Digital Twins have much attention in the shipping industry, attempting to support all phases of a vessel’s life cycle. With several tools appearing in Digital Twin software suites, high-quality manoeuvring and performance prediction remain cornerstones. Propulsion efficiency is in focus while in service. Simulator-based training is in focus to ensure safety of manoeuvring in confined waters and harbours. Prediction of ships’ velocity and turn rate are essential for correct look and feel during training, but phenomena like dynamic inflow to propellers, bank and shallow water effects limit simulators’ accuracy, and master mariners often comment that simulations could be in better agreement with actual behaviours of their vessel. This paper focuses on digital twin enhancements to better match reality. Using data logged during in-service operation, we first consider a system identification perspective, employing a first-principles model structure. Showing that a complete firstprinciples model is not identifiable under the excitation met in service, we employ a Recurrent Neural Network to predict deviations between measured velocities and the model output. The outcome is a hybrid of a first-principles model with a machine learning generic approximator add-on. The paper demonstrates significant improvements in prediction accuracy of both in-harbour manoeuvring and shallow water passage conditions.
As the world collectively looks to technology to salvage what is left of our world to sustain a habitat that can accommodate our way of life, users are increasingly exposed to technological solutions, rarely developed with an offset in their practice. This also holds for the maritime sector in Denmark, where the way of developing technology is limited to the applicability of technological artifacts and can reduce the potential efficiency gains that technologies can introduce. This paper applies qualitative research to show that there is a disconnect between, on the one hand, funders, technology developers, and decision-makers and, on the other hand, technology users and practitioners in the Danish maritime sector. It argued that if technology is to replace or assist any human practice and solve for example the climate crises, then knowledge of users’ practices must be key to developing the technological solutions.
Background: Fishing is a risky occupation as injuries and fatalities in fishing vessels are quite common. This paper investigates the pattern of injuries aboard fishing vessels in Denmark to get a better understanding of areas where further action is needed to reduce the number of injuries and fatalities in Danish fishing vessels. Materials and methods: Data for this study, extracted from the Danish Fishermen’s Occupational Health Service’s database (in the period 1998–2012) and the Danish Maritime Authority’s accident report from 2013 to 2016, include 1840 injuries in Danish fisheries. Result: The results showed decreased injuries in the study period from 45 injuries and deaths per 1000 fishermen reported to the authorities to 12 injuries and deaths per 1000 fishermen in 2016: 2.1% (n = 39) of all reported injuries in the study period resulted in the death of a fisherman and the remaining injuries resulted in sick leave of more than one day; 52.5% (n = 600) of reported injuries involved fishermen who have less than one year’s experience of employment; 29% (n = 407) of injuries took place between 12:00 and 16:00, and the second largest number of injuries, 23.3% (n = 324), took place between 8:00 and 12:00. The incident rate of slip/fall injuries has decreased from 10.06 per 1000 fishermen in 1998 to 3.84 in 2016. The incidence rate of injuries caused by crushing also decreased, from 9.32 accidents per 1000 fishermen in 1998 to 2.56 in 2016. Most of the injuries, 74.5% (n = 1307), happened on the deck of the vessel. Sprain/strain was among the most common injuries (34.2%; n = 538) followed by fracture (24.8%; n = 391). Conclusion: This study indicated that the number of injuries had been gradually decreasing in Danish commercial fishing vessels in the period from 1998 to 2016. The rate of injuries had been declining due to several initiatives such as the establishment of The Danish Fishermen’s Occupational Health Services, training, safety campaigns, technological improvement and structural changes in fisheries management. However, there are still places for improvement.
ABSTRACT: Climate change provides for improved conditions for maritime navigation and results in increased activity in the Arctic. Those increased activities influence the safety at sea and risk of accidents. A disaster as the Costa Concordia incident would have far more serious consequences in Greenlandic waters than it had in Italy, therefore the question of prevention and disaster-preparedness is crucial. One approach to avoid risks is to create specific legislation. The legal system guiding safe navigation of cruise ships in/around Greenlandic waters is complex: the legal regime for navigation is set in different general and specific international, regional and national legal acts, partly non-binding, therefore issues of effectiveness arise. Safety is also influenced by practical issues, e.g. the lack of sufficient nautical charts for Greenlandic waters and “preparedness” at land to handle potential disasters, such as the SAR-system and preparedness of different actors, for example hospitals.
The increasing focus on energy efficient operation of vessels can be seen in both legislation and research. This paper focuses attention on the human factor influencing energy efficiency and explores the conditions for improving energy efficiency in working vessels taking situational awareness (SA) theory into consideration.
The study builds on two cases: an offshore supply vessel for the oil & gas industry and an installation vessel for wind turbines. The study used qualitative methods based on 49 interviews with seafarers and onshore employees from the vessels and shipping companies.
The study has identified that the energy efficiency of a ship is mainly influenced by legislation and the praxis formed on board. The results showed that the theory on SA is very a useful tool in explaining the factors affecting the energy efficiency of a vessel and the praxis.
The study has shown that obtaining a more energy efficient operation is complex and depends not only on the officer on board the ship. The improvement of energy efficiency is possible, but there is a need to understand the complexity of the issue and to involve both the crew and the entire system around the ship, and to obtain a shared perspective of energy efficient operation. Furthermore, in order to improve energy efficiency in shipping companies, there is a need to support the seafarers in gaining more skills for operating the ship more energy efficiently; to do this the right way there is a need to create an understanding of the system by the authorities, ship owners and charterers.
In 2018 the International Maritime Organization (IMO) agreed to cut the shipping sector’s overall CO2 output by 50% by 2050. One of the key methods in reaching this goal is to improve operations to limit fuel consumption. However, it is difficult to optimize speed for a complete liner shipping network as routes interact with each other, and several business constraints must be respected. This paper presents a unified model for speed optimization of a liner shipping network, satisfying numerous real-life business constraints. The speed optimization is in this research achieved by rescheduling the port call times of a network, thus, the network is not changed. The business constraints are among others related to transit times, port work shifts and emission control areas. Other restrictions are fixed times for canal crossing, speed restrictions in the piracy areas and desire for robust solutions. Vessel sharing agreements and other collaboration between companies must also be included. The modeling of the different restrictions is described in detail and tested on real-life data. The scientific contribution of this paper is threefold: We present a unified model for speed optimization together with numerous business constraints. We present a general framework for handling routes with different frequencies. Moreover, we present a bi-objective model for balancing robustness of schedules against fuel consumption. The tests show that the real-life requirements can be handled by mixed integer programming and that the model finds significant reductions of bunker consumption and cost for large-scale real-life instances.
Major liner shipping companies offer pre- and end-haulage as part of a door-to-door service, but unfortunately pre- and end-haulage is frequently one of the major bottlenecks in efficient liner shipping due to the lack of coordination between customers. In this paper, we apply techniques from vehicle routing problems to schedule pre- and end-haulage of containers, and perform tests on data from a major liner shipping company. The paper considers several versions of the scheduling problem such as having multiple empty container depots, and having to balance the empty container depot levels. The influence of the side constraints on the overall cost is analysed. By exploring the fact that the number of possible routes in the considered case is quite limited, we show that the model can be solved within a minute by use of column enumeration. Alternative constraints and problem formulations, such as balancing empty container storage level at depots, are considered. Computational results are reported on real-life data from a major liner shipping company.
In this paper speed optimization of an existing liner shipping network is solved by adjusting the port berth times. The objective is to minimize fuel consumption while retaining the customer transit times including the transhipment times. To avoid too many changes to the time table, changes of port berth times are only accepted if they lead to savings above a threshold value. Since the fuel consumption of a vessel is a non-linear convex function of the speed, it is approximated by a piecewise linear function. The developed model is solved using exact methods in less than two minutes for large instances. Computational experiments on real-size liner shipping networks are presented showing that fuels savings in the magnitude 2–10% can be obtained. The work has been carried out in collaboration with Maersk Line and the tests instances are confirmed to be representative of real-life networks.
In this paper speed optimization of an existing liner shipping network is solved by adjusting the port berth times. The objective is to minimize fuel consumption while retaining the customer transit times including the transhipment times. To avoid too many changes to the time table, changes of port berth times are only accepted if they lead to savings above a threshold value. Since the fuel consumption of a vessel is a non-linear convex function of the speed, it is approximated by a piecewise linear function. The developed model is solved using exact methods in less than two minutes for large instances. Computational experiments on real-size liner shipping networks are presented showing that fuels savings in the magnitude 2–10% can be obtained. The work has been carried out in collaboration with Maersk Line and the tests instances are confirmed to be representative of real-life networks.
The selection of alternative energy sources for shipping can effectively mitigate the problems of high energy consumption and severe environmental problems caused by shipping. However, it is usually difficult for decision makers to select the most sustainable alternative energy source for shipping among multiple alternatives due to the complexity of considering different aspects of performances and the lack of information. This study developed a novel multi-criteria decision-making method that combines Dempster-Shafer theory and a trapezoidal fuzzy analytic hierarchy process for alternative energy source selection under incomplete information conditions. According to the developed method, nuclear power has been recognized as the most sustainable alternative energy source for shipping, followed by liquefied natural gas (LNG) and wind power, and sensitivity analysis reveals that the weights of the criteria have significant on the sustainability sequence of the three alternative energy sources for shipping. The developed method can be popularized for selecting the most sustainable alternative energy source despite incomplete information.