Fernanda Strozzi

Learning Factories (LFs) have become increasingly important in engineering education, offering environments where students can engage in experiential learning and connect theoretical knowledge with industrial practice. In 2016, LIUC University established the i-FAB LF, a foosball assembly line where students experience real factory scenarios, as part of educational formats designed to develop skills in lean manufacturing and Industry 4.0. In this context, a variety of activities devoted to industrial engineering students has been developed. Among these, a learning activity centered on the integration of Artificial Intelligence (AI) into quality management stands out as a representative example, fostering the development of the skills required by the new workforce in the context of Industry 5.0 (I5.0). This activity offers a hands-on, team-based learning experience, with its pedagogical foundation rooted in the A3 problem-solving framework, which guides students in systemat ically identifying quality issues, collecting relevant data, and analyzing root causes in the production process. Following this structured analysis, students apply their insights to develop an AI tool leveraging convolutional neural networks to automati cally detect and classify assembly defects. In this way, the A3 process provides both the diagnostic foundation and the data driven roadmap for AI implementation, connecting structured problem solving with innovative technological countermeasures. Taken together, these elements foster skills in creative and innovative thinking, collaboration, data analytics and problem solving – considered as key competencies in the I5.0 paradigm. The contribution of this study is to present the LF-based educational activity and to report students’ perceptions collected through a structured questionnaire on three dimensions: learn ing experience and pedagogical design, collaboration and motivation, and quality of the learning environment.

As industries worldwide face mounting environmental regulations and resource constraints, the integration of Circular Economy (CE) principles has gained prominence, with Industrial Symbiosis (IS) emerging as a key operational mechanism. IS facilitates the mutual exchange of materials, energy, water, and by-products among firms, thereby enhancing resource efficiency and minimizing waste. This study investigates the intersection of IS and Social Network Analysis (SNA), a methodological approach increasingly used to map and analyze the complex inter-organizational networks underpinning symbiotic exchanges. Employing a Systematic Literature Network Analysis (SLNA) framework, this research reviews and synthesizes 86 core publications to uncover prevailing themes, methodological trends, and network structures. The results highlight the growing sophistication of SNA applications within IS studies, revealing key metrics such as centrality, density, and tie formation that elucidate the dynamics of resource sharing. Furthermore, the analysis identifies dominant network configurations—such as core-periphery and decentralized clusters—that characterize successful IS systems. The study proposes a conceptual framework delineating the cyclical development phases of IS networks, emphasizing the critical roles of trust, information sharing, and stakeholder engagement.

The interest of the literature in the last few years around the theme of Digital Twins (DT) and its connection with the pillars of Industry 4.0 (I 4.0) paradigm, in particular relating with Virtual Reality (VR) and Augmented Reality (AR) technologies has strongly grown. As a matter of fact, since 2018 it can be noticed a steady increase in publications that relates to these technologies, especially DT and VR. However, even if the body of the literature is rich in journal papers, conference papers and book chapters, it lacks specific literature reviews that connects these technologies. Therefore, the main aim of this paper is to provide a clear overview of the applications of VR and AR concerning the brand-new concept of Digital Twins. In doing so, this study conducts a bibliometric review carried out with a Systematic Literature Network Analysis (SLNA) on the relationship between VR, AR and DTs. Firstly, by analysing the literature, this article describes the main contributions to the research on VR and AR-related DT applications. Secondly, this paper aims at identifying the main topics to which DTs have been related when matched with VR and AR concepts, and therefore to identify the importance of these technologies on DTs applications. Finally, the paper provides an analysis of the past, present and future trends of DT applications in the literature when related to VR and AR. In doing so, a new visual analysis and representation of keywords trend in time, based on the co-word network analysis typical of the SLNA, is presented, i.e. the Keyword Trend Detection (KTD). The study leads to two main conclusions. The first is related to contributions branches identification. Indeed, two main branches of contributions have been identified; the first is related to the concept of virtualization of manufacturing resources, while the second is focused on the applications of DT and VR. Secondly, as a result of the application of keyword clustering techniques, this research identified five clusters of research streams, i.e., AR-, Robotics-, Virtual-, I 4.0 pillars-and DT-related clusters.

Nowadays many companies deal with lean: some of them have a consolidated lean adoption, others are facing the lean transformation and many others are combining lean with the newest strategies. In all these contexts, the key resource is the human factor and utmost attention should be put to its interface with the organization. This study aims to clarify the link between lean and human resource management (HRM) or organizational behaviour (OB) depicting an overview of the body of literature devoted to their intersection. Two bibliometric tools allowed to examine literature in a dynamic and quantitative way. In particular, the citation network analysis, through the main path analysis, identified the development trajectory of the topic, while the analysis of author keywords co-occurrence network distinguished the different research areas within it. As first result, two main development trajectories were identified: one devoted to the central role of the HR practices included in the “High involvement work systems” to obtain a successful lean implementation; the other one to the clarification of the core nature and patterns of lean when combined to HRM or OB. The second result is the distinction of five different research areas: Lean and BIM – collaboration centrality, Teamwork and lean practices, Training in lean six sigma, Lean leadership and kaizen benefits. Finally, the literature analysis highlighted the need of more cross-fertilization between the fields.

The present hostile economic conditions highlight the need for organizations to integrate various supply chain (SC) strategies to compete favourably. Lean and Agile are two critical strategies because the former ensures efficient use of resources while the latter involves matching supply with demand in unpredictable markets. This paper aims at advancing their understanding by conducting a review to unravel the state of art of Lean-Agile SC by examining the procedure of knowledge conceiving, transfer and development via the application pf "Systematic literature network analysis". The investigation enabled unravelling research directions/emerging themes thereby supporting researchers/newcomers to target specific theme to explore.

The recent revolution connected to the manufacturing and assembly process digitalization, known as Industry 4.0 (I40), is radically changing the way these processes are conducted. Assembly systems are expected to benefit from positive effects, such as significant innovation and improvement in system flexibility, increase in process speed and efficiency, as well as the possibility of extremely customized products. Accordingly, interest in the exploitation of technological improvements introduced by I40 in the design and management of AS is increasing as well. The objective of this paper is to inspect the evolution of research on I40 applied to AS by means of the analysis of the literature on this topic. To achieve this objective, a traditional content-based literature review is combined with quantitative information extracted from bibliographic networks to detect emerging topics, and by revealing the dynamic evolution of the scientific production. This dynamic analysis allowed highlighting research directions and critical areas for the development of the 'assembly I40'. Moreover, the analysis offers insights on the technology improvements that have not been explored yet in order to allow a real transition towards the I40 transformation of AS.

Recurrence is a fundamental property of dynamical systems and studying it helps in deepen our understanding of the systems and predict their evolution. Recurrence has been studied in many real systems, such as financial exchange rates, damage detection and neuroscience data, but, as far as we know have never been applied with the aim of detecting demand patterns needed to develop a reliable forecast model. The analysis is performed using the Recurrence Plot (RP) together with the tool called Recurrence Quantification Analysis (RQA). RP is based on the computation of a distance matrix between reconstructed points in phase space. RQA provides a set of measures for RP quantification. In this work we analyse the RPs corresponding to several simulated demand time series and the relationship between Determinism (DET, a RQA measure) and parameters traditionally used to assess demand patterns. The visualization of the RP and the calculation of DET of the simulated demand time series provide positive results when used to detect demand patterns.

Since the publication of the UN-sponsored World Commission on Environment and Development report [1] in 1987, thousands of initiatives have been undertaken to address the different aspects of environmental challenges [2]. Among these initiatives, in 2002 the UN General Assembly proclaimed the UN Decade of Education for Sustainable Development, 2005-2014, 'emphasising that education is an indispensable element for achieving sustainable development'. Sustainability has been on the agenda of many engineering faculties since the late 1990s [3]. It has become clear that “a new kind of engineer is needed, an engineer who is fully aware of what is going on in society and who has the skills to deal with societal aspects of technologies” [4]. Literature covering this topic is abundant. The discussion on how sustainability can be successfully integrated into engineering programmes is still receiving attention. This paper aims to present a literature review focused on sustainability in engineering education. The review is based on the Systematic Literature Network Analysis (SLNA), a methodology including a collection of computer-based tools that analyses bibliographic data, and that have been applied to the continuous improvement of Higher Education [5]. The SLNA is adopted in this work in order to unfold the dynamics of sustainability in engineering education and identify the directions in which engineering faculties are moving.