This thesis addresses inefficiency and limited operational visibility in the production lines of small and medium‑sized enterprises (SMEs). It proposes integrating Artificial Intelligence, specifically Large Language Models (LLMs), with data analytics to convert shop‑floor data streams into a practical, intuitive dashboard for production managers. The work demonstrates how these tools facilitate the early detection of issues on the lines and generate automatic recommendations that enhance overall production efficiency.
La tesi affronta l’inefficienza e la scarsa visibilità operativa nelle linee di produzione delle piccole e medie imprese (PMI). Propone l’integrazione di Intelligenza Artificiale, in particolare dei Large Language Models (LLM), con l’analisi dei dati per trasformare i flussi provenienti dagli impianti in una dashboard pratica e intuitiva a supporto dei responsabili di produzione. L’elaborato mostra come tali strumenti facilitino l’individuazione dei problemi nelle linee e forniscano raccomandazioni automatiche per incrementare l’efficienza complessiva.
Integrazione di Large Language Models e Data Analytics per l’Ottimizzazione delle Linee di Produzione Industriali
FANTINATO, MICHAEL
2024/2025
Abstract
This thesis addresses inefficiency and limited operational visibility in the production lines of small and medium‑sized enterprises (SMEs). It proposes integrating Artificial Intelligence, specifically Large Language Models (LLMs), with data analytics to convert shop‑floor data streams into a practical, intuitive dashboard for production managers. The work demonstrates how these tools facilitate the early detection of issues on the lines and generate automatic recommendations that enhance overall production efficiency.| File | Dimensione | Formato | |
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Fantinato_Michael.pdf
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3.65 MB | Adobe PDF |
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https://hdl.handle.net/20.500.12608/89986