ABS: What is the future of cutting-edge maritime technology

The publication offers a glimpse into the future of advanced marine and offshore technologies, laying out a vision and timeline for key technological milestones on the journey to net-zero emissions and digitalization.

Artificial Intelligence

AI-derived autonomous systems could revolutionize the operation of vessels, especially during long transits. For example, a fleet of autonomous vessels could travel together in wake-reducing formations to increase energy efficiency. Traveling in a tight formation would be possible because connected AI systems can make decisions much faster than humans, thereby reducing risk.

Marinized robotics could take direction from human crewmembers and perform various high-risk tasks on board vessels. In extreme cases, a vessel or offshore asset could be fully autonomous and crewed entirely by robots that could replace parts using simulation-driven condition-based maintenance. The parts could be printed on demand using additive manufacturing machines.

No matter to what degree vessels and assets become autonomous, AI will likely play a pivotal role in the increasing digitalization of marine assets. From personnel communications to preventative maintenance, AI-based decision-making can be critical to broadly improving efficiency and reducing risk.

Digital Twins

THE GROWTH of connectivity infrastructure, sensor capabilities, cloud and edge computing power and AI systems are combining to drive the evolution of digital twins. As digital twins become more pervasive and reliable, they will play an ever-increasing role in maritime operations. The more variables a digital twin can account for, enabled by the various digitalization areas, the clearer the picture it will have of the real-world vessel or offshore asset.

Initially, real-time monitoring will support human-level decision-making, such as voyage optimization, fuel management, maintenance timing and decisions regarding remaining life. In time, digital twin systems are expected to reach self-learning and self-awareness benchmarks that will serve as essential foundations for fully autonomous functions.

As digital twin technology advances alongside improvements in connectivity, computational power and machine learning, twins will be capable of proactively seeking relevant data from potential inputs, such as sensors, drones or video systems. The twin will decide which inputs offer the most useful data for a given situation and continuously update its own model. An advanced twin could also gain enough awareness to model its own environment and account for possible outside variables during decision-making

Modeling and Simulation

While modeling and simulation offers a significant step in improving engineering and design processes, the rapid concurrent growth of maritime asset connectivity, cloud computing accessibility and edge computing power represent a leap forward beyond the design phase, bringing simulation-based decision-making to real-time situations.

Cloud technology allows the modeling and simulation to be performed at greater scale, complexity and speed. When fed with operational data, models can be fine-tuned to reflect real-life conditions. Modeling and simulation in the cloud serve as the central knowledge base for producing more advanced algorithms and models, which are then pushed to edge devices through reduced-order modeling. These reduced-order models, trained by the corresponding simulation models, can continuously analyze and optimize data from sensors on a system.

Autonomous Functions

THE IMPLEMENTATION of autonomous and remote-control functions offers several benefits to the industry. The technology has the potential to enhance safety by reducing human involvement in high-risk operations. Initially, autonomous technology could be used to assist in repetitive or dangerous tasks, freeing a seafarer to focus on the overall health and performance of the entire system.

As the technology matures and the industry gains more operational experience, more functions and tasks could be carried out autonomously. While the technology could lower operational expenses related to crew numbers, it could also help attract new talent to the maritime workforce as roles shift to monitoring and controlling systems remotely.

The expanding use of autonomous and remote control functions also has the potential to usher in a paradigm shift for vessel and offshore asset design. As human crew roles are altered or reduced, designs could be optimized to allocate more space and resources to the primary objective and less space to human habitability

Additive Manufacturing

AS AM CONTINUES to evolve, the process could revolutionize how the marine and offshore industries handle vessel or individual system repairs. By decentralizing part manufacturing, some repairs or part replacements could be achieved independent of supply chains and far from ports.

On-site or remote AM systems can provide additional value for users by printing parts nearer to the point of need, reducing the woes of traditional logistics and supply chain services. Cloud-based storage of digital part files, coupled with on demand manufacturing, can now replace large, physical inventories of complex parts. AM systems shift the focus to maintaining blockchain-secured part files on the cloud, managing an inventory of materials or feedstock and printing uniquely serial numbered parts just-in-time, improve efficiency and streamlining the repair process.

The 3D printing nature of AM systems also provides more flexibility in part design. Printing can be more cost-effective than traditional machining or casting of complex shapes while also providing greater control of material properties. When used with generative design, the benefits can be further enhanced to increase part performance, create lightweight parts, and provide solutions to part consolidation, whereby systems can now integrate multiple pieces into a single part during printing, further reducing assembly and installation costs.

explore more at abs’s report on maritime tech

Comments are closed.