Ship Officers Research Articles

The Effect of Safety Training and Technology on Ship Officers Performance and Its Implications on Human Resource Competency on Dynamic Positioning 2 Ship at PT Wintermar Offshore Marine Indonesia

This research aims to analyze the influence of training and safety technology on the performance of ship officers and its implications for human resource (HR) competence on the Dynamic Positioning 2 (DP2) vessel at PT Wintermar Offshore Marine Indonesia. The issues raised include significant investments in training, the use of outdated DP2 technology, and challenges in implementing training and compliance with safety procedures. The population of the study consists of ship crew members on board in 2024, with a sample of 80 Dynamic Positioning Officers (DPOs). The research method employs a quantitative approach, using questionnaires for data collection, and analysis is conducted using SMART PLS. The results indicate that training and safety technology significantly influence the performance of ship officers, positively impacting HR competence. The dimension that best reflects training is the relevance of the material, while for safety technology, the IoT system has a dominant influence. Based on the findings, it is recommended that the company adopt innovative approaches to problem-solving and update the satellite communications system to support field operations.

Deep Learning Methods to Mitigate Human-Factor-Related Accidents in Maritime Transport

Artificial intelligence aims to be the solution to multiple engineering problems by trying to emulate the human learning process. In this sense, maritime transport standards have clearly evolved, which are based on two principal pillars: the International Convention for the Safety of Life at Sea Convention (SOLAS) and the International Convention for the Prevention of Pollution from Ships (MARPOL). Based on a formal safety assessment research process, these pillars try to solve most of the maritime transport accidents, which, in their final steps, are associated with human factors. In this research, an original methodology employing a deep learning process for image recognition during mooring line operation, a dangerous process on ships, is developed. The main results indicate that the proposed method is an excellent tool for advising ship officers on watch and, consequently, provides a new way to prevent human factors onboard from causing accidents, which in the future must be considered in international standards.

Implementation of ISPS Code Security Level 2 at the Time the Ship Entered the Pontianak Navy Line to Prevent Security Threats Load at KM. Meratus Benoa

This research aims to implement ISPS Code Security Level 2 when the ship enters the Pontianak shipping channel to prevent cargo security threats on KM. Meratus Benoa. The time used by researchers to conduct research for 11 months and 13 days, starting from March 11, 2023-24 February 2024. KM. Meratus Benoa is one type of container deck ship managed by PT Meratus Line. This research method uses qualitative methods using Phenomenological research strategies. This data source collection technique is obtained from direct observation, interviews with ship crews and several journals related to this research. The results of this study indicate that the implementation of ISPS Code Security Level 2 when the ship enters the Pontianak shipping channel to prevent cargo security threats on KM.Meratus Benoa, namely by, a) Involving various efforts and activities such as patrols, security drills and additional supervision. Crew awareness and external support are also factors that influence the effectiveness of ISPS Code Security Level 2 implementation. b) There are coordination and training efforts carried out by ship officers to improve crew preparedness in dealing with security threats. As for the efforts made to prevent cargo security threats on KM Meratus Benoa by a) Restricting access to the ship and inside the ship to prevent unauthorized access, adding bulkheads to the pilot ladder door to increase security, adding guard officers and optimal division of guard duties when the ship enters a high-risk port area. b) conducting annual security exercise trials on a regular basis.

Conversational user interfaces for maritime autonomous surface ships

We propose integrating conversational user interfaces (CUIs) into Maritime Autonomous Surface Ships (MASS) to facilitate direct communication with other ships without human intervention. The aim is to enable other ships and shore stations to inquire about and discuss the autonomous vessel's status, decisions, and future intentions in natural language, offloading VHF radio conversations for MASS operators. Recent advancements in Natural Language Processing (NLP) technology show promise. This paper presents an experimental study conducted in a ship simulator using a functional prototype CUI system. While the CUI system was capable of providing coherent answers to questions, the results indicate that interacting with the system is less trustworthy than interacting with a human ship officer. Key challenges contributing to this included: (1) a missing connection between the CUI and an autonomy system, leading to inaccurate and incorrect answers, (2) speech that lacked intonation and human-like qualities, and (3) a perceived inability of the system to collaborate. The paper discusses several aspects of utilising CUI systems in a maritime shipping environment and concludes by proposing an approach to develop and implement them safely.

Determination of Ship Collision Avoidance Timing Using Machine Learning Method

The accurate timing for collision avoidance actions is crucial for preventing maritime collisions. Traditional methods often rely on collision risk assessments, using quantitative indicators like the Distance to the Closest Point of Approach (DCPA) and the Time to the Closest Point of Approach (TCPA). Ship Officers on Watch (OOWs) are required to execute avoidance maneuvers once these indicators reach or exceed preset safety thresholds. However, the effectiveness of these indicators is limited by uncertainties in the maritime environment and the human behaviors of OOWs. To address these limitations, this study introduces a machine learning method to learn collision avoidance behavior from empirical data of ship collision avoidance, particularly in cross-encounter situations. The research utilizes Automatic Identification System (AIS) data from the open waters around Ningbo Zhoushan Port. After data preprocessing and applying spatio-temporal constraints, this study identifies ship trajectory pairs in crossing scenarios and calculates their relative motion parameters. The Douglas–Peucker algorithm is used to identify the timing of ship collision avoidance actions and a collision avoidance decision dataset is constructed. The Random Forest algorithm was then used to analyze the factors affecting the timing of collision avoidance, and six key factors were identified: the distance, relative speed, relative bearing, DCPA, TCPA, and the ratio of the lengths of the giving-way and stand-on ships. These factors serve as inputs for the XGBoost algorithm model, which is enhanced with Particle Swarm Optimization (PSO), and thus constructing a ship collision avoidance decision model. In addition, considering the inherent errors in any model and the dynamic nature of the ship collision avoidance process, an action time window for collision avoidance is introduced, which provides a more flexible time range for ships to make timely collision avoidance responses based on actual conditions and the specific encounter environment. This model provides OOWs with accurate timing for taking collision avoidance decisions. Case studies have validated the practicality and effectiveness of this model, offering new theoretical foundations and practical guidance for maritime collision avoidance.

Justifying an application of the explanatory sequential mixed methods research design in maritime research

ABSTRACT Despite the efficacy of the mixed methods research design, there appears to be a need for more application in the maritime theme areas. This paper demonstrates the use of explanatory sequential mixed methods research (MMR) design in investigating the retention of ship officers. Previous studies often relied on the lopsided viewpoint of industry employers (using qualitative-oriented mono-methods) without capturing the employee side of the discourse. A web-based survey of 305 ship officers and a semi-structured telephone interview with 20 senior managers helped identify factors predicting the departure of ship officers to landside jobs. A long period of separation from family is a vital issue. Analysis of the interview transcripts helped explain the survey results. Sustainable HR practices are needed among shipping industry employers. Many respondents indicated that personal reasons accounted for the departure to landside jobs. The lack of support from employers during times of crisis compounds a high turnover conundrum among highly skilled ship officers. Shipping industry employers need to dedicate more resources to seafarer training even as the emergence of new technologies on board ships is placing existing skills out of fashion.

Quality Standards for Pollution Prevention Countermeasures for Safety and Security at the Port of Surabaya (Survey o (Survey on Tanker Ships at the Port of Surabaya)

The purpose of this study is to determine and analyze the activities of the shipping fleet in the use and use of aids to prevent and prevent pollution of the marine environment, the attention and willingness of officers and crew on the prevention and prevention of pollution of the marine environment, as well as strategies for handling and preventing pollution of the marine environment to support safety and shipping security. By using descriptive qualitative research, data collection is done through interviews and documentation studies to be further processed and analyzed. The results of the first analysis showed that there were still ships that were not in accordance with international standards on the means of supporting marine pollution prevention equipment and there were still crew members who were not aware of the need to prevent sea pollution. The second analysis shows that the attention and willingness of the ship's officers and crew still aboard the ship's officers who neglected the prevention of pollution by ships, not all crew members have the habit of paying attention to pollution by ships. The results of the third analysis indicate that there are still shipping companies that have not yet fully equipped the pollution prevention aids on ships, when shipping equipment is damaged it is rather difficult to provide a replacement. The results of the fourth analysis show that the strategy for preventing and preventing pollution of the marine environment to support shipping safety and security is the result of an analysis of the strengths and weaknesses as well as opportunities and threats to increase the prevention and prevention of pollution of the marine environment to support shipping safety and security.

Multi-ship encounter situation graph structure learning for ship collision avoidance based on AIS big data with spatio-temporal edge and node attention graph convolutional networks

With the increasing number of ships on the sea, the frequency multi-ship encounters situation was becoming more common than two-ship encounter. The complexity and risk of the navigation will exponentially increase with the more ships involved. Relying solely on the International Regulations for Preventing Collisions at Sea (COLREGS) (objective knowledge) was insufficient to handle the multi-ship intelligent collision avoidance problem, also needed the ship officer's good seamanship (subjective knowledge). In this study, we propose a methodology that combines subjective insights from AIS big data with objective analysis through multi-ship encounters recognition with graph convolutional networks (GCN). (1) The ship encounter 8-azimuths map was utilized to identify the two-ship encounter situation (25 types) from the AIS data. (2) Identify the multi-ship encounters trajectory data by cross-matching the two-ship encounter data. (3) To handle the intricate relationship information between the multiple ships which were transformed into a graph structure using graph theory. (4) Finally, a spatial-temporal edge and node attention graph convolutional network (ST-ENAGCN) was proposed with the graph convolutional unit and long short-term memory (LSTM) unit. The 2022 Ningbo Sea area AIS big data was utilized to achieve graph-structured learning regarding human experiences during the multi-ship encounters situation. The results indicate that the ST-ENAGCN model can understand the complex marine traffic situation to make the own ship collision avoidance decisions. This study contributes significantly to the increased efficiency and safety of sea operations in complex marine traffic conditions and support autonomous navigation of swarm of MASSs under the human-machine hybrid (HMH) conditions to better understand the collision avoidance intention of the ship officer in the multi-ship encounters situation.

Navigating careers at sea: Career proactivity in extreme work contexts

AbstractExtreme work contexts are characterized by highly demanding labor under intense, stressful, and risky conditions. The literature has to date been predominantly focused on operational, organizational, and institutional responses to these challenges. Consequently, scant attention has been paid to how individuals understand and respond to extreme work contexts when managing their careers. We conducted semi‐structured interviews with 33 Iranian merchant ship officers and developed a grounded theory model of career proactivity in extreme work contexts. Our model delineates two stages leading to proactive career behaviors: The first stage is sensemaking, where individuals wake up to the challenges of their extreme work context, engage in comparative elaboration, and arrive at a settled understanding of the extremity of their work context. The second stage is agency, where individuals engage in experimentation of when they can modify situations or adapt to them, which ultimately helps them choose one of the following proactive career behaviors: exit planning, job crafting, career drifting, and job embracing. To support the generalizability of our model, we interviewed nine firefighters, which confirmed the model's applicability to another extreme context. We discuss the theoretical and critical implications of our model for recent conversations in extreme context research and career research.

Emerging Dynamics of Training, Recruiting and Retaining a Sustainable Maritime Workforce: A Skill Resilience Framework

The maritime industry is regarded as the fulcrum of the global economy. It contributes significantly in diverse ways to the movement of goods. To effectively deliver on its mandate, maritime transportation needs to be sustainable. In the absence of a resilient and highly adaptive workforce; however, it is impossible to address the tangible set of economic, environmental and social expectations for the sector. From a human capital perspective, this paper explores the emerging dynamics of producing a sustainable workforce for global maritime transportation. Results from a recent study involving 305 ship officers (web-based survey) are compared with new changes (from academic sources and industry reports) in the maritime transportation sector. The comparison (findings) highlights emerging changes within the global maritime workforce and the implications for skill development. It also emerged that the shortage of highly skilled talent (on both the landside and seaside) is a critical challenge and is being exacerbated by growing industry changes. Ultimately, these developments endanger sustainable maritime transportation. Consequently, the paper proposes a skill resilience framework with which industry stakeholders could identify skill gaps among the workforce and improve training content to produce an adaptive workforce capable of handling emerging challenges.

RAGAN: A Generative Adversarial Network for risk-aware trajectory prediction in multi-ship encounter situations

Ship trajectory prediction plays a vital role in ensuring safety in dense waterway traffic. However, conventional prediction methods often disregard the intricate spatial–temporal interactions and the inherent collision avoidance maneuvers that occur during multiple ship encounters, leading to inadequate accuracy in interacted trajectory predictions. To address this challenge, we propose a risk-aware trajectory prediction framework based on Generative Adversarial Network (RAGAN) architectures. RAGAN leverage GANs to learn latent collision avoidance interaction patterns in multi-ship encounters. Through adversarial training, RAGAN continuously enhances its capability to generate precise and safely acceptable ship trajectories that faithfully represent the actual collision avoidance strategies adopted by ship officers. Furthermore, by incorporating an interacting gate function, RAGAN effectively captures the evolving risks and influences within encounter situations, enabling dynamic representation of ship interactions and their profound impact on the development of encounters. Evaluation using real-world ship trajectory data demonstrates the superior performance of RAGAN compared to the baseline method across various evaluation metrics. Through case studies, RAGAN exhibits the ability to learn navigation rules beyond existing regulations, such as the COLREGs, and provides valuable insights for enhancing safety in maritime operations.

The effectiveness of S-100 ECDIS capable of ENDS in the view of ship officers’ visual characteristics

The development of electronic chart display and information systems (ECDIS) has enabled conversion of nautical charts from paper publications to electronic format. Because the International Maritime Organization (IMO) has mandated the installation of ECDIS in ships engaged in international navigation, the effectiveness of the newly introduced S-100 ECDIS must be determined using electronic equipment, compared with traditional navigation preparation tasks. Here, the effectiveness of the S-100 ECDIS, capable of Electronic Navigational Data Service (ENDS), was compared with the effectiveness of the existing ECDIS and traditional nautical publications by analyzing the visual performance of ship officers during tasks involved in developing a voyage plan. This study showed that the S-100 ECDIS with ENDS is more effective than the S-57 ECDIS with nautical publications. The improvement in voyage planning using the S-100 ECDIS was demonstrated by ship officers’ visual performance.

Coordinated multi-stage and multi-objective optimization approach for ship collision avoidance decision-making

Appropriate decision-making is essential to prevent ship collisions and further ensure navigational safety at sea. Current research on collision avoidance decision-making (CADM) primarily aims to find limited feasible solutions based on a designated safe distance under the strong assumption that ships take no or little maneuvering actions. To overcome such limitations, a multi-stage and multi-objective CADM optimization approach is proposed to satisfy the requirements of safety and economy, while considering the ship path uncertainties and risk preferences of ship officers. First, a comprehensive collision risk estimation method is formulated by quantifying degree of domain violation and probability of domain violation (PDV) in dynamic and uncertain situations. Then, the CADM for each individual ship is treated as a multi-objective optimization problem, and a three-stage optimization approach outlines the process to find optimal collision avoidance path. Preliminary non-dominated solutions are obtained and filtered to enhance the robustness by an accepted threshold of the PDV. Optimal solutions are selected for ship officers with different risk preferences. Finally, the coordinated collision avoidance path for multi-ship encounter is determined based on the exchange of individual collision avoidance path through several rounds of coordination. The effectiveness of CADM method is validated through extensive case studies. The results show that it can provide feasible solutions for multi-objectives and adaptively determine the most appropriate scheme for ship officers with different risk preferences to make coordinated decisions.

OPTIMALISASI PENERAPAN PERAWATAN HATCH COVER UNTUK MENGHINDARI KETERLAMBATAN PROSES MUAT BONGKAR PADA MV. CHANDRA KIRANA

Hatch Cover is a part of the ship that is useful for protecting cargo from seawater and avoiding damage that can cause cargo damage. To make the load not damaged, of course, optimal maintenance is needed for the hatch cover and what needs to be applied in the maintenance of the hatch cover on the MV. Chandra Kirana so that damage can be avoided completely. 
 The research method used is descriptive qualitative by describing the problem through observing what happens in the field, indirect interviews conducted with ship officers and crew, literature study, and documentation. By using this research method, the required data is obtained and then analyzed and presented with a descriptive narrative. 
 From the results studied, it was found that there were problems with the application of hatch cover maintenance which was less than optimal and there were many obstacles encountered when carrying out hatch cover maintenance which resulted in delays in maintenance. Researchers suggest that companies can implement workshops for crew members who will board so they can know what to do in treating and repairing hatch cover damage and following hatch cover maintenance procedures in accordance with Doc. No. JSP E41 namely inspection and maintenance plan of bulk carrier hatch cover so that hatch cover maintenance can be carried out properly and reduce additional costs in the event of cargo damage

Fatigue Detection for Ship OOWs Based on Input Data Features, From the Perspective of Comparison With Vehicle Drivers: A Review

Ninety percent of the world’s cargo is transported by sea, and the fatigue of ship officers of the watch (OOWs) contributes significantly to maritime accidents. The fatigue detection of ship OOWs is more difficult than that of vehicles drivers owing to an increase in the automation degree. In this study, research progress pertaining to fatigue detection in OOWs is comprehensively analysed based on a comparison with that in vehicle drivers. Fatigue detection techniques for OOWs are organised based on input sources, which include the physiological/behavioural features of OOWs, vehicle/ship features, and their comprehensive features. Prerequisites for detecting fatigue in OOWs are summarised. Subsequently, various input features applicable and existing applications to the fatigue detection of OOWs are proposed, and their limitations are analysed. The results show that the reliability of the acquired feature data is insufficient for detecting fatigue in OOWs, as well as a non-negligible invasive effect on OOWs. Hence, low-invasive physiological information pertaining to the OOWs, behaviour videos, and multisource feature data of ship characteristics should be used as inputs in future studies to realise quantitative, accurate, and real-time fatigue detections in OOWs on actual ships.

Ship navigation from a Safety-II perspective: A case study of training-ship operation in coastal area

This study presents how resilience is incorporated in the everyday operation of a ship from the Safety-II perspective. The study identifies the contribution to ship safety owing to the bridge team's performance in navigating the ship. A qualitative observation and the functional resonance analysis method have been applied to analyse officers’ everyday performance. Essential functions of officer activities onboard are generated via direct observation and semi-structured interviews on the training ship Fukae-maru. System activities are modelled in terms of how the actual work happens. The specific dynamic functional model of ship navigation is obtained to further express the dynamic work of the watch officers. The result indicates that the ship officer's adaptability and flexibility beneficially contributed to the system's ability to monitor, respond, learn, and anticipate. This resilience was distinctly demonstrated through function and couplings. Furthermore, this study acknowledges human functions as a resource to cope with the complexity escalation that results from technological development for future maritime transportation.

Evaluation of ship collision risk in ships’ routeing waters: A Gini coefficient approach using AIS data

Ships’ routeing was first adopted to reduce the risk of ship collisions and promote marine traffic efficiency. But as maritime transport continues to develop, the number of ships passing through ships’ routeing areas keeps increasing and the navigational environment is becoming increasingly complex, which also poses a major challenge to navigational safety. In this contribution, a quantitative assessment method based on the Gini coefficient is proposed to evaluate the ship collision risk in ships’ routeing waters. This method is applied to Ningbo Zhoushan Port, the Gini coefficient of the course over ground (COG) for each leg is calculated with the historical Automatic Identification System (AIS) data, and then the Hierarchical Clustering Algorithm (HCA) is applied to classify the 28 legs of the ships’ routeing waters in Ningbo Zhoushan Port into 5 risk levels. The results show that: PA 4 and 7 are high-risk areas; PA 1 and 2 are medium-high-risk areas. It is recommended that when navigating in these areas, ship officers and captains should be particularly cautious and that priority should be given to these areas when formulating ship collision risk prevention measures and risk control plans.

Analysis of Collision Hazard Prevention With Operating Radar NICD – 453 Type On MV Amrta Jaya 1

The navigation system is the key to the safety of the ship in carrying out the voyage. RADAR will be very useful during bad weather, foggy conditions and sailing at night, especially when navigational instructions such as beacons, buoys, hills or buildings cannot be visually observed. So prospective ship officers must understand and understand to use RADAR navigation tools. To find out the target position and reduce the accident rate in the shipping lane, the role of RADAR in supporting shipping safety is needed. This study aims to analyze the prevention of collision hazards by using the Maneuvering Board in the operation of the Binocular RADAR at MV AMRTA JAYA 1. The type of research used in this study is quantitative research. In this case the data collection techniques used are documentation and observation. Documentation is in the form of searching for information in the form of books and documents, while observation is in the form of an approach to the object of research. From the results of research conducted, it can be seen that the method used to calculate the RADAR Plotting Sheet can be done by theoretical methods with formulas and scale methods with mathematical logic. The two methods can be used with the same results but with different time efficiency. The use of muvering boards and RADAR Plotting Sheet calculations can help identify the presence or absence of a collision hazard, and help estimate the closest distance, time taken, course and speed of the target ship.

The Role of Fire Detection Equipment To Prevent Fires In MV. Soemantri Brodjonegoro

The role of fire detection tools is very helpful in preventing fire hazards in MV. Soemantri Brodjonegoro, on this basis, the author formulates the problem of the extent of the ship's crew's knowledge of fire detection tools and how to maintain fire detection tools in MV. Soemantri Brodjonegoro. The method used in this study is a qualitative method that produces descriptive data in the form of written words from people and observed behaviors. In this case, collecting data in the form of an approach to the object through observation, direct interviews with the subject. Based on the results of research and discussion of problems carried out by the author during the practice of screening in MV. Soemantri Brodjonegoro regarding the role of fire detection devices found problems in the role of fire detection devices which include the lack of knowledge of ship crews about fire detection tools caused by the lack of implementation of new crew familiarization and the lack of implementation of safety meetings on ships. The discussion of the results of the study is to increase the ship crew's knowledge of fire detection equipment by means of maximum familiarization of the new crew and carry out safety meetings once a month, as well as improve the maintenance of fire detection equipment by means of good coordination between the ship and the company and increasing the responsibility of ship officers by checking fire detection equipment regularly. In this case, it is concluded that the lack of knowledge of the ship's crew and the maintenance of fire detection equipment can cause the malfunction of the tool properly, namely as a tool to detect fire hazards on board so that the fire detection tool can function properly to support shipping.

PLANNING THE CARGO OPERATIONS OF A BULK CARRIERWITH CONTINUOUS MAINTAINING ITS SEAWORTHINESS

The nautical safety of bulk carriers is largely determined by their correct loading. The available ship's instruments do not allow timely planning of loading operations and real-time control of the ship's condition during their execution. The ship's officers in charge have to spend a lot of time preparing the loading (unloading) plans. The high intensity of cargo operations at modern dry bulk terminals and the lack of sufficient time to prepare and verify the new cargo plan may create a risk of cargo holds being overloaded. This may lead to a deterioration of the local and longitudinal strength of the hull and a violation of the seaworthiness of the ship. The solution to this problem should be the development of new methods of cargo operations planning. Such methods should be based on a strategy of optimizing the distribution of a given quantity of bulk cargo, taking into account the availability of port facilities and the design of the vessel itself, its nautical parameters, stability, longitudinal and local strength. In order to achieve this objective, it is necessary to formalize the cargo operations in terms of a mathematical model of the ship and to establish the functional relationship between the parameters affecting the seaworthiness of the ship. Obviously, the development of this method is a promising area of scientific research aimed at improving the safety of bulk carriers.The article describes the method of loading operations of a bulk carrier with the task of choosing the best strategy for carrying out cargo operations according to the criterion of continuous seaworthiness of the vessel.Keywords: bulkcarrier, maritime safety, cargo operations, permissible loading, ship stability, the vessel strength, optimisation.