Open Access

AbstractPowder Bed Fusion with Laser Beam of Metals (PBF-LB/M) has gained more industrial relevance and already demonstrated applications at a small series scale. However, its widespread adoption in various use cases faces challenges due to the absence of interfaces to established Manufacturing Execution Systems (MES) that support customers in the predominantly data-driven quality assurance. Current state-of-the-art PBF-LB/M machines utilize communication architectures, such as OPC Unified Architecture (OPC UA), Message Queuing Telemetry Transport (MQTT) and Representational State Transfer Application Programming Interface (REST API). In the context of the Reference Architecture Model Industry 4.0 (RAMI 4.0) and the Internet of Things (IoT), the assets, particularly the physical PBF-LB/M machines, already have an integration layer implemented to communicate data such as process states or sensor values. Missing is an MES component acting as a communication and information layer. To address this gap, the proposed Extract Transform Load (ETL) pipeline aims to extract relevant data from the fabrication of each build cycle down to the level of scan vectors and additionally to register process signals. The suggested data schema for archiving each build cycle adheres to all terms defined by ISO/TC 261—Additive Manufacturing (AM). In relation to the measurement frequency, all data are reorganized into entities, such as the AM machine, build cycle, part, layer, and scan vector. These scan vectors are stored in a runtime-independent format, including all metadata, to be valid and traceable. The resulting machine log represents a comprehensive documentation of each build cycle, enabling data-driven quality assurance at process level.

Data-driven quality assurance and reproducibility are critical for advancing the industrial maturity of Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M). This study addresses the extraneous variance in scan vectors that arises even for identical cross sections of nominally identical components but located at different positions on the build platform. This inherent variance, common across most PBF-LB/M machines, is caused by scan vector computation relative to the machine coordinate origin and subsequent projection of the resulting pattern onto individual component cross sections. In this work, scan vectors are computed still following conventional slicing, but relative to the workpiece origin of each component, using an EOS M 300-4. This digital preprocessing approach homogenizes fabrication conditions, ensuring that anomalies, such as scan vector overlaps, occur consistently across identical components. The impact during fabrication is assessed through powder bed imaging, melt pool monitoring, and operational data from the multilaser PBF-LB/M machine. Components are manufactured from AlSi10Mg for each scan vector computation origin and subsequently qualified using x-ray computed tomography, optical coordinate measurement, and optical surface measurement. A comprehensive evaluation is conducted, comparing the results in terms of component density, geometric accuracy, and surface roughness to those obtained using conventional preprocessing. Based on these findings, practical recommendations are provided, focusing on achieved quality criteria to identify potential drawbacks, while also considering the life cycle analysis of fabrication. Finally, the study emphasizes the significance of consistent scan vector provisioning for identical components placed at different build platform positions, assuming no roll or pitch during nesting.