A Methodology and Replication Roadmap for Designing Digital Twins in Additive Manufacturing
Year: 2025
Type: conference-paper
Abstract: The industrial adoption of Digital Twins (DTs) for optimizing Additive Manufacturing (AM) processes is frequently hindered by the lack of standardized, reproducible frameworks. This report addresses this gap by proposing a structured methodology for the design and deployment of an end-to-end Digital Twin (DT) architecture for Laser Powder Bed Fusion (LPBF) processes. The core of this methodology is the synergistic fusion of two components: a physics-based simulation model based on Finite Element Model (FEM) that captures the complex physics phenomena of the process, and an AI-powered model for in-situ visual defect detection during the printing process. The entire system is orchestrated by a microservices backbone utilizing containerization and a modular big-data architecture that is realized via an event-driven message broker that ensures seamless data communication and interoperability. The aim of this work is to provide a clear, actionable guide and a generalized replication roadmap as a blueprint for researchers and engineers to systematically develop and deploy sophisticated DT systems, thereby bridging the gap between theoretical concepts and industrial viability.
Authors: Meintanis, Ioannis, Mayr, Michael Mayr, Mallor, Carlos, Zambrano, Valentina, Lani, Sebastien, Wenger, Joe, Chasparis, Georgios
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W7130737060
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