Automation of non-destructive tetsing and information processing using AI

Context

During the construction of pipelines, stations, and other energy infrastructure, non-destructive testing (NDT) is essential to ensure structural integrity and the quality of welds, materials, and components. Most tests are currently manual, and results are recorded in heterogeneous formats, limiting traceability, analysis, and integration with digital asset models. This reduces quality control efficiency and slows decision-making during construction and operation.

Opportunity

Automating the capture, processing, and analysis of NDT data using AI and digital technologies can enable real-time digitalization and integration with BIM and asset management systems. This would improve quality control, reduce inspection time and costs, and ensure full traceability throughout the asset lifecycle.

What are we looking for

Solutions combining automation, computer vision, and AI to collect, interpret, and classify NDT results. Proposals should enable immediate digital capture, intelligent defect detection, and seamless integration with BIM and asset management systems. Key considerations include interoperability, detection of accuracy, and ease of implementation in industrial environments.

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