SHIPPING
SAFETY

SAFETY ENHANCEMENTS

For an industry with casualty rates far exceeding those of comparable land-based industries, the critical question is: how can technology make shipping safer?

The spotlight is falling on technology that essentially removes humans from the equation. This includes remote operations and autonomy.  Fully automated ships are expected to enter the market by 2025, but in the near-term their use will be localized and limited owing to regulatory barriers.  This will not prevent more and more onboard systems becoming automated, with the crew reduced, and more decisions made from shore-based control centres.

Advances in real-time analytics are making possible new approaches to condition-based maintenance, as well as systems to map a ship’s condition status in relation to safety risk levels, allowing for dynamic adjustment of safety barriers in order to maintain minimum safety levels.

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Shipping will benefit from significant automation and remote operations developments in the offshore, aviation, aerospace, and automotive industries.

REMOTE OPERATIONS AND AUTONOMY

As sensor technologies and connectivity become more robust, remotely operated vessels, or even unmanned vessels, could become a reality.

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The use of sophisticated robotics and automation are now commonplace for many land-based industries, particularly manufacturing. In the past decade, we have seen the deployment of a number of unmanned autonomous and remotely operated vehicles, including unmanned aerial vehicles (UAVs), remotely operated underwater vehicles (ROVs), e.g., in the offshore sector servicing subsea installations, and significant steps towards development of driverless trucks and autonomous cars.

For shipping, remote operations require automation and high reliability of the engine and other integrated systems. In addition, advanced navigation systems and sophisticated algorithms to maintain a vessel’s course in changing sea and weather conditions, avoid collisions, and operate the ship efficiently, within specified safety parameters are prerequisites. Such systems rely on robust and secure communication via satellite and land-based systems. Onboard ship control and decision management systems can be adjusted to allow different levels of autonomy, but with further advances in these enabling technologies, we can imagine a completely autonomous ship that reports to shore-based operators only when human input is needed, or if emergency situations arise.

Shipping will benefit from developments in the offshore, aviation, aerospace, and automotive industries, which have been the drivers for advances in automation and remote operations. It is likely that shipping will first apply these technologies to instrumented machinery, and then gradually to vessel navigation. These solutions will increasingly rely on sensor technologies and computers to manage onboard systems from remote locations. As more onboard systems become automated, the crew will be reduced, and more decisions will be made from shore-based control centres.

These control centres will be responsible for operating vessels in congested sea-lanes, or in proximity to ports and terminals, and in emergency situations. To manage these tasks, control centres will be equipped with system simulators designed to select optimal routing procedures and interfaces with land-based supply chain networks. Onshore control centres will also be responsible for the asset integrity management of the ship and the possible downtime related to the failure of onboard equipment. As with many emerging technologies, the ability of the system to manage the interaction between man and machine will be critical. Such systems should provide accurate representations of risk and allow humans to take full control of vessels from a remote location when necessary.

The first conceptual prototypes of fully autonomous ships are here already, and many ship types will be delivered with remote/ autonomous operation capabilities towards 2025. Ports will also have automated systems for loading and unloading of cargo. However, although fully automated ships are expected to enter the market by 2025, regulatory barriers will hinder operation of autonomous ships in international waters, limiting its application to country waters and short sea shipping in the near future.

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REAL-TIME ANALYTICS FOR ASSET AND OPERATIONS MANAGEMENT

A new approach to Reliability, Availability, Maintainability, Safety (RAMS) and performability techniques…

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RAMS and performability techniques are used in many engineering fields to design and operate industrial assets to meet safety standards and to optimize overall system performance. While these techniques have proven value in system design, their application in operations has been lacking, although they offer a valuable approach for evaluating and comparing different scenarios from a risk-based perspective. However, in the next decade a new set of RAMS techniques that leverage the use of (near) real-time monitoring of operational parameters will increasingly be used by the shipping industry.

The most immediate expected benefits of these types of real-time analytics in supporting Asset and Operation Management will be to enable owners to reduce the number and frequency of inspections and repairs, and allow them to anticipate and replace damaged and worn parts with minimal resources and downtime. Similarly, these systems can map a ship’s condition status in relation to safety risk levels, allowing for dynamic adjustment of safety barriers in order to maintain minimum safety levels. With real-time access to a vessel’s current and future status, maintenance and operational personnel will have more accurate information on system capabilities, allowing for timely action to increase reliability, availability, safety, and efficiency.

In order to achieve the full potential of real-time analytics, further development of a number of technologies is necessary. The performance of real-time analytics is a function of predictive data that can indicate a developing failure. Therefore, smart sensor networks will be critical, as their ability to work together offers a detailed and accurate picture of various systems. In turn, real-time analytics will rely not only on how sensors are configured and linked, but also on the quality of ship-to-shore connectivity. Due to limited onboard storage and processing power, data will be analysed on board and/ or sent to shore, where it will be managed by increasingly sophisticated software tools and computing power. These tools will provide full-range analytics and visualization capabilities, and be seamlessly linked to onboard sensor and actuation devices via the Internet.

Advances in how organizations run their work processes following a data-driven approach will enable a dramatic shift in how the industry approaches asset management. As an example, this could involve moving from a scheduled maintenance approach, a process that is often driven by supplier recommendations, to condition-based maintenance, driven by the actual condition of onboard components and systems. This shift alone may require a new type of agreement between service providers and vessel owners and operators, perhaps through agreed levels of performance that are measurable at any time.

Data quality will represent a critical factor for the successful implementation of real-time analytics. The adoption of a data-driven philosophy for asset operations, such as reliability-centred maintenance, lifecycle asset management, and system engineering, will therefore become even more important in the maritime industry. Furthermore, new standards to verify the quality of real-time data streams will need to be developed. Similarly, the ability to trust data analytics and black box models will also need to be demonstrated, and new formal approaches for analytics verification must be developed. As more stakeholders will rely on information retrieved from several sources, it will be necessary to guarantee consistency across industry stakeholders’ data lakes and information models. Last, but not least, for a full industry-wide implementation, new standard and technological solutions for data governance and cybersecurity will be needed.

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