Marine Incidents Research Articles

An investigation of the effect of workload on ship engine room operators using fNIRS

This is an investigation into the Performance Shaping Factors (PSFs) associated with ship engine room operators. This study looks at the effect of workload. There is a large portion of human error associated with marine incidents. Human error may be considered as a result of additional supplementary tasks on top of an accustomed workload. The aim of this study is to evaluate the effect of workload on human performance. To achieve this, a TRANSAS simulator series 5000 was used to replicate a real scenario with the addition of workload as a PSF. Each participant engaged in a fault detection and correction task. 20 participants were used for the workload study; all 20 were trained for 3 h to use the engine room software interface. The participants then completed a 30-min ballasting task. During this interaction, 50% of the participants underwent a simulated scenario where the workload was increased. The other 50% were given a standard task. Functional near-infrared spectroscopy (fNIRS) was used to measure the participant's activation levels, more specifically from the dorsolateral prefrontal cortex (DLPFC) region of the cerebrum. The results showed an increase in activation of the DLPFC during each phase of the task, this trend was magnified by the addition of increased workload. The results are discussed with respect to human performance during varying workload. From the results of this study, a human classification performance model was developed. This model can be used by the maritime industry to better evaluate and understand human error causation.

Unraveling the patterns of critical contributory factors and flag-state affiliations linked with maritime incident outcomes

Maritime incidents are complex in nature and result from various factors. Although researchers have explored the factors influencing maritime safety, it is unclear how the critical contributory factor chains including flag-state associations, influence maritime incident outcomes, namely deaths, injury, and missing person cases. This paper applies a robust non-parametric Association Rules Mining (ARM) algorithm to an extensive marine incident database to identify critical patterns of key contributory factors and flag-state associations leading to different maritime incident casualty outcomes. The study dataset comprised 13,758 maritime incidents recorded between 2002 and 2015 in US territorial waters. This data was sourced from the Marine Information for Safety and Law Enforcement (MISLE) database system and served as the basis for analysis. A preliminary investigation revealed that low-weight passenger ships were most likely involved in maritime incidents. Further analysis established that, whereas Bahamas-registered vessels were highly likely to be involved in incidents associated with deaths, US-registered vessels were primarily related to injury-related incidents. Singaporean ships were often involved in missing-person incidents. Additionally, the results highlighted significant associations between ocean cruise vessels and existing medical conditions with deaths. Besides, passengers, towing service vessels, and crewmembers were identified to be highly associated with injury. Higher-order associations depicted that tank ships, fishing vessels, ship masters and crew members are likely to be involved in maritime incidents where missing persons are involved. Policies directed at eliminating/controlling the contributory factors identified to lead to a particular outcome to help reduce the occurrence or impacts of maritime incidents have been suggested.

An Analysis of Causes Related to Human Factors in Maritime Accidents

Safety is the most critical job of any Mariner. Recently, the maritime industry has embedded automated systems onboard ships to reduce workload and improve safety. This study explores several recent marine incidents generated by human errors resulting from improper use of technology and the loss of situational awareness. Accidents within three categories of vessels illustrate findings, small passenger vessels, a container ship, and military vessels, using the official accident reports and agency findings. The results indicate that three categories of errors were identified: competence-based, regulatory-based, and perception-based. By sharing this information, Governments, Educators, Mariners, Admiralty Lawyers, and vessel owners can work together to improve maritime safety. This research article proposes academic Maritime Education and Training (MET) strategies and administrative systems to recognise the deficiencies between human factor errors and digital innovation to prevent such accidents from reoccurrence.

Oil spill trajectory modeling and validation: case study on a marine incident at Adriatic Sea

Oil spill trajectory modeling and validation: case study on a marine incident at Adriatic Sea

Detection of Abnormal Vessel Behaviours Based on AIS Data Features Using HDBSCAN+

Achieving maritime security is challenging due to the vastness and complexity of the domain. Monitoring all Achieving maritime security is challenging due to the vastness and complexity of the domain. Monitoringall vessels that use this medium is humanly impossible but is needed for law enforcement. This paper proposes amachine learning solution based on HDBSCAN+ to classify the movements of vessels into ‘normal’ or ‘abnormal’.This classification reduces the number of vessels that have to be monitored by law enforcement agencies to amanageable size. To date, AIS is the primary source of information that can represent vessel movements andenable the detection of maritime anomalies. The proposed model uses latitude, longitude, type of vessel, courseand speed as features of the AIS data for analysis. The performance of the proposed model is validated against the marine incidents reported by Information Fusion Centre-Indian Ocean Region (IFC-IOR). The proposed model has successfully detected the incidents reported by IFC-IOR.

Analysis of marine incidents and policy implications: Case study of the South Korea

According to Heinrich's Law, dozens of minor accidents and signs of their impending occurrence appear for the same cause before a major accident occurs. The International Maritime Organization (IMO) recommends that member states manage marine incidents to prevent very serious marine casualties. This paper analyzed the marine incident notification system managed by the South Korea and suggests policy implications accordingly. First, marine incident statistical data were used to analyze the relationship with marine casualties. Additionally, a survey was conducted on ship operators who report marine incidents, and trends were analyzed. Last, system dynamics was used to analyze the effect of activating the marine incident notification system on the reduction of marine casualties. The analysis revealed that 1.9 very serious marine casualties can be reduced per year by activating the system. Introducing the case of South Korea managing marine incidents and performing a case analysis, it was confirmed that managing marine incidents is helpful in reducing very serious marine casualties. These findings can serve as basic data for marine incident management policies.

Developing the marine medicine syllabus for medical sciences students: a multiphase design study

BackgroundMarine medicine is one of the medical fields that deals with the health and safety of people related to the sea but the marine medicine syllabus for education to the students is not specified yet. The present study aimed to develop the marine medicine syllabus to medical sciences students education.MethodsThis study was conducted in three phases. First, a literature review was conducted to find the concepts and topics related to marine medicine. Second, a content analysis research method was conducted. Data collection was done first by using semi-structured interviews with the 12 experts in marine medicine. Sampling was purposeful and continued until data saturation was reached. The information obtained from the interviews was analyzed by conventional content analysis with Geranheim's method. The found topics in the literature review and content analysis of interviews were combined and formed the initial draft of the marine medicine syllabus, which was validated with the Delphi method in the third phase. The Delphi was conducted in two rounds and the panel consisted of 18 experts in the field of marine medicine. After the completion of each round, the items that had less than 80% consensus among the participants were removed and the remaining topics after round two formed the final syllabus of the marine medicine.ResultsThe findings showed that the marine medicine syllabus should include an overview of marine medicine, health at sea, common physical diseases and injuries at sea, subsurface medicine and hyperbaric, safety action in marine incidents, medical care at sea, psychology at sea and medical examinations of people working at sea main topics and their sub topics.ConclusionsMarine medicine is an extent and specialized medical field which has been neglected and it is necessary to teach this lesson to medical sciences students with the syllabus found in the present study.

The Analysis of Social and Situational Systems as Components of Human Errors Resulting in Navigational Accidents

As in any industry exposed to risk, human and organizational factors are the main stakes of maritime safety. Understanding the causes and risks of maritime accidents is integral to the sustainability of shipping. The investigation of marine accidents is a crucial tool for their identification in areas related to operations and ships, including social and situational systems, their design, and technical systems. The authors conducted a cause–effect analysis of marine incidents. For this purpose, case-by-case analysis and an Ishikawa diagram were used, which is a tool that helps identify actual or potential causes of accidents. The study showed that by far the most significant cross-section of causes of accidents were elements of social and situational systems that affect the safety of the ship, crew, and environment. The least significant contribution came from the machinery area. Through the detailed descriptions, a picture emerges not so much of a lack of knowledge of the regulations as of a failure to comply with existing procedures or best practices. In the authors’ opinion, more emphasis is needed on preventive measures, including safety culture, training, competence assessment, and increased awareness of the need for sustainability.

Collaborative search and rescue based on swarm of H-MASSs using consensus theory

Swarm of marine autonomous surface ships (MASSs) constitutes the most critical part in maritime search and rescue (MSR). A collaborative consensus strategy for the swarm of heterogeneous MASSs (H-MASSs) is proposed, which realizes large-scale continuous and efficient search after marine incidents. (1). The MSR area is allocated according to the search and rescue capability (SRC) of H-MASSs based on the drift model; (2). Based on the search and rescue progress rate (SRPR), a consensus controller is designed to make the swarm of H-MASSs collaborate to complete the task synchronously; (3). Line-of-Sight method is improved to ensure stable path tracking of swarm. The experimental verification and efficiency comparison shows that the collaborative consensus strategy improves the efficiency by 42% compared with the strategy without considering the SRC, and is 22% higher than the decentralized control strategy, which has strong efficiency and stability. It can provide a theoretical basis for the large-scale cooperative operation of the swarm of H-MASSs in the future, and gradually realize the autonomous navigation of the swarm of H-MASSs formation in the whole sea area with the development of ship networking technology.

Generalized Behavior Decision-Making Model for Ship Collision Avoidance via Reinforcement Learning Method

Due to the increasing number of transportation vessels, marine traffic has become more congested. According to the statistics, 89% to 95% of maritime accidents are related to human factors. In order to reduce marine incidents, ship automatic collision avoidance has become one of the most important research issues in the field of ocean engineering. A generalized behavior decision-making (GBDM) model, trained via a reinforcement learning (RL) algorithm, is proposed in this paper, and it can be used for ship autonomous driving in multi-ship encounter situations. Firstly, the obstacle zone by target (OZT) is used to calculate the area of future collisions based on the dynamic information of ships. Meanwhile, a virtual sensor called a grid sensor is taken as the input of the observation state. Then, International Regulations for Preventing Collision at Sea (COLREGs) is introduced into the reward function to make the decision-making fully comply with COLREGs. Different from the previous RL-based collision avoidance model, the interaction between the ship and the environment only works in the collision avoidance decision-making stage. Finally, 60 complex multi-ship encounter scenarios clustered by the COLREGs are taken as the ship’s GBDM model training environments. The simulation results show that the proposed GBDM model and training method has flexible scalability in solving the multi-ship collision avoidance problem complying with COLREGs in different scenarios.

Marine diesel engine ANN modelling with multiple output for complete engine performance map

Marine incidents given in recent years have been in part caused by propulsion issues. In this context, incipient propulsion faults may be identified by deviations between real values and healthy engine values provided by an accurate model. Engine modelling techniques have thus become a topic of interest in the last decade. On this basis, Machine learning approaches such as Artificial Neural Networks (ANN) have proved to be accurate and fast in terms of calculation times. However, up to now most research work has focused on predicting a few parameters for specific operation points. In order to analyse the generalization capability of ANN when predicting multiple outputs in real engine conditions, 35 different performance and emission parameters were simultaneously predicted in this study with an ANN. To do so, different engine operation points were tested in a six-cylinder marine diesel engine, characterizing the whole engine performance map. Additionally, some points from random regions throughout the entire engine performance map were tested to later analyse ANN performance on them. After defining network optimum structure and training and validating the Artificial Neural Network with 1000 data samples, the ANN was tested with data extracted from unseen random regions of the performance map. Mean Absolute Percentage Errors obtained for testing samples from random points of the engine performance map remained below 8.5% for all parameters with the exception of CO and NO2 emissions predictions. For low temperature and high temperature cooling systems, oil system and exhaust gas system, MAPE values obtained were below 4.3%. Calculation time for 24 testing samples containing 35 parameters was 0.109 s, which along with the high accuracy level obtained demonstrated that ANN can predict multiple outputs throughout the whole engine performance map.

МЕТОДОЛОГІЇ ТА ПІДХОДИ ДО РОЗСЛІДУВАННЯ АВАРІЙ ТА ІНЦИДЕНТІВ НА МОРІ

High-priority question now is to provide a common approach for States to adopt in the conduct of marine safety investigations into marine casualties and marine incidents. Marine safety investigations do not seek to apportion blame or determine liability. Instead a marine safety investigation is an investigation conducted with the objective of preventing marine casualties and marine incidents in the future. This aim will be achieved through States: - applying consistent methodology and approach, to enable and encourage a broad ranging investigation, where necessary, in the interests of uncovering the causal factors and other safety risks; - providing reports to the Organization to enable a wide dissemination of information to assist the international marine industry to address safety issues. A marine safety investigation should be separate from, and independent of, any other form of investigation. However, not precluding any other form of investigation, including investigations for action in civil, criminal and administrative proceedings. Further, a State or States conducting a marine safety investigation should not refrain from fully reporting on the causal factors of a marine casualty or marine incident because blame or liability, may be inferred from the findings. Each flag State has a duty to conduct an investigation into any casualty occurring to any of its ships, when it judges that such an investigation may assist in determining what changes in the present regulations may be desirable, or if such a casualty has produced a major deleterious effect upon the environment. A flag State shall cause an inquiry to be held, by or before a suitably qualified person or persons into certain marine casualties or marine incidents of navigation on the high seas. However, if a marine casualty or marine incident occurs within the territory, including the territorial sea, of a State, that State has a right to investigate the cause of any such marine casualty or marine incident which might pose a risk to life or to the environment, involve the coastal State’s search and rescue authorities, or otherwise affect the coastal State.

Shipping Accidents Dataset: Data-Driven Directions for Assessing Accident’s Impact and Improving Safety Onboard

Recent tragic marine incidents indicate that more efficient safety procedures and emergency management systems are needed. During the 2014–2019 period, 320 accidents cost 496 lives, and 5424 accidents caused 6210 injuries. Ideally, we need historical data from real accident cases of ships to develop data-driven solutions. According to the literature, the most critical factor to the post-incident management phase is human error. However, no structured datasets record the crew’s actions during an incident and the human factors that contributed to its occurrence. To overcome the limitations mentioned above, we decided to utilise the unstructured information from accident reports conducted by governmental organisations to create a new, well-structured dataset of maritime accidents and provide intuitions for its usage. Our dataset contains all the information that the majority of the marine datasets include, such as the place, the date, and the conditions during the post-incident phase, e.g., weather data. Additionally, the proposed dataset contains attributes related to each incident’s environmental/financial impact, as well as a concise description of the post-incident events, highlighting the crew’s actions and the human factors that contributed to the incident. We utilise this dataset to predict the incident’s impact and provide data-driven directions regarding the improvement of the post-incident safety procedures for specific types of ships.

System of Water Vehicle Power Plant Remote Condition Monitoring

Remote condition monitoring of water vehicles plays an important role in preventing potentially very expensive marine incidents and ensuring maximum efficiency of a ship's operation and reliability with minimum maintenance downtime and repair costs. Concept of the condition-based approach to maintenance is today's best practise, and it is becoming increasingly important to move from planned maintenance to condition-based maintenance, to reduce the increasingly high cost of maintaining a modern fleet. Onboard and remote monitoring is now an essential part of condition-based maintenance process to obtain the good quality data, correct analysis, and effective counteractive actions necessary for such an approach, and article presents the water vehicle power plant monitoring model developed by authors. Considered approach, coupled with preventive maintenance, saves shipowners time and money through early diagnosis of component failure or excess wear. Power plant of water vehicle comprises far more than just an engine with its auxiliary equipment but also other main propulsion blocks – in particular, thrusters. The result was the development of the Water Vehicle Condition Monitoring (WVCM) system, which enables to closely examine water vehicle equipment performance. A WVCM system comprises the following installed onboard: accelerometers, pressure and temperature transmitters, oil, fuel and exhaust monitoring units and a torque measurement system.

A Statistical Analysis of the Causes of Marine Incidents occurring during Berthing

A Statistical Analysis of the Causes of Marine Incidents occurring during Berthing

The value of meteorological data in marine risk assessment

The objective of this paper is to investigate whether the use of meteorological data improves the prediction of marine incidents, as represented by marine insurance claims for a vessel's voyage, both on a stand-alone basis and when combined with vessel-specific features and ship tracking data from the Automated Identification System (AIS). Furthermore, the paper investigates whether predictive performance improves when using machine learning algorithms, such as logistic LASSO regression and eXtreme Gradient Boosted Trees over classical logistic models, and identify dependencies and interaction effects among the risk factors within the SHapley Additive exPlanations framework. The data sample includes weather and AIS data for 42,000 voyages in the North Pacific between January 2013 and August 2019. The results suggest that meteorological information adds value in claims prediction and that short-term complex interactions between the vessel and weather conditions impact marine risk. The research is important for the improved modelling of marine risk on the basis of high-frequency, high-resolution ship tracking and weather data.

Poor sleep quality, long working hours and fatigue in coastal areas: a dangerous combination of silent risk factors for deck officers on oil tankers.

The high number of marine incidents in port and coastal areas due to the tired deck officers' erroneous actions are one of the major challenges of marine transportation. Approaching, berthing, and cargo handling (ABC) are the most stressful and exhausting operations of the ship in these areas, which are carried out consecutively and uninterruptedly. This study examined Psychomotor Vigilance Task (PVT) performance, Arrow Flanker Task performance and the Pittsburgh Sleep Quality Index (PSQI) of 70 deck officers of ocean-going oil tankers with 4on-8off shifts at the end of the first shift of cargo-handling operations. In this case, they had worked more than 14 hours continuously. Also, their level of sleepiness was assessed using the Karolinska Sleepiness Scale (KSS) at the beginning, middle, and end of their first shift of handling operation. The results were analysed according to the duration at sea and deck officers rank. PSQI, KSS, PVT mean reaction times and lapses, and also Flanker's variables were higher among the chief and second officers who were present on board between 0-30 days. The state of officers who were present on board between 31 to 60 days was better than the officers with 0-30 and 61-90 days' duration at sea. In addition, the results show that sleep quality during tour of duty affects cognitive performance and sleepiness of officers during cargo handling operations. The paper concludes by discussing possible solutions for reducing fatigue and human error among seafarers.

Time to Rescue for Different Paths to Survival Following a Marine Incident

The time required for rescue is a critical factor for surviving a marine incident. The regulatory framework, International Maritime Organization (IMO) Polar Code, utilizes a risk-based approach. It states that the vessel operators are to define the time required for rescue but never less than 5 days. Based on experience from the classification society DNV GL, utilization of the minimum requirement of five days is the current industry standard when conducting risk assessments. The dimensioning of search and rescue resources is a national issue. There are no international requirements defining the adequacy of the resources for different geographical areas. The remoteness and lack of resources present within the IMO Polar Code area imposes a significant challenge for mariners in distress. The time required for rescue is highly dependent on multiple variables. Based on this study, the number of persons to be rescued, the number and type of evacuation platforms and the distance each evacuation platform must travel significantly impacts the time required for rescue. In addition, the meteorological and oceanographical (metocean) conditions play a significant role when determining the efficiency of a search and rescue operation.

A Study on the Selection of VTS Marine Incident Classification Criteria at the Busan Port

A Study on the Selection of VTS Marine Incident Classification Criteria at the Busan Port

A Study on the Revision of the Notification Form and Procedures of Marine Incident

A Study on the Revision of the Notification Form and Procedures of Marine Incident