Work

Applying AI in Supporting Additive Manufacturing Machine Maintenance

Year: 2025

Type: article

Abstract: Based on recent Artificial Intelligence advancements, this paper addresses implementing an AI-based maintenance strategy within a controlled production environment. The architecture employs real-time machine monitoring. Data is first processed locally for early fault detection and later cloud-based to support predictive maintenance functions. A Large Language Model trained with domain-specific knowledge provides operators with basic instructions to manage repetitive faults. The architecture is implemented and tested as a source of experimental data.

Source: Zeitschrift für wirtschaftlichen Fabrikbetrieb

DOI: 10.1515/zwf-2024-0169

Authors: Luiz F. C. S. Durão, Florian Schmitt, Júlio César R. A. Paz, Denilton Donizetti Silva, Eduardo Zancul, Eckhard Kirchner

Institutions: Universidade de São Paulo, Technische Universität Darmstadt

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,712