Task-based error analysis of ship biofouling inspection processes using SHERPA

Biofouling on ship surface is a critical environmental and performance concern. Biofouling effective inspection is necessary to ensure the ships efficiency and regulatory compliance. These inspection procedures are subject to human error, though, which can compromise safety and effectiveness. This study describes a theoretical application of the Systematic Human Error Reduction and Prediction Approach (SHERPA) to analyze task-oriented human errors in ship biofouling inspections. Hierarchical task models for three operation conditions are developed: underwater hull inspection, confined-space ballast tank inspection, and Remotely Operated Vehicles (ROV)-based hull inspection. Possible human errors at each stage of a task are determined and categorized into SHERPA error types (action, checking, retrieval, communication, and selection). The assessment highlights the fact that checking errors and action/omission errors are common in all contexts and can lead to excessive biofouling or safety hazards missed detection. They are described as the possible ramifications of these mistakes – from not being able to find invasive species to dangerous mishaps on entering a sealed environment – and suggest strategies including improved training, uniform checklist use, and greater utilization of robotic or automated devices. The findings identify the advantages of proactively applying human reliability analysis approaches like SHERPA in maritime activities to enhance inspection safety and reliability.