InSensa: In-process sensors and adaptive control systems for additive manufacturing

The InSensa project aims to detect and prevent errors in powder bed-based laser additive manufacturing (PBF-LB/M) by integrating advanced sensor and control technologies. An error catalog defines detectable process errors, prioritized by AM user experiences. Demonstrator components are created to provoke these prioritized errors. Sensors are positioned coaxially for direct melt pool observation and off-axis for broader component monitoring. New technologies include a high-speed pyrometer (100 kHz), a customized thermographic camera, and an OCT topography sensor optimized for PBF-LB/M.

A 3D camera system is prototypically tested for capturing reflective surfaces. Multimodal process monitoring is successfully demonstrated. A database for process and error documentation is prototyped, supporting automatic error detection evaluations. Real-time laser power control using pyrometer feedback achieves a response time of 50 µs, effective for practical scan speeds, improving surface roughness by 20% in tests. Foundational work for future automatic error detection is established.

Grantor:

• BMBF

Partners

• Aconity
• Materialise
• Precitec
• ISRA Vision
• Fraunhofer Insitute IAPT
• University Bremen
• C.F.K. CNC-Fertigungstechnik Kriftel

Project Date:

• 2017 -2020

Link:

• https://publica.fraunhofer.de/entities/publication/847d94bf-a650-44ed-966d-c91f56e6ff3b