Emerging inspection technologies, tools and platforms such as unmanned aerial vehicles (UAVs), remotely operated vehicles (ROVs), robotic crawlers, and wearable/handheld devices are creating actionable data to help enable more informed decision making and improve process efficiency during survey and inspection related activities. This paper will discuss ABS’ initiatives to further understand and help define the use of and the integration of these tools and technologies to support the evolution of the maritime industry's transition to digitalization.
ABS, in conjunction with technology equipment manufacturers and service providers, has been conducting feasibility trials to evaluate the pragmatic application and implementation of these technologies to support Class surveys. These trials have focused on areas such as the detection of coating breakdowns using high-definition optics to aid in close-up visual inspections (CVI) and leveraging mobile platforms (wearable and handheld devices) in conjunction with a collaborative software platform to execute survey activities virtually in real-time (connected) or near real-time (disconnected), capturing data as required by Class Rules.
In support of these trials, ABS is actively involved in a joint development project (JDP) with academia focusing on the realization of image recognition (artificial Intelligence [AI]) into the survey decision-making process. As part of this JDP, an AI software was developed incorporating thousands of damaged structural coating images. These images were used for the training, testing and evaluation of the software's image recognition capabilities.
This paper discusses the results of the feasibility trials and the next steps in the digital evolution for Classification Society activities. Potential applications include but are not limited to: condition-based/remote surveys, evaluation of maintenance programs, development of 3D models with 3D scanning/image data capture, documentation auditing, and corrosion mapping of steel plates.