Abstract

Abstract
The increasing adoption of the Digital Twin concept and technology for managing complex physical assets has led to the emergence of Digital Twin Ecosystems, where interconnected digital twins generate additional value. However, ensuring seamless data sharing and interoperability among diverse systems presents significant challenges. Although research on digital twin architectures has advanced, gaps remain in addressing data governance, security, and stakeholders’ trust. This study performs a comprehensive literature review to investigate architectural solutions to overcome challenges in digital twin ecosystems. The findings identify key requirements such as interoperability, governance, and data management, emphasizing the role of Data Spaces as enablers of secure data sharing. By structuring the requirements for digital twin ecosystem architectures, this paper identifies gaps suggesting future research on scalable and sustainable digital twin ecosystem implementations. These insights are expected to contribute to the development of frameworks that integrate technical advances with organizational and regulatory considerations, ultimately fostering the adoption of digital twin ecosystems across industries. © 2025 Elsevier B.V., All rights reserved.

Abstract
This paper evaluates an Augmented Reality (AR) solution designed to support quality control in a assembly line inspection station before body marriage at a European automotive manufacturer. A three-phase methodology was applied: an AS-IS assessment, a formative evaluation of an intermediate prototype, and a summative evaluation under real production conditions. The AR solution aimed to improve task standardization, non-value-added time (NVAT), and enhance operator accuracy. The results showed that operators successfully developed inspections using the AR tool, identifying and correcting non-conformities (NOKs) while maintaining task duration. Participants valued having contextual information directly in their field of vision and reported increased rigor and consistency. However, usability and ergonomic improvements were noted, such as headset weight, gesture interaction, and visibility over dark components. The findings highlight AR’s potential to support operator autonomy and accuracy in industrial environments while emphasizing the need for human-centered design and integration to ensure long-term adoption. © 2025 Elsevier B.V., All rights reserved.

Abstract
This project was developed to improve the cost estimation process of new products within the Product Development Department of a furniture manufacturer. This work involved developing a methodology using Machine Learning (ML) models trained on products’ existing data to predict the cost of new innovative ones based on similarities and given data. The ML models used were Linear Regression (LR), Light Gradient-Boosting Machine (LGBM), Random Forest (RF), and Support Vector Machine (SVM). The proposed methodology considers the estimation of the total cost of producing a product, which encompasses both material and operational costs. Throughout this project, several analyses were developed to identify and evaluate different independent variables that could explain the behaviour of these two cost components. The suitability of the different variables was studied by applying several ML models, and a set of functions that return an estimate of the cost as a function of these predictor variables was obtained. The proposed approach, which incorporates ML models into more complex variables to predict, resulted in a 19.29% reduction in estimation error. © 2025 Elsevier B.V., All rights reserved.

Abstract
PurposeThe present study aims to analyse the presumed relationship between VLC use and students' grades.Design/methodology/approachThe research strategy unfolds as a case study (Yin, 1994), framed by how undergraduate students of pharmaceutical sciences used video lecture capture (VLC) and the impact of VLC on pedagogic differentiation. Looking at the course of Mechanistic Toxicology (MecTox), the objective is to describe this case of pharmaceutical sciences in depth.FindingsThe findings reveal that over 90% of students engaged with VLC videos, with the average viewing time exceeding the total available video minutes, indicating strong student engagement. The study particularly highlights VLC's positive impact on students with lower academic performance (grades D and E), suggesting that VLC can help reduce the performance gap and support a more inclusive educational environment.Research limitations/implicationsThe findings may have limited generalisability beyond the specific context and sample used. However, this study allows the research findings to be compared with previous research (Remi & atilde;o et al., 2022), contributing to the debate on how pedagogic research can promote evidence-based decisions regarding innovative strategies. The meaning of educational inclusion processes and diversity is, thus, contingent on the institutionalisation of research as a practice of teaching and learning.Practical implicationsThe results of this study thus provide interesting insights for the design of strategic action, considering the diversity of students as seen in parents' academic qualifications and students' conditions (e.g. student-workers, living away from home, holding a grant of economic and social support).Social implicationsThe implications of research findings for society bring the issue of equity in education to the fore. By addressing the diverse needs of students, HEIs can contribute to greater educational equity.Originality/valueUsing VLC as a differentiated pedagogic device might give diversity real content insofar as institutional and national policies can mitigate the possible negative effects of parents' low academic qualifications and the students' conditions of living away from their residence area and holding a grant of economic and social support.

Abstract
Complex systems, characterised by high interconnectedness and unpredictability, demand structured approaches to support decision-making, system integration, and operational efficiency. This study aims to develop a comprehensive understanding of these systems to facilitate the implementation of Digital Twins (DTs) in Complex Operations Environments (COEs). A Systematic Literature Review (SLR), following PRISMA methodology, is conducted and complemented by a grounded theory approach to identify, organise, and synthesise system characteristics. The result is a hierarchical conceptualisation comprising eight core categories that capture the essential dimensions of complexity, including: Process and System Interoperability, Human Relationships, Behaviour/Nature, Products and Services, Multi-processes, Performance, System Structure, and Management and Skill Requirements. This framework offers a structured foundation for designing and implementing DT-based decision support in COEs.