Enhancing Unmanned Maritime Systems’ Efficiency with Digital Collaboration and Advanced Inspection Case Study

Importance of Management Systems in UMS Operations

The effectiveness of Unmanned Maritime Systems (UMS) heavily relies on management systems and tools. Effective management support systems are required to accomplish efficient forward operations. Since operators must make difficult decisions and undertake fieldwork, technology cannot replace them; supporting them is essential to the effectiveness of management support systems (Liu, 2022). However, sophisticated procedures are made possible by current tools and systems. The main problem is that their interface and capabilities may be highly time-consuming and expensive.

Limitations of Current Engineering Environments

Equipment manufacturers undertake much of the digital engineering used for major naval recording programs and other projects in their digital environments. The Navy lacks access to real-time design data since these settings are typically restricted. Equipment designers often operate in their digital environments, extract a limited amount of data, and then offer the results as contract artifacts (Martin et al., 2019). Due to this, it is challenging to find issues or gather comprehensive information. Engineers might not have all the information they require to thoroughly assess and impact the design of the artifacts themselves (Snowden & Wood, 2021).

Supporting Non-Technical Field Operators

Since field operators are the systems’ intended users, the UMS is made to support them. While field operators are specialists in operations, they are often not computer experts, and most operators struggle to create complex programs (Veitch et al., 2021). To address this issue, UMS can offer a visual editor and automated recording with an example operator as extra customization tools.

Benefits of Collaborative Digital Engineering

Work on designing management systems should be done in collaborative digital contexts. Users who work in a shared digital environment may see the same design data as the OEM, allowing them to spot possible problems immediately without waiting for eventual access to artifacts (Ghaderi, 2020). For instance, if a producer creates a brand-new side-scan sonar for UMS, assessment, analysis, and feedback may be given considerably more quickly throughout the project lifecycle.

Faster sonar integration, testing, and commissioning would result from this. By drawing in a larger community of technology providers, such as academics and unconventional defense contractors, the opening up of the digital engineering environment also fosters competition and innovation (Veal et al., 2019). Service providers have an earlier and more thorough awareness of what the business wants, thanks to a collaborative digital environment.

Role of Open Architectures in Tool Integration

Connecting to and utilizing the top new technologies from the vendor community is one of the essential elements in the quick adoption of management tools in UMS. Open architectures are necessary for any manufacturer to develop simple solutions to integrate with current systems (Zeng et al., 2021). Every day, digital engineering environments considerably aid the creation of these open architectures.

This strategy also considerably lessens reliance on the provider. The organization relies less on third parties for system changes when other suppliers have direct access to the design data (Costanzi et al., 2020). Additionally, the business is no longer constrained by proprietary methods owing to open architectures. This must be done with the proper degree of cybersecurity to thwart invasions, data manipulation, and theft of cutting-edge technological data.

Tools for Seabed and Wind Farm Inspection

Finally, it is necessary to consider tools and equipment for inspecting wind farms and the seabed. Multibeam sonars and AUVs (Autonomous Underwater Vehicles) can be used for seabed inspections. The former employs numerous sound waves to produce a three-dimensional picture of the seafloor (Stewart & Rasul, 2018). They are precise and can find even small objects on the seafloor (Stewart & Rasul, 2018).

AUVs are also pre-programmed to carry out particular tasks, including surveying the seafloor (Stewart & Rasul, 2018). For instance, A18-D is one of the possible AUVs that can be employed. It helps to perform deep water operations (“A18D / AUV / Autonomous underwater vehicle,” n.d.). It enables a 3D seabed survey to autonomously function at a depth of up to 3000m, a significant advantage (“A18D,” n.d.). For this reason, A18-D can be recommended as the equipment that might be helpful regarding the context and the mission.

Role of Uncrewed Surface Vehicles (USVs)

Uncrewed surface vehicles are also required for the existing tasks. For instance, Inspector 90/USV is a multipurpose drone platform designed to cope with various tasks (“Inspector 90,” n.d.). It has an autonomous mode and can operate in extremely harsh conditions, making it an attractive option (“Inspector 90 / USV / Unmanned Surface Vehicle,” n.d.).

The USV Inspector 90 can monitor the current state of the objects of interest, collect accurate and relevant data, and enhance the quality and accuracy of inspections. For this reason, this equipment is necessary for performing planned operations. Moreover, this USV will launch A18-D, the AUV above, to help boost performance.

Drones for Wind Turbine Inspection

Finally, the offshore wind turbine inspection can be performed using DJI’s Matrice 300 RTK. It is a drone designed to work in extreme weather conditions (“Wind turbine drone inspection: A guide,” n.d.). Furthermore, it is equipped with sensors to detect and report any defects in the construction. It has around 55 minutes of autonomous work, sufficient for the existing objectives (“Wind turbine drone inspection,” n.d.). In such a way, the drone can be an appropriate solution and complement the AUV and USV chosen above.

Moreover, UMS is quite good at inspecting wind farms, another field. Due to their versatility and ability to deliver high-quality images and data, drones have grown in popularity. Hybrid drones combine the benefits of quadcopters and fixed-wing drones (Ozana et al., 2023). They will be used since they can swiftly travel around an extensive area and conduct thorough inspections of wind turbines.

References

A18D / AUV / Autonomous underwater vehicle. (n.d.). ECA Group. Web.

Costanzi, R., Fanucci, D., Manzari, V., Micheli, M., M orlando, L., Terracciano, D. & Tesei, A. (2020). Interoperability among unmanned maritime vehicles: Review and first in-field experimentation. Frontiers in Robotics and AI, 7(1), 91. Web.

Ghaderi, H. (2020). Wider implications of autonomous vessels for the maritime industry: Mapping the unprecedented challenges. Academic Press.

Inspector 90 / USV / Unmanned surface vehicle. (n.d.). ECA Group. Web.

Ozana, S., Deb, D., Dalwadi, N. (2023). Adaptive hybrid control of quadrotor drones. Springer Nature Singapore.

Liu, H. (2022). Maritime and aviation law: A relational retrospect and prospect on unmanned ships and aircraft. In Regulation of Risk (pp. 471–499). Brill Nijhoff.

Martin, B., Tarraf, D. C., Whitmore, T. C., DeWeese, J., Kenney, C., Schmid, J., & DeLuca, P. (2019). Advancing autonomous systems: An analysis of current and future technology for unmanned maritime vehicles. Rand Corporation.

Snowden, E. M., & Wood, R. F. (2021). Maritime unmanned: From Global Hawk to Triton. Naval Institute Press.

Stewart, I. C., & Rasul, N. M. (2018). Geological setting, palaeoenvironment and archaeology of the Red Sea. Springer International Publishing.

Veal, R., Tsimplis, M., & Serdy, A. (2019). The legal status and operation of unmanned maritime vehicles. Ocean Development & International Law, 50(1), 23–48. Web.

Wind turbine drone inspection: A guide. (n.d.). FlyAbility. Web.

Veitch, E. A., Kaland, T., & Alsos, O. A. (2021). Design for resilient human-system interaction in autonomy: The case of a shore control center for unmanned ships. Proceedings of the Design Society, 1, 1023-1032. Web.

Zeng, C., Wang, J. B., Ding, C., Zhang, H., Lin, M., & Cheng, J. (2021). Joint optimization of trajectory and communication resource allocation for unmanned surface vehicle-enabled maritime wireless networks. IEEE Transactions on Communications, 69(12), 8100-8115. Web.