Technical advisory services firm American Bureau of Shipping (ABS), Google Cloud, and Ukrainian software company SoftServe have completed a pilot project using artificial intelligence models to detect corrosion and coating breakdown on ships and offshore structures. The project developed an image recognition tool using photos of hull structures to identify structural anomalies during visual inspections, with demonstrated accuracy.
“Digital innovation in AI will change how surveys and maintenance strategies are executed, driving more condition-based approaches to class and maintenance,” said ABS chairman, president and chief executive officer, Christopher Wiernicki in a statement. “We are building a future in which digital tools can remotely assess the condition of a ship or offshore unit, and automatically detect and measure coating breakdown and other structural issues, improving safety and reliability.”
ABS cites the potential benefits of of AI-driven inspections on ships and offshore assets as:
- Safety – reducing physical attendance and safety risk with alternative inspection methods and tools;
- Accuracy – deliver reliable, consistent assessments based on objective data analytics leveraging machine learning; and,
- Efficiency – expediting visual inspection evaluations that reduce the impact on operations.
Visual inspection data gathered by remote inspection technologies such as drones, crawlers, and remotely operated underwater vehicles further reduces costs and safety risks. Using machine learning (ML) technology, the inspection data can then be assessed automatically to identify defects.
“We are excited to team with Google Cloud and SoftServe to effectively apply AI technology to the marine and offshore industries,” said ABS deputy chief digital officer, Kashif Mahmood. “By combining our deep domain experience in offshore and marine structures with Google Cloud’s extensive knowledge of AI applications and SoftServe’s development capabilities, we were able to take this idea from concept to reality.”