The PAULA consortium project, carried out from 1 January 2018 to 31 December 2022, focused on advancing additive manufacturing for aerospace components by integrating advanced process monitoring, defect detection, and repair strategies into a digital factory framework. The German company EOS led the main work package “AM‑Process 2.0” (HAP 1) and also supported the “Digital Factory 4.0” package (HAP 3). Within HAP 1, EOS executed sub‑packages AP 1.1 (multimonitoring of Ti‑6Al‑4V), AP 1.2 (online repair strategies), and AP 1.3 (location‑dependent parameters). In HAP 3, EOS contributed to AP 3.2 (digital process chain) and AP 3.3 (intelligent powder handling concepts), including the development of a digital twin and the design of a functional carrier for powder mixing, mixing, and sampling.

Technical results are centred on the correlation of optical‑temperature (OT) signals with process parameters. Experiments showed that both the illuminated area and the gas flow influence the OT signal, indicating that reduced flow leads to laser defocusing, a flatter but wider melt pool, and the formation of surface spheres that emit 900 nm radiation. This mechanism explains the intense point signals observed in OT data and the large‑area signals caused by scattered melt‑pool glow. The findings prompted the creation of a new sample series (Charge E) with enlarged area and a zig‑zag pattern on the outer surface, enabling precise layer‑by‑layer correlation between OT and computed tomography (CT) data even after plastic deformation. However, the new samples did not achieve the previously recorded 8 % total strain of the post‑processed round specimens, highlighting the trade‑off between surface area and mechanical performance.

EOS also developed a geometry‑dependent preprocessing algorithm (completed 30 September 2022) that adjusts laser parameters locally based on part geometry, thereby reducing defects. The algorithm was validated through metallographic examinations and integrated into the AM system software. Online repair strategies were defined and tested: a repair plan for induced defects was established (31 December 2021), and repair procedures were evaluated in the AM system (31 December 2022). The project produced a defect catalog (31 August 2019), a defect matrix (31 September 2019), and a list of specific material defects (30 September 2019). A process model was successfully developed (28 June 2019), and location‑dependent process parameters were implemented (31 March 2022).

In the digital factory domain, EOS contributed to the creation of a digital twin of the manufacturing workflow, including data serialization and integration of the laser‑based powder‑handling (LLI) process chain. The powder handling concept was extended to central powder supply, mixing, and traceability, with a functional carrier built and validated (AP 3.3.3.4). The project also explored x‑ray‑based powder analysis methods, identifying potential for new inspection techniques and developing process‑near, automatable testing methods.

Collaboration involved partners such as Liebherr Aerospace Lindenberg GmbH, which participated across all work packages, and IABG, which performed testing of the printed specimens. The consortium operated under the PAULA framework, with EOS as the lead for the AM‑Process 2.0 package and a key contributor to the Digital Factory 4.0 package. The project’s outcomes demonstrate a significant simplification of process development, enhanced reliability of aerospace components, and a move toward fully digital, data‑driven additive manufacturing workflows.