This thesis examines the impact of Industry 4.0 technologies, with a specific focus on data mining and machine learning, within the Italian fashion industry, particularly in the footwear and leather sectors. The main objective is to understand how digital innovation can enhance production efficiency, sustainability, and competitiveness while preserving the artisanal tradition that defines the Made in Italy identity. Through theoretical analysis and a review of 85 scientific articles, grouped into three main areas – production, design, and quality control – the research highlights how the integration of IoT, artificial intelligence, robotics, and predictive systems is reshaping production models in fashion. The most relevant applications concern process automation, digital design, product customization, and the adoption of Quality 4.0 practices. Findings reveal that digital transformation does not threaten craftsmanship; rather, it serves as a strategic driver for its enhancement, merging creativity, technology, and sustainability. The future of Italian fashion thus relies on a virtuous balance between tradition and innovation, aligned with the principles of Industry 5.0, where humans and technology collaborate to create a more efficient, ethical, and resilient production system.
La tesi analizza l’impatto delle tecnologie dell’Industria 4.0, con particolare attenzione a data mining e machine learning, nel settore della moda italiana, focalizzandosi sulle filiere delle calzature e delle pelli. L’obiettivo è comprendere come l’innovazione digitale possa migliorare l’efficienza produttiva, la sostenibilità e la competitività del Made in Italy, mantenendo al contempo la tradizione artigianale che lo contraddistingue. Attraverso l’analisi teorica e una revisione di 85 articoli scientifici, suddivisi in tre macroaree – produzione, progettazione e controllo qualità – emerge come l’integrazione di IoT, intelligenza artificiale, robotica e sistemi predittivi stia ridefinendo i modelli produttivi del settore. Le applicazioni più rilevanti riguardano l’automazione dei processi, la progettazione digitale, la personalizzazione dei prodotti e l’introduzione della Qualità 4.0. I risultati mostrano che la trasformazione digitale non rappresenta una minaccia per l’artigianato, ma una leva strategica di valorizzazione, capace di coniugare creatività, tecnologia e sostenibilità. Il futuro del fashion italiano passa dunque attraverso un equilibrio virtuoso tra tradizione e innovazione, in linea con i principi dell’Industria 5.0, dove l’uomo e la tecnologia collaborano per costruire un sistema produttivo più efficiente, etico e resiliente.
L'Innovazione Tecnologica nella Manifattura di Calzature e Pelletteria: Un'Analisi Critica delle Tecnologie Abilitanti e dei Benefici
MICUCCI, TOMMASO
2024/2025
Abstract
This thesis examines the impact of Industry 4.0 technologies, with a specific focus on data mining and machine learning, within the Italian fashion industry, particularly in the footwear and leather sectors. The main objective is to understand how digital innovation can enhance production efficiency, sustainability, and competitiveness while preserving the artisanal tradition that defines the Made in Italy identity. Through theoretical analysis and a review of 85 scientific articles, grouped into three main areas – production, design, and quality control – the research highlights how the integration of IoT, artificial intelligence, robotics, and predictive systems is reshaping production models in fashion. The most relevant applications concern process automation, digital design, product customization, and the adoption of Quality 4.0 practices. Findings reveal that digital transformation does not threaten craftsmanship; rather, it serves as a strategic driver for its enhancement, merging creativity, technology, and sustainability. The future of Italian fashion thus relies on a virtuous balance between tradition and innovation, aligned with the principles of Industry 5.0, where humans and technology collaborate to create a more efficient, ethical, and resilient production system.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12075/23528