Ship Operation Research Articles

THE RELIABILITY EVALUATION OF THE DECK MACHINERY AND GALLEY EQUIPMENT OF A BULK CARRIER BY UTILIZING THE FAILURE RECORDS

Among various modes of transportation, maritime transportation holds critical importance since it provides substantial carrying capacity with low unit costs. To perform seamless and efficient operations in maritime transportation plays a pivotal role in achieving sustainable development goals and the International Maritime Organization (IMO) targets. The execution of uninterrupted operations can only be carried out with the existence of reliable systems. Creating reliable systems onboard is possible through the implementation of planned and proactive maintenance strategies and leveraging experiences gained from past failures. 10-year failure records of bulk carriers have been scrutinized within the scope of system reliability to determine critical equipment and units. The data has been categorized into subgroups under four fundamental headings, and subsequent reliability analyses have been conducted on each subgroup. Within the subgroups, the reliability of navigation equipment should be improved since it has the highest failure rate and its malfunction can cause very serious marine accidents. This equipment is followed by fire-fighting systems, cargo equipment, and GMDSS instruments which are essential for ship operations based on reliability results. Therefore, regular failure records, planned and proactive maintenance strategies, and also extra efforts should be performed on this equipment to ensure sustainable and seamless operations in the maritime sector.

Research on Big Data Intelligent System for Fault Diagnosis of Computer Aided Ship Power System

This paper aims to build a new fault diagnosis system based on big data and artificial intelligence technology. This study first expounds the application value and prospect of big data technology and intelligent algorithm in the fault diagnosis of ship power system, and realizes the effective integration and mining of massive, multi-source and heterogeneous ship power system operation data through in-depth analysis of the characteristics of ship power system operation data. Secondly, in view of the nonlinear and time-varying characteristics of ship power system faults, this study designs and implements a fault diagnosis model that integrates intelligent algorithms such as machine learning and deep learning. The model can automatically extract key fault features, realize early warning and accurate identification of potential faults, and improve the accuracy and response speed of fault diagnosis through continuous learning and optimization. Finally, this study applies the big data intelligent system for fault diagnosis of computer-aided ship power system to a practical case to verify its effectiveness and practicability in improving fault diagnosis efficiency, reducing maintenance costs, and ensuring navigation safety. The research results have important theoretical significance and practical value for improving the level of ship operation and maintenance management and ensuring the stable operation of ship power system.

Risk Analysis of Pirate Attacks on Southeast Asian Ships Based on Bayesian Networks

As a bridge for international trade, maritime transportation security is crucial to the global economy. Southeast Asian waters have become a high-incidence area of global piracy attacks due to geographic location and complex security situations, posing a great threat to the development of the Maritime Silk Road. In this study, the factors affecting the risk of pirate attacks are analyzed in depth by using the Global Ship Piracy Attacks Report from the IMO Global Integrated Shipping Information System (GISIS) database (i.e., 2013–2022) in conjunction with a Bayesian Network (BN) model, and the Expectation Maximization algorithm is used to train the model parameters. The results show that piracy behaviors and the ship’s risk are the key factors affecting the risk of pirate attacks, and suggestions are made to reduce the risk of pirate attacks. This study develops a theoretical basis for preventing and controlling the risk of pirate attacks on ships, which helps maintain the safety of ship operations.

Feasibility of the Northern Sea Route: Impact of Sea Ice Thickness Uncertainty on Navigation

With the accelerated melting of the Arctic sea ice, the opening of the Northern Sea Route (NSR) of the Arctic is becoming increasingly accessible. The purpose of this paper was to examine the impact of uncertainty in sea ice thickness (SIT) data on the opening of the NSR and to quantify the extent of this impact, which is essential to the regularized operation of polar shipping. A quantitative assessment framework was proposed to examine the influence of SIT data uncertainty on navigational uncertainty through three aspects: the navigational spatiotemporal windows, the distribution of safe sailing speeds, and the uncertainty in optimal route planning by employing four distinct SIT datasets. Furthermore, the sensitivity of navigational spatiotemporal windows, the distribution of safe sailing speeds, and route planning to variations in SIT were also evaluated. Results show that experiment results based on CS2SMOS exhibit a more aggressive profile, while results based on CPOM are more conservative. The difference in SIT data has a significant impact on the proportion of operations subject to special consideration areas, such as safety speed, sailing time, and distance in NEP. A 0.1 m discrepancy in sea ice thickness data results in an approximate 0.067 change in the proportion of operations within special consideration areas. This discrepancy also leads to an approximate speed change of 0.89 knots, a navigation duration change of approximately 4 days, and a distance change of 152 km within specified limits.

RESHAPING CURRICULUM OF INDONESIAN MARITIME EDUCATION AND TRAINING

Maritime education and training are pivotal for the development and operation of autonomous ships and green port era, encompassing areas such as safety, economic advantages, legal frameworks, cybersecurity, and operational efficiency. The author aims to develop robust and resilience curriculum for future generation which is a combination of well developed STCW (Standard of Training & Certification of Watchkeeping) and Indonesia Educational Standards through literature review and applying a well-designed guidance from the Indonesian Ministry of Education. The research contribution lies in the development of an integrated curriculum that aligns international maritime standards with national educational requirements, using a systematic approach informed by literature and official educational guidance. The data then compared with some MET's curriculum and the results are proven to be aligned with every limitation set up by International Standards and Indonesian National Education Standards.

Data-driven model for anti-pitching control of wave-piercing trimaran with stern-flap interceptor in waves

The control of pitching in wave-piercing trimarans helps improve crew comfort and navigation stability, providing a strong guarantee of safe and efficient ship operation. Current research on anti-pitching has mostly focused on control algorithms that use empirical formulas to calculate the stabilising moments directly. Little research has been conducted on appendage modelling. The Reynolds-averaged Navier–Stokes (RANS) method was employed to conduct a series of numerical simulations of waves on a trimaran equipped with a stern-flap interceptor with variable angles of attack. An optimal feature combination was designed by considering the spatial and temporal characteristics, such as the interaction between the stern-flap interceptor and hull, and the memory effect of the flow field. Based on long short-term memory (LSTM), a data-driven model of the stern-flap interceptor oriented towards anti-pitching control was constructed. In addition, the anti-pitching and drag-reduction mechanisms of the stern-flap interceptor were explored. The proposed model, which is oriented towards anti-pitching, establishes the relationship between the angle of attack of the appendage, the ship's attitude, and the stabilising moment applied to the hull. Experiments verified the accuracy and generalisation of the model. This study provides a theoretical basis for designing and developing an anti-pitching control system for wave-piercing trimarans.

In-depth characterization of exhaust particles performed on-board a modern cruise ship applying a scrubber

To comply with environmental regulations, ship operators may adopt exhaust after-treatment devices such as scrubbers or selective catalytic reduction (SCR). Beyond gaseous emission control, these technologies impact the exhaust particles emitted from marine engines to the atmosphere. This study characterizes comprehensively the chemical composition and physical properties of exhaust aerosol particles upstream and downstream a hybrid scrubber operating in open loop mode on-board a modern cruise ship. The study considers two engines, one equipped with SCR and both with scrubber, during engine load conditions of 75 % and 40 %, and the influence of marine gas oil (MGO) use in addition to heavy fuel oil (HFO). At least 4 different particle types were observed in the exhaust based on transmission electron microscopy (TEM) studies both upstream and downstream scrubber, and both scrubber and SCR affected the particle number size distribution (PSD). The geometric mean diameter (GMD) of the particles increased over scrubber both due to removal of nucleation mode particles and particle growth in the scrubber. The scrubber effectively decreased particle number (PN) and, also, non-volatile particles, but the effect depended on particle size and no significant decrease was observed in number of particles above 50 nm, typically comprising black carbon (BC) and in the case of HFO combustion, also asymmetrical metal containing particles. In addition to PN, concentrations of PAH compounds were reduced in the scrubber. The results may be further utilized when including the exhaust aerosol characteristics from ships applying scrubbers to emission inventories, as well as climate and air quality models.

2G1-3 Study on the required skill for remote ship operators

2G1-3 Study on the required skill for remote ship operators

Alignment Prediction of Air Spring Vibration Isolation System for Marine Shafting Based on Genetic Algorithm-Back Propagation Neural Network.

Shafting alignment plays an important role in the marine propulsion system, which affects the safety and stability of ship operation. Air spring vibration isolation systems (ASVISs) for marine shafting can not only reduce mechanical noise but also help control alignment state by actively adjusting air spring pressures. Alignment prediction is the first and a key step in the alignment control of ASVISs. However, in large-scale ASVISs, due to factors such as strong interference and raft deformation, alignment prediction faces problems such as alignment measurement sensors failure and difficulty in establishing a mathematical model. To address this problem, a data model for predicting alignment state is developed based on a back propagation (BP) neural network, fully taking advantage of its self-learning and self-adaption abilities. The proposed model exploits the collected data in the ASVIS instead of the alignment measurement data to calculate the alignment state, providing another alignment prediction approach. Then, in order to solve the local optimum issue of BP neural network, we introduce the genetic algorithm (GA) to optimize the weights and thresholds of the BP neural network, and an improved GA-BP model is designed. The GA-BP model can leverage the advantages of the global search capability of GA as well as the BP neural network's fast convergence in local search. Finally, we conduct experiments on a real ASVIS and evaluate the prediction models using different criteria. The experimental results show that the proposed prediction model with the GA-BP neural network can accurately predict the alignment state, with a mean-square error (MSE) of 0.0114. And compared to the BP neural network, the GA-BP neural network reduces the MSE by approximately 74%.

Features of planning and evaluation of the work of small shipping vessels enterprises at the present stage

The article considers one of the possible approaches to planning and evaluating the fleet operation of small shipping enterprises at the present stage. The existing algorithms for mathematical modeling of fleet operations are universal and can be used for enterprises with a small number of vessels, but at the same time they are complex, costly and therefore inefficient, and therefore unclaimed. In this regard, the article state the problem of developing a system for operational planning and evaluation of the fleet of small shipping enterprises in the context of modern economics and trends in the use of information technology, defines the objectives of the development and implementation of the system, its configuration; reveals the purpose and methods of implementing the components of the system. The methods necessary for the development of the system and also to be developed are called. The importance of substantiating the effectiveness of informatization is emphasized.

Markov Chain Analysis of Ship Energy Efficiency

A formulation is presented for the assessment of the CO2 generated by ships in operation and their evolution with time, conditional on the current legislation using Markov chains. Any potential deep repair or retrofitting of the ship propulsion system or enhancement of route operational characteristics during the service life are not accounted for. The Markov transition matrix is defined based on the ship operations and CO2 history of A, B, C, D, and E carbon intensity indicator (CII) rates. The transition between different CII rate states in the survey data is used to estimate the probability of transition of the analysed ships between different CII grates. Distinct transition matrices employing the progressively tightened legislation of CII are employed and analysed. In addition, the transition matrices can be fed into risk-based models that take the CII rates as input for defining the most appropriate ship energy efficiency management plan.

A framework of a data-driven model for ship performance

An accurate assessment of a ship's required power is increasingly relevant for ship operations. We used a simplified framework of a data-driven model to predict ship's fuel consumption. Our approach was based on the learning capabilities of a generalized AutoML (Automated Machine Learning) process, trained with a variety of databases obtained from Computational-Fluid-Dynamics (CFD) simulations or from simplified numerical methods. These CFD simulations were conducted by solving the Reynolds Averaged Navier-Stokes (RANS) equations, using the STARCCM + commercial CFD software to calculate the ship resistance at speed under different operating conditions. Initially, we conducted a statistical analysis to select the independent variables before fitting the regression models and identifying potentially wrong assumptions. The AutoML process allowed optimizing the model's hyperparameters and designing the topology of the neural networks. For a set of unknown scenarios, comparative predictions obtained from the data-driven model and from numerical simulations showed that the data-driven model, trained with results obtained from CFD simulations, accurately and efficiently predicted ship operational parameters under realistic operating conditions, thereby dispensing with the need to perform elaborate CFD computations. Specifically, this low-cost and efficient operational data-driven technique forecasted the ship's operational fuel consumption although only a limited amount of recorded operational data was available.

A Multi-Attribute Decision-Making Approach for International Shipping Operator Selection Based on Single-Valued Neutrosophic Power Hamy Mean Operators

A Multi-Attribute Decision-Making Approach for International Shipping Operator Selection Based on Single-Valued Neutrosophic Power Hamy Mean Operators

Implementasi Pendidikan Karakter dalam Pembentukan Taruna Pelayaran

Character education has its own uniqueness when applied in the context of shipping cadet education. Sailing cadets are those who are undergoing education to become reliable sailors or sailors. In this profession, it requires not only technical expertise in navigation and ship operations, but also a strong character to face challenges in an often harsh and dangerous maritime environment. Qualitative method with case study is a suitable research approach to investigate the implementation of character education in the formation of shipping cadets. Through this method, research will be conducted in depth to understand how character education is integrated in curriculum and daily practice in specific shipping schools. In this context, research shows that there is a need to strengthen the integration of character education in the cruise education curriculum to ensure that character values and principles are not only taught separately, but also integrated in every aspect of cadet learning and experience. This can be done through the development of more holistic and well-rounded programs, as well as through training for cruise school faculty and staff to understand how to best integrate character education into their teaching. Studies show that cadets consider strong character important in the maritime profession. However, there are variations in their views on the effectiveness of character education in cruise schools. There needs to be stronger integration between character education and technical curriculum, as well as training for shipping school teachers and staff. The findings of this study provide the basis for the development of more effective strategies in improving the integration of character education in cruise schools.

ЕКОЛОГІЧНА КОМПЕТЕНТНІСТЬ СУДНОВОДІЇВ В УМОВАХ СТАЛОГО РОЗВИТКУ

Relevance: Under current conditions, the problem of ship navigation gains particular relevance – the formation of ecological competence of ship operators in the context of sustainable development, the study of important aspects of the interaction of vessels and the surrounding environment, particularly their impact on water resources, water pollution, emissions of harmful substances, and other ecological aspects. Objective: To determine the role of ecological competence of ship operators in the context of sustainable development. Methods: Theoretical methods: analysis, synthesis, generalization of scientific works on the issue of ecological competence of future professionals in the field of ship navigation and official documents – to define the theoretical and methodological bases of the phenomenon; study and generalization of the existing problem status with the aim of choosing pedagogical tools – for the development of ecological competence of ship operators; comparison – to identify various approaches to solving the researched problem; modeling – to justify the structural elements of the model for the development of ecological competence of ship operators. Results: Key characteristics of ecological competence and its components have been identified; ecological competence of ship operators is considered as a complex integrative characteristic of the personality, reflecting motives of ecological activity, possession of ecological knowledge and natural science bases, practical skills and abilities regarding environmental protection; the necessity of forming ecological competence in ship operators during their professional training has been substantiated, as it directly affects the conservation of the marine water state, protecting them from pollution. It is noted that under current conditions, when sustainable development has become one of the priority directions of global policy, the ecological competence of ship operators is a key factor in ensuring safe navigation, and ecological education in the maritime sector is an important tool for forming this competence in ship operators. Conclusions: Education acts as a catalyst for the development of sustainable thinking and practices in the maritime sector, promoting ecological safety and sustainable development in this strategically important industry; as the maritime sector continues to develop, the results of the conducted research emphasize the important role of education in preparing future ship operators to navigate the ecological complexities of the global maritime industry and to contribute to sustainable development and effective communication.

Метод определения эффективности вариантов организации перевозок барже-буксирными составами

A study has been conducted on the method of evaluating options for organizing cargo transportation by barge-tow trains based on determining their effectiveness. Using the methods of the classical theory of transport processes, this problem has no quantitative solution, since it is not possible to take into account the regrouping of the composition during the passage of the route. To overcome this problem, additional mathematical tools have been developed for constructing integral time and velocity matrices, an objective function and graphs of the ratios of the total volume of transported cargo to the time it was en route. The consistent implementation of the proposed tools ensures the coherence of the calculation methods for determining the effectiveness of a flight with and without regrouping on the route, and also makes it possible to select the most appropriate option for organizing transportation. The cumulative result allows us to reflect the method of evaluation, comparison and selection of the most effective option for organizing a flight / group of flights, taking into account the ability to set individual parameters for the movement of the train and cargo. An example of approximation of the coordinate points of the route from the Nizhne-Svirsky shipping lock to Lake Ladoga is illustrated, as well as an example of discretization of an inland waterway section according to a three-level model. The parameters of equalization of the objective function of determining the efficiency of cargo transportation are considered. It is concluded that the optimal transportation option can be carried out on the basis of a combined approach, when several parameters are taken into account or sequentially set in the process of modeling the operation of ships. Graphs have been built that demonstrate the differences between the ways of organizing flights.

Evaluation of constraints for investment in NOx emission technologies: case study on Greek bulk carrier owners

PurposeThe maritime industry is the transport mode that contributes most to air pollution. The International Maritime Organization (IMO) identified the reduction of air pollution by ships as a crucial issue. Since 1 January 2020, ships have had to adopt strategies and new technologies to eliminate air pollution. However, ship compliance with nitrate oxide (NOx) emission restrictions is more challenging. This paper aims to identify shipowners' challenges in investing in new technologies.Design/methodology/approachThis paper applied a hybrid methodology combining a survey, a balanced scorecard and fuzzy analytic hierarchy process (F-AHP) to identify and evaluate constraints and weights in investment decision-making for NOx technologies. A survey was carried out to validate constraints.FindingsA survey was carried out, representing 5.1% of Greek-owned ships by deadweight capacity. The findings provide a weighted list of seven crucial technical and economic constraints faced by ship operators. The constraints vary from ship retrofit expenditure to crew training and waste management. Additionally, NOx emission technologies were compared. It was found that liquefied natural gas is the preferred investment option for the survey participants compared with selective catalytic reduction, exhaust gas recirculation and batteries.Originality/valueSeveral studies have dealt with the individual technical feasibility of NOx reduction technologies. However, apart from technical feasibility for a shipowner, the selection of a NOx technology has several managerial and safety risks. Therefore, the originality of this paper is to reveal those constraints that have a higher weight on shipowners. With this cost-benefit approach, investment challenges for ship operators are revealed. Policymakers can benefit from the results of the employed methodology.

Developed Status and Forecast of Intelligent Ship Application

The concept of smart ships is not limited to ship autonomous driving, it covers a broader scope, including the full life cycle of ship design, construction, operation and maintenance. By integrating advanced sensors, navigation systems and data analysis platforms, smart ships are able to monitor ship status and the Marine environment in real time, optimize route planning and improve fuel efficiency, thereby reducing energy consumption and greenhouse gas emissions. In addition, smart ships can revolutionize the shipping industry by improving maritime safety and reducing human error through remote control and autonomous decision-making. In recent years, smart ship technology has gradually moved from the theoretical research stage to practical application, and has attracted wide attention from the global shipping industry. A number of international cooperation and research projects have been launched to explore the practical application potential and promotion paths of smart ships. However, the development of smart ships also faces many challenges, including technical difficulties, legal and regulatory restrictions, and public acceptance issues. This paper will deeply discuss the current development status of smart ships, analyze the main challenges it faces, and forecast the future development trend, in order to provide reference and inspiration for the innovative development of the shipping industry.

Complex network-based risk analysis for maritime heavy casualties in China during 2012–2021

A collection of accident investigation reports for the 21 maritime heavy casualties that occurred in China during 2012–2021 is studied statistically and analytically in the present study. The basic accident factors are first extracted from these investigation reports to present the distribution features of these heavy casualties. Then, the accident factors in terms of crew, environment, ship equipment and management in each individual investigation report are logically linked to develop a causative chain. As a result, 21 chains developed from the 21 accident investigation reports are interweaved into a complex network by sharing the same factors. The accident factors involved in the complex network are quantitatively assessed in terms of activeness, connection strength and criticality based on the network topology parameters and the improved K-shell decomposition algorithm. The topology of the developed complex network implies that the occurrence of maritime heavy casualties is under control, and the results show that the seaworthiness of crew, ship equipment and cargo is critical to maintain safe operation on board; meanwhile, supervising ship operators and managers to ensure that they fulfil their responsibility is an effective way to maintain the maritime safety level.

Proposal of a New Control System Making Use of AI Tools to Predict a Ship’s Behaviour When Approaching the Synchronism Phenomenon

In spite of the IMO’s efforts to improve the safety of intact stability on ships, synchronous rolling still causes large rolling angles, resulting in a very dangerous situation on board. The implementation of automatic tools to predict this undesirable situation has not been widely implemented. Furthermore, the safety of ship stability is not the only responsibility of people involved in the design process, so ship operators must have enough knowledge to predict and avoid these dangerous situations well in advance. Therefore, from a theoretical point of view, in the first part, this paper aims to present a valuable guiding tool for ship operators in order to predict synchronous rolling and avoid undesirable situations on board by making use of only empirical observations of the wave profile and moments. With this purpose, mathematical models are first proposed, with the ship sailing in the worst condition, i.e., with and without considering the damping factor, at zero speed and considering the influence of any pure beam and trochoidal waves. Relevant results shown provide the exact time and wave profile at which the maximum rolling angles are reached. In the second part of the paper, a new control system making use of AI tools is proposed in order to be used by ship operators on board, avoiding dangerous situations. Finally, the results are validated using a set of ship rolling simulations for the most common and representative ship loading conditions and wave periods.