From electronic certificates, machine learning tools and drone surveys to the launch of a new industry data platform, DNV GL is embracing digitalization to enhance class services and improve communication with customers.
Shipping has undergone a remarkable transformation over the past few decades. Advances in technology, new materials and new insights into the design, construction and operation of vessels mean that they are more complex, more efficient and larger than ever before. While the use of ship-to-shore data and greater digitalization is improving operations and performance, reducing maintenance and operational costs, as well as enhancing safety. DNV GL has been at the heart of this transformation for more than 150 years.
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“For us, digitalization is not an end in itself, we see it as another means to fulfil our main purpose: ensuring safe operations at sea and protecting life, property and the environment,” says Knut Ørbeck- Nilssen, CEO of DNV GL – Maritime. “The role of class in ensuring the integrity of the vessel and safety of the crew will continue, but the way surveys are conducted may change significantly. Furthermore, digitalization enables us to become more efficient and improve our level of service,” he adds.
Single access point to all digital services
When our customers interact with classification, they want this to be as simple and efficient as possible. To help, we launched My DNV GL. This is a single access point for all of our digital services, with many applications designed to support our customers in areas such as port state control inspections (see paragraph PSC PLANNER), cybersecurity preparedness and regulatory compliance. To provide worldwide access to class documentation, DNV GL customers will soon be able to use electronic certificates. This means their documentation never gets lost, is always up to date and is accessible from any device (see paragraph ELECTRONIC CERTIFICATES).
“And with the introduction of our new simple survey booking tool towards the end of the year, we will also start using intelligent software agents to help customers find the best time and place to book a survey,” adds Ørbeck-Nilssen (see paragraph SMART SURVEY BOOKING). When customers have questions or run into a problem, they can get in touch with one of DNV GL’s technical experts through the DATE service. “This service has been a great success and now, to make it even better, we have introduced a tool that uses machine learning to automatically match our customers with the right expert for their question,” says Ørbeck- Nilssen. The tool has already analysed more than 200,000 requests and is continuing to learn (see paragraph MACHINE LEARNING). “Soon, we expect it will be able to answer simple questions on its own,” he adds.
Modern survey methods
One of the most important ways we work to keep shipping safe is by conducting annual surveys on all of the vessels in our class. So far this has meant a surveyor needs to crawl and climb to reach every remote corner inside a ship. But new technologies are changing even how DNV GL does this. Already, surveyors have used camera-equipped drones to visually inspect large cargo holds and tanks. Using a drone opens up a lot of new possibilities. “In the future, drones could eventually be piloted remotely or even autonomously, meaning the surveyors could work from their desk thousands of miles away from the ship and inspect the vessel in virtual reality (VR),” says Ørbeck-Nilssen.
For our customers, the successful delivery and regular inspections of a vessel as well as interactions with class are just one part of a bigger puzzle. The other big questions are: How does the design perform in daily operations? Is the engine achieving optimal fuel consumption? And are the safety systems reliable at sea?
Turning data into business intelligence
Today, advanced sensor technology and powerful satellite connections have opened up a new range of possibilities for understanding more about vessels and their operation. Everything on board, from the engines, the propeller and the safety systems to the containers themselves can be fitted with smart sensors to monitor performance and catch irregularities early on. This information can then be fed into the DNV GL performance management platform ECO Insight, which can check the quality of the data before analysing it. “This lets operators benchmark their vessels against the world fleet, turning their data into valuable business intelligence,” says Ørbeck-Nilssen.
DNV GL can also take this data and combine it with information from inspections and a 3D model of the ship to build a “digital twin” – a digital copy of a real object, modelled to exactly represent its properties. DNV GL experts can use the digital twin to find the best design, see how the networks on board respond to cyber attacks, test measures to improve performance and identify when vital equipment needs maintenance or replacement – throughout the lifetime of the vessel. Ultimately, digital systems could end up controlling ships entirely – without the need for a human crew. An autonomous ship would use advanced navigation software and smart control systems to follow a course, avoid obstacles and safely deliver its cargo. Of course, if the industry is going to rely on these systems, they need to be as reliable and secure as possible. With software-in-the-loop testing and a digital twin, DNV GL can check and correct weaknesses in the system.
The broader view
These new digital solutions are not confined to the world of shipping. “It doesn’t matter where you look in DNV GL, our customers are using data analytics to improve safety, gain efficiencies, reduce environmental impacts and evolve new business models,” says Remi Eriksen, Group President & CEO at DNV GL. “On drill ships, we’ve seen how sensor data and advanced data analytics are helping our customers save millions of dollars in downtime. In the renewables industry, power cybernetics is helping to integrate variable wind and solar power safely into the grid, while machine learning helps oil and gas pipelines become safer by drawing insights from previously unconnected data sets,” he explains.
A new industry data platform
All of these advances need many different project partners working together with accurate, reliable and secure data from multiple sources. And as decision-making and business models become more data-driven, trustworthy data becomes even more valuable. “Without trust in this data, truly cooperative projects cannot deliver the progress we hope for. At DNV GL, we have always been trusted with data, trusted to give an independent expert view and trusted to connect different industry players. That is why we have created a place for industry experts and data to come together securely: our new, multi-sided industry data platform called Veracity,” says Remi Eriksen.
Veracity is a meeting ground for co-innovation and co-creation between multiple industry stakeholders, playing a key role by assuring data quality, data security and access. It is an open platform for qualifying, unlocking and improving data from sensors and other sources. Customers stay in control in this secure environment, and can trust domain experts, algorithms and analytics to combine and transform their data into real value. And Veracity could be a key component of a class-concept built around sensor-based data: securing and assuring data for use in the condition assessment of the hull and critical components.
“The digital transformation cannot be realized with one solution or one service. It is a journey,” says Knut Ørbeck-Nilssen. “By working together with us, customers can capitalize on these new opportunities – to make the world safer, smarter and greener.”
VERACITY
The Veracity industry data platform is designed to help companies improve data quality and manage the ownership, security, sharing and use of data. One area where the maritime industry could benefit from the Veracity data platform in the future could be allowing DNV GL’s maritime customers to document compliance of main on-board machinery and systems through predictive analytics, removing the need for calendar-based inspections. In one of DNV GL’s first pilot projects a drilling operator embarked on a project to explore predictive analytics with a components vendor and an analytics services company. Working with DNV GL to see if this approach could gain class approval, an analysis of the data revealed severe quality issues that none of the partners were previously aware of. Once the data was quality-assured, machine learning algorithms could be applied to the data with success. A key learning from the project was that it demonstrated the need for continuous data management and quality assurance to reap the benefits of a data-driven approach.
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ELECTRONIC CERTIFICATES
Starting in September 2017, DNV GL will introduce electronic certificates for the class and statutory regimes. Accessible from anywhere in the world, electronic certificates bring many advantages to both DNV GL and its customers. By eliminating paper handling, they reduce the administrative burden on all stakeholders. A validation solution ensures that electronic certificates are just as safe as paper. In addition, electronic certificates are easy and convenient to share. Compiling them in My DNV GL provides acomprehensive overviewof key ship data that cannot get lost and is just a few clicks away. For DNV GL, electronic certificates help make processes more efficient, and they provide experts with easy access to certificates when they need to check up on something, be it during a survey or at a customer meeting. Electronic certificates will be rolled out gradually and will be implemented with avessel’s next annual survey.
More on Electronic Class and Statutory Certificates
SMART SURVEY BOOKING
The Smart Survey Booking solution will be launched towards the end of the year. It simplifies survey booking, fitting inspections into the customers’ schedule while saving time and costs. This is how it works:
Customers are notified about the best time to order surveys and audits and notified shortly before the due date of the next survey.
The tool proposes the scope of the survey and estimate of how long a survey of this scope would take.
A list of approved service suppliers in each port is provided, and helps operators to find out whether an in-water survey can be performed in a specific port.
The solution offers up-front cost estimates for travel and overtime charges for survey combinations during any given port stays based on ETA (estimated time of arrival) and ETD (estimated time of departure).
Based on automatically calculated cost estimates and the possible scope of the inspection in each port, customers can compare and benchmark various port-stay options.
Once the date is set, relevant survey preparation notes are attached to the booking confirmation to help the operator prepare for the inspection.
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PSC PLANNER
Launched in April 2017, the Port State Control (PSC) Planner is one of the most recent additions to the My DNV GL customer portal. Designed to help shipowners, managers and operators increase operational efficiency, the PSC Planner gives an overview of vessel or fleetwide PSC performance, which can then be benchmarked against the IACS-classed worldfleet. The tool also assists the crew on board by highlighting specific areas to focus on when preparing for the next inspection.
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MACHINE LEARNING
DNV GL has introduced a new machine learning tool to the Direct Access to Technical Experts service (DATE). When customers have a query, this service connects them to one of more than 400 technical experts located at five support hubs worldwide. DATE was used more than 20,000 times in 2016, with over 97 per cent of requests being completed within the customer’s deadline. Matching every request with the right expert as quickly as possible is essential. DNV GL’s new machine learning tool searches for key words in a customer enquiry to create a profile for each request. Then it sends the request to an appropriate expert. After a piloting phase the machine learning tool went live for all DATE requests at the beginning of May 2017. It has viewed about 200,000 requests already and is learning continually. In the future, it could even answer simple questions on its own.
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