Schiffstechnik | Ship Technology »We are at the cutting edge of developments« Artificial Intelligence, Digital Twins, data-driven ship design, drones – this year’s conference on Computer Applications and Information Technology in the Maritime Industries, COMPIT 2018, brought together the forerunners of innovative thinking in the maritime sector, reports Hans Payer More than 70 attendees from many European countries, USA, Canada and Asia got together in the Castello di Pavone in the Piemont region, Italy, to discuss 45 papers on future developments in shipping and shipbuilding with today’s and future technological innovations. Artificial intelligence, artificial neural nets, knowledge-based systems, Digital Twins, Virtual and Augmented Reality, all the way to the autonomous ship were addressed. Artificial Intelligence Mankind has long been fascinated by Artificial Intelligence (AI). In the beginning it was Science Fiction films where man built smart robots which fulfilled various tasks autonomously. Several films developed stories of successful Artificial Intelligence as well as cases where things went wrong and mankind lost control. As we make rapid progress with the increasing digitalization of our world, the importance of ethical principles in dealing with Artificial Intelligence is becoming obvious. Several of the larger companies working on AI, such as Google or Amazon, take initiatives today to assure ethical conduct always keeping the technology under control. Volker Bertram, organizer of the Conference, presented the paper Demystify Artificial Intelligence for maritime applications, explaining the key technologies used today. The principles of machine learning are described going from simple examples to more complex tasks. Starting from data sets from concrete processes we frequently try to find regularities and patterns which can be used for extrapolation to new designs. The human brain is very good at trend spotting and pattern recognition. Machine learning tries to mimic this ability and take it further. The most popular technique in machine learning and AI is Artificial Neural Networks (ANN) which allows mapping of multi-dimensional input/output data sets for an arbitrary number of input and output variables. An ANN structure may consist of several layers, with large numbers of nodes on each level, somewhat comparable to the brain. ANNs are convincing, nevertheless they do have limitations. They cannot predict the unpredictable, such as random events, or chaotic behavior, e.g. crash-stop maneuvers of ships. Machine learning needs vast amounts of data points. Real-world problems in shipping for instance, depending on Photo: Payer 64 HANSA International Maritime Journal – 155. Jahrgang – 2018 – Nr. 7
Schiffstechnik | Ship Technology many factors, operational as well as ambient conditions, may easily lead to billions of data points required to train a neural network. This is a formidable job, even by today’s standards. ANNs have been successfully used in system identification, deriving design formulas, to create response surfaces for interpolation of simulation results, automatic ship type identification, economic predictions etc. The ambition is to extend automation on board through artificial intelligence further to a degree where the ship will eventually operate by itself, the autonomous ship. The operation of all components as well as the complete ship system are automatically controlled by mechanical and electronic devices that take the place of humans in observation, decision making and reaction. Technically we have come a long way. Nevertheless we cannot completely replace the human being. Jukka Merenluoto from DIMEC, Finland said: »The automation of ships will continue. We’ll see autonomous ships, but they will not be unmanned.« The Digital Twin journey With today’s possibilities we can create a complete and accurate digital representation of a ship, maintained during the construction period and throughout the operational life of the vessel. Such a Digital Twin is the platform of platforms. It should contain all relevant information about the vessel and should be contained within a single software platform, which is flexible enough to communicate with other related platforms. Digital Twins have been in use successfully in several industries. Rolls-Royce for instance offers Digital Twins for airplane jet engines or thrusters for speed boats, usually maintaining the models in their data centers. Maintenance and replacement requirements are determined with the Digital Twin on the basis of operational data from the actual unit and prepared at suitable service centers worldwide. NASA confirms a Digital Twin for a spacecraft, manned or unmanned, as ultra-realistic. Christian Cabos, DNV GL, proposes to test a software update on the Digital Twin and only if it is successful to roll it out for the real object. Setting up a comprehensive data model for a ship is quite elaborate as ships are very complex and mostly unique or from small series. Thus, Digital Twins are still rare for ships. For Denis Morais from SSI, Victoria, Canada, the benefits of a Digital Twin in shipping are real, (see HANSA 5/2018). The creation of a Digital Twin of a ship will start from the geometric data and attributes coming from the engineering CAD tools, but include much more to finally represent the as-built condition of the vessel. The twin will always be up-to-date with the real ship, not only for structure and machinery, it must also have links to class approvals, simulations and calculations as well as paint information, to mention only a few. Ultimately, the system could include the use of »Internet of Things-sensors« to automatically keep the physical ship and its digital representation synchronous at all times. The modern shipyard will benefit largely from having a Digital Twin available during construction of a ship and afterwards. But the main benefit will go to the ship owner/operator interested in higher safety and savings in operation over the lifecycle of his vessel. Several containership operators, for instance Maersk and Hapag-Lloyd, have signed up for DNV GL’s Digital Twin software to manage a virtual model of each of their vessels worldwide in the cloud. Ships result from multi-tier collaborations between designers and manufacturers. With new »outcome-based« business models, shared responsibility for the integrity and performance of components and systems during operation is emerging. Therefore multi-tier Digital Twins will emerge in the industry. This means that condition data, asset representation, and behavioral models will be shared. Because of obvious interests for safeguarding intellectual property, access rights and change management will be important aspects of a system implementing shared Digital Twins. Data-driven ship design The computational power – speed and capacity – has been growing dramatically in recent years, bringing new possibilities for data collection and knowledge extraction from data never seen before. Good decision making comes from good data via DIKW, Data, Information, Knowledge and Wisdom hierarchy; KDD, Knowledge Discovery and Data mining; and DDD, Data-Driven Decision making. The expanded computational possibilities make new design methods feasible. Henrique Gaspar from Brasil, professor at NTNU, Alesund, describes how efficient data-driven decision making is connected to a combination of intuition and analysis of data. Traditional methods of knowledge extraction and visualisation of information from data such as regression analysis and other fitting models are today augmented by methods such as clustering and text mining. In data-driven ship design data is both, studied topdown from regressions, previous designs and parametric studies based on existing solutions, as well as bottom-up, where it is connected to specific key elements and subsystems that directly affect the mission of the specific ship design. Data-driven ship design aims to integrate product and process content according to modern DevOps practices, such as versioning, tracking, monitoring, testing, tuning and feedback. An open and collaborative ship design library is briefly introduced as an initiative aiming to Digital Twin of a main engine’s cylinder station Source: DNV GL HANSA International Maritime Journal – 155. Jahrgang – 2018 – Nr. 7 65
