Description:
This invention enables real-time, in-situ defect detection in metal additive manufacturing using Frequency Domain Thermoreflectance (FDTR). By analyzing thermal waves generated during printing, it detects and characterizes subsurface flaws as they form, ensuring higher part integrity and drastically reducing post-process inspection costs.
Background:
Metal additive manufacturing processes such as selective laser melting are critical for producing complex, high-performance parts, but they are prone to internal defects like voids and incomplete fusion that compromise reliability. Current inspection techniques such as CT scans and ultrasound are post-process, expensive, and lead to wasted parts once flaws are found. Existing in-situ monitoring methods lack depth resolution and cannot effectively detect subsurface defects in real time. A more sensitive, depth-selective, and non-invasive method is needed to identify and correct issues during the build process itself.
Technology Overview:
The invention employs Frequency Domain Thermoreflectance (FDTR) to provide in-situ, non-destructive monitoring during metal additive manufacturing. By modulating the power of the main laser to generate thermal waves, the system measures the phase lag and amplitude of surface temperature oscillations to infer subsurface thermal conductivity. This allows detection of defects such as microvoids, incomplete fusion, or powder anomalies several layers below the surface. The modulation frequency determines probing depth, enabling layer-by-layer analysis and real-time feedback or feed-forward control to optimize laser parameters and repair defects before they are buried.
Advantages:
• Real-time subsurface defect detection enables early intervention during the build process.
• Depth-selective thermal measurement provides layer-resolved insight into material integrity.
• Operates non-invasively using the existing manufacturing laser, minimizing added cost.
• Enhanced signal-to-noise ratio offers high sensitivity and reduced measurement error.
• Supports real-time feedback and feed-forward control to optimize print parameters.
• Detects powder bed anomalies before melting, improving material quality assurance.
• Significantly reduces reliance on costly post-process inspection and part rejection.
Applications:
• In-situ quality assurance for metal additive manufacturing.
• Feedstock powder verification and contamination detection.
• Adaptive process control for laser-based additive manufacturing.
• Quality monitoring for laser welding and electron beam fabrication.
• Advanced process development and thermal material characterization.
Intellectual Property Summary:
• United States US 11,654,635
• United States US 12,220,874
Stage of Development:
Prototype
Licensing Status:
This technology is available for licensing.
Licensing Potential:
Strong potential for additive manufacturing companies, aerospace and defense manufacturers, and industrial process developers seeking real-time quality assurance, reduced waste, and improved reliability in metal fabrication processes.
Additional Information:
Information available upon request.
Inventors:
Arad Azizi, Matthias Daeumer, Scott Schiffres, Jacob Simmons
Alternate NCS Title: Real-Time Subsurface Defect Detection for Metal Additive Manufacturing