Fabio De Felice

Digital Twin technology is increasingly recognized as a strategic enabler of Industry 4.0, combining efficiency, resilience, and sustainability. By replicating physical assets and processes in dynamic digital environments, Digital Twins enable real-time monitoring, predictive maintenance, and energy optimization. This chapter provides a scenario-based analysis on digital twin. Evidence from existing implementations shows measurable sustainability outcomes: energy savings of 15–30%, CO₂ emission reductions up to 25%, and maintenance cost decreases between 20 and 30%. These benefits are most evident in energy-intensive and complex industries, where Digital Twins have already demonstrated tangible impacts on operational performance and ecological transition. At the same time, barriers such as high initial costs, lack of standardization, and cybersecurity risks remain critical challenges. The chapter emphasizes the role of Digital Twins not only as technological tools but as catalysts of systemic transformation toward greener, more resilient industrial and urban models.

The evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0.

In the era of Industry 4.0, the integration of intelligent systems with human elements presents both opportunities and challenges. This study explores this interplay through the application of an industrial engineering technique to a real process issue, demonstrating originality in problem selection and solution tools, as well as the relevance of the results. An operational framework is proposed to drive digital transformation in manufacturing by balancing automated systems efficiency with the complexity of human activities, which include decision-making flexibility, adaptability, tacit knowledge and collaborative interaction. It examines Industry 4.0 domains to find solutions that use smart technology while enhancing human experience. A key element is the use of discrete-event simulation to create a digital replica of the existing process. This enabled a detailed analysis and the development of innovative, validated approaches through what-if scenarios. The implemented solutions led to a significant annual increase in productivity, the result of an overall improvement in process efficiency, which was also achieved through the identification and resolution of key process bottlenecks, confirming the method’s effectiveness. The research offers a scalable model for various sectors, emphasizing the need to integrate human aspects into intelligent systems. It highlights how technological progress should enrich, not overshadow, human contribution, contributing to a deeper understanding of digital transformation in intelligent manufacturing and service systems, where technology and humanity evolve together.

The textile industry is among the most environmentally impactful sectors, underscoring the urgency of transitioning to circular economy models. This study examines the development of a digital-driven circular ecosystem for the Italian textile sector, leveraging insights from a comprehensive survey on sustainable practices. By analyzing material flows and identifying inefficiencies, the research proposes an integrated framework to enhance sustainability across the supply chain. Key indicators are established to monitor environmental, economic, and social impacts, offering a practical tool for decision-making. The findings reveal how scenario-based approaches and targeted strategies can empower Italian textile companies to adopt circular practices effectively. This work lays the groundwork for a robust ecological transition, fostering both environmental sustainability and competitive advantage in the global market.

Among the causes of the low success rate of the projects (around 35% of the total) is the low level of maturity of the technologies available for the management of the projects themselves. However, today many researchers, startups and innovative companies are starting to apply artificial intelligence (AI), machine learning and other advanced technologies to the field of project management. By 2030 the industry will undergo significant changes. By using the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol this paper explores the intersection of project risk management and AI. The study highlights how AI-driven methodologies and tools can revolutionize the way project risks are managed throughout the project lifecycle. Specifically, 215 papers have been analysed to explore how the scientific community has been moving so far on the topic. Besides, a cross-sectional investigation of the PM processes and AI categories/tools was carried out to identify any path that is prevalent, where the prevalence comes from, and for which PM process or sector it is most successful. Finally, from this study several gaps emerged that scientific research would have to fill to effectively implement AI in PM and that have been turned into opportunities for future research in the form of a research agenda.

In recent years, the focus on digital transformation has begun to push companies and society towards an epochal change that will require a complete overhaul of the culture, operations, technologies and value delivery of individual companies and of the entire society worldwide

In recent years, the potential of the metaverse as a tool to connect people has been increasingly recognized. The opportunities offered by the metaverse seem enormous in many sectors and fields of application. However, on the academic side, although a growing number of papers have been found to address the adoption of the metaverse, a clear overview of the solutions in place and their impact on education has been largely neglected so far. In the context of increasing challenges found with the metaverse, this review aims to investigate the role of the metaverse as tool in education. This contribution aims to address this research gap by offering a state-of-the-art analysis of the role the metaverse plays in education in relation to the future of work. The study is based on a systematic review approach performed by means of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. The findings of this research help us to better understand the benefits, potential and risks of the metaverse as a tool for immersive and innovative learning experiences. Implications are discussed and streams for future investigation are identified.