ABS, Google Cloud and SoftServe completed a pilot project applying artificial intelligence (AI) models to detect levels of corrosion and coating breakdown on ships and offshore structures.
The need to reduce operating expenditures continues to challenge owners and operators to improve efficiencies and enhance safety in maritime operations. As a key enablers, technologies advancements and remote inspection techniques will drive digital innovation with new approaches to class and asset management strategies.
ABS, Google Cloud and SoftServe completed a pilot project applying artificial intelligence (AI) models to detect and assess levels of 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. AI techniques could be further used to analyze images over time to understand corrosion and coating breakdown trends.
Benefits of AI-Driven Inspections on ships and offshore assets:
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 and segment defects such as coating failures, corrosion, and structural damage.
Our joint project with Google Cloud and SoftServe demonstrates how an AI-based image recognition tool enables deeper insight on asset condition using objective evaluations for reliable, informed decisions on asset condition monitoring.