Abstract
The resources systems selection is still a difficult matter to solve in the Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. Globally, we can say that the resources selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project). We intend in this paper to show: a formulation of a kind of resources selection problem; the performance (computation processing time) of an exact solution algorithm proposed to solve it, according to the number of processing tasks and the number of pre-selected resources per processing tasks; and, as a consequence of the domain of applicability of that algorithm, to propose the formulation an approximate solution algorithm, namely genetic algorithm (GA) based. The final goal it is to improve the knowledge about the algorithms domain for the broker tool, in order to select the most adequate algorithm to perform the resources system selection.

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Abstract
This paper examines the concept of learning factories and their role in addressing contemporary challenges in the production sector. Learning factories integrate learning and production environments, offering hands-on experiences to develop essential competencies for modern manufacturing. Originating from initiatives like the Germany's "Lernfabriken" in the late 1980s and the National Science Foundation's funding in the 1990s, learning factories have gained global prominence. They serve as platforms for research, education, and workforce development, attracting students and workers from diverse sectors. Examples from Europe, the United States, and China illustrate various approaches to leveraging learning factories for industrial advancement and skill development. Overall, learning factories play a vital role in fostering innovation, enhancing competitiveness, and driving economic growth in the manufacturing sector. © 2024 The Authors.

Abstract
Purpose: This paper intends to evaluate the impact of Toyota Way (TW) focused activities on operational performance and its connection to sustainability and longterm success. Methodology/Approach: Three theoretical-practical activities were implemented in a real pickup assembly plant. Performance was assessed through the recording of standard documentation before and after implementation, direct observation at the gemba, and anonymous qualitative surveys of those involved. Findings: Results show how TW enhances workers' skills alongside TPS through experiential learning, fostering continuous improvement with minimal or no financial investment and creating value iteratively and exponentially. However, it had a limited impact on environmental factors. TW emerges as a critical link between short-term operational performance and long-term sustainable growth. Research Limitations/Implications: The sample is restricted to a single assembly plant in Portugal. The surveys involved between 5 and 13 respondents per activity. Originality/Value of paper: In contrast to TPS and lean manufacturing, current literature on TW is limited, often outdated, and lacks clarity regarding its Japanese and American interpretations. Furthermore, few studies emphasise the human element as a driver of company growth-a factor often overlooked by companies. Category: Case study

Abstract
In this article it is performed an in-depth literature review of simulation in Industry 4.0. This paper intends to evaluate the use of simulation tools, focusing on its developments in Industry 4.0. In the first part a literature review was executed on the significance of simulation tools, such as Digital Twins, Discrete Event Simulation and Agent-Based Modelling, throughout several fields of study, giving special attention to manufacturing and production. A bibliometric analysis is also performed to understand the growth in number of articles published on simulation in Industry 4.0. Then, two case studies are presented, conveying the effectiveness of Digital Twins and Discrete Event Simulation in assisting process planning and control, and manufacturing automation. A few more case studies are also briefly referred in order to reinforce this point. At the end, a discussion about the future of simulation, its applications and advantages in industry settings is held, finally presenting the final thoughts, predicting an exponential growth in simulation uses, establishing this tool as a pillar of industrial production in the future. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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This article presents a comprehensive evaluation of the recent development in Enterprise Resource Planning (ERP) Systems. Through a detailed review of current literature and case study analysis, it explores the benefits, challenges, and trends related to the implementation and use of ERP systems in business environments, as well as the key factors influencing the success or failure of ERP projects in the context of Industry 4.0. Furthermore, it highlights the practical and strategic implications of using ERP systems to improve operational efficiency, decision-making, and competitiveness in the global market. This article contributes to a deeper understanding of the role of ERP systems in business management and promotes digital transformation within organizations. In the future, paths like Artificial Intelligence, sustainability, mobile ERP, and customization will enhance the efficiency and adaptability of ERPs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.