medium for data transaction in measurement and control systems, is not as popular as it should be. This article aims to demonstrate the advantages of using wireless technology in maritime engineering applications through a proposed Wi-Fi based wireless system dedicated to performance and safety monitoring in marine cargo cranes. The system is based on some concepts that were suggested in the earlier literature to perform authenticated data transmission from multiple sensors through using both the ESP-NOW protocol and the WebSerial remote serial monitor. The introduced system will be integrated with an already installed system in order to render the means for implementing effective principles in automation and control engineering, such as functional safety and predictive maintenance. Additionally, this article will highlight the economic efficiency of adopting wireless technology instead of cabling as a medium for data transaction in measurement and control systems in marine engineering applications such as cargo cranes. Full article

The aim of this research is to devise a continuous simulation model for predicting ship crane failures to increase their reliability and reduce unplanned downtime during cargo loading and unloading operations. To predict the condition of the hydraulic system, a database from the GALIOT software package was used for carrying out maintenance on cranes at m/v “O” over a period of 120,000 working hours. In the research, fault tree analysis (FTA) was used to identify causal relationships between system failures and basic events, while the Markov mathematical model was used to model the system state and predict transitions between different failure states. A system dynamics simulation model was developed to simulate the behavior of a system using POWERSIM PowerSim Constructor 2.5.d (4002), and regression analysis was performed to analyze the simulation results and understand the relationships between dependent and independent variables. The results show that a model for predicting failures in the hydraulic motors and pumps of ship cranes was developed, and the Markov model makes it possible to estimate the frequency of transitions between states under the condition that the sum of reliability equals one. The simulation model shows high reliability of the cranes and a constant frequency of failures throughout the 120,000 operating hours, while the regression analysis confirms the validity of the simulation model and shows a strong correlation between the analyzed variables. These models are used to improve the planning of ship crane maintenance, reduce unplanned downtime, and predict and promptly detect failures, which overall minimizes maintenance costs and failures. Full article