Digital Services

Increasing demands for quality assurance, traceability, and automation are fundamentally transforming industrial nondestructive testing. Inspection data should no longer be viewed in isolation but rather integrated as a valuable data resource into digital production, quality, and maintenance processes.

At the same time, nondestructive testing generates large volumes of heterogeneous information—ranging from sensor signals and test results to device data, test parameters, and reports, as well as standards, process data, and digital twins. To make this data efficiently usable, standardized interfaces, intelligent evaluation methods, and secure AI-based assistance systems are required.

Consequently, networked, interoperable, and semi-autonomous inspection systems are becoming increasingly important, particularly in safety- and quality-critical industries such as automotive, aerospace, rail, energy, and industrial production. They make it possible to evaluate inspection results more quickly, better validate quality decisions, and seamlessly integrate inspection processes into digital value chains.

Our Solution: Connected Inspection and Data Systems for NDE 4.0

Fraunhofer IZFP supports companies in advancing traditional nondestructive testing into digital, intelligent, and connected inspection ecosystems.

By combining NDT expertise, digital twins, standardized communication protocols, data management, and AI-supported analysis, inspection data is captured, structured, and evaluated in real time, making it usable for production, quality, and maintenance decisions.

Our solutions specifically address

the digital integration of inspection systems with production and enterprise IT,
the use of Asset Administration Shells to map digital twins,
standardized communication via interfaces such as OPC UA and MQTT
structured archiving, exchange, and traceability of inspection data, e.g., via DICONDE,
automatic defect detection through AI-supported analysis methods,
the visualization of inspection and process data in dashboards, and
the use of domain-specific LLM assistants for inspection, training, documentation, and knowledge management.

We develop IIoT-enabled inspection architectures that connect NDE hardware, sensor data, digital twins, and enterprise systems into end-to-end digital process chains. Standardized information models enable the consistent description and further processing of complex inspection data, such as that from micromagnetic, acoustic, ultrasonic, or imaging methods. In addition, we are developing secure, local AI and LLM systems that provide support for procedure selection, result interpretation, report generation, training, and knowledge access. The focus is on traceability, data protection, validation, and human oversight, ensuring that AI-supported results can be reliably integrated into inspection and quality processes.

Your Benefits

Better utilization of inspection data for quality assurance, production, and maintenance
End-to-end traceability throughout the product and equipment lifecycle
Seamless integration of inspection systems into Industry 4.0 and IIoT environments
Standardized data structures for exchange, archiving, and further processing
Automated defect detection and reduced manual evaluation effort
Intuitive interaction with inspection data, devices, standards, and documentation
Secure, local, and domain-specific AI solutions
Greater transparency, efficiency, and decision-making quality in NDE processes

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