Dual scan head approach for in-situ defect detection in laser powder bed fusion of metal

Laser powder bed fusion of metal has emerged as a key technology in additive manufacturing, enabling the production of intricate, high-performance metal components directly from digital designs. However, challenges such as dimensional inaccuracies and internal defects continue to hinder its broader industrial application. Addressing these limitations requires enhanced process monitoring and control strategies. This study introduces an innovative process monitoring system, designed to improve defect detection and process control. By employing a dual scan head configuration, enabling precise and independent path planning of the laser and the measurement field of an infrared camera, the Synchronized Path Infrared Thermography (SPIT) setup utilizes the principle of exploiting differences in cooling behavior to identify subsurface defects. Pre-printed samples with embedded cylindrical defects ranging from 300 to 1000 μm in diameter are used and an additional layer of powder is applied and fused within the experimental setup. The volumetric energy density and scanning speed are varied to analyze their influence on process monitoring reliability. The sensor scan head is synchronized with the laser scan head’s movements, while the infrared camera captures thermal radiation at 1904 fps. The results demonstrate the system’s capability to detect subsurface defects with a minimum size of 356 µm.

Authors

Institutions

Publication Details

Journal
Progress in Additive Manufacturing
Published
2026-03-16
DOI
https://doi.org/10.1007/s40964-026-01568-0
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dual scan head approach for in-situ defect detection in laser powder bed fusion of metal

Jürgen Hartmann, Dennis Höfflin, Christian Sauer, Andreas Schiffler et al.
Progress in Additive Manufacturing
Additive Manufacturing Materials and Processes
article

Dual scan head approach for in-situ defect detection in laser powder bed fusion of metal

Jürgen Hartmann, Dennis Höfflin, Christian Sauer, Andreas Schiffler, Alexander Versch
article en

Abstract

Laser powder bed fusion of metal has emerged as a key technology in additive manufacturing, enabling the production of intricate, high-performance metal components directly from digital designs. However, challenges such as dimensional inaccuracies and internal defects continue to hinder its broader industrial application. Addressing these limitations requires enhanced process monitoring and control strategies. This study introduces an innovative process monitoring system, designed to improve defect detection and process control. By employing a dual scan head configuration, enabling precise and independent path planning of the laser and the measurement field of an infrared camera, the Synchronized Path Infrared Thermography (SPIT) setup utilizes the principle of exploiting differences in cooling behavior to identify subsurface defects. Pre-printed samples with embedded cylindrical defects ranging from 300 to 1000 μm in diameter are used and an additional layer of powder is applied and fused within the experimental setup. The volumetric energy density and scanning speed are varied to analyze their influence on process monitoring reliability. The sensor scan head is synchronized with the laser scan head’s movements, while the infrared camera captures thermal radiation at 1904 fps. The results demonstrate the system’s capability to detect subsurface defects with a minimum size of 356 µm.

Progress in Additive Manufacturing
Technical University of Applied Sciences Würzburg-Schweinfurt (DE), Schneider Electric (Germany) (DE), Bavarian Center for Applied Energy Research (DE)
Affordable and clean energy
Openalex Percentile: Top 21%
Additive Manufacturing Materials and Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.