Abstract
In this article the application of the discrete version of the bat algorithm to flowshop scheduling problems is presented and compared with Simulated Annealing, Local Search, as well as versions of each that start from constructive heuristics (Palmer and CDS). Bat algorithm is a novel metaheuristic, developed for continuous problems that has shown exceptional results. This paper intends to assess its effectiveness and efficiency for discrete problems when compared with other optimization techniques, including Simulated Annealing and Local Search, whose results are already proven. First, it was developed a literature review about those algorithms, then they were implemented in VBA with Microsoft Excel. Once implemented, the parameterization was carried out, ensuring an adequate application of the algorithms before they can be compared. Then, the methods were applied for 30 normally distributed instances, in order to draw broader conclusions. Finally, a statistical evaluation was carried out and concluded the inferiority of the Local Search in relation to the metaheuristics and the superiority of the hybrid version of the Bat Algorithm with CDS in relation to Simulated Annealing, with significantly better solutions, in an equal computation time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Meta-heuristics are some of the best-known techniques to approach hard optimization problems, however, there are still questions about what makes some meta-heuristics better than others in a specific problem. This paper presents an analysis of the Firefly and Cuckoo Search Algorithm, such as others meta-heuristics. In order to assess the performance of the Firefly Algorithm and the Cuckoo Search Algorithm, they were compared with other well-known optimization techniques, such as Simulated Annealing and Local Search. Both meta-heuristics analysed in an in-depth computational study, reaching the conclusion that both techniques could be useful in Scheduling Problems and lead to satisfactory solutions quickly and efficiently. Moreover, the results of the analysis show that the Firefly Algorithm, despite having a high runtime, performs better than the other techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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.

Abstract
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.

Abstract
This document addresses and develops a framework tool to solve reliability issues in the calculation of processing times for components, using their dimensions. This framework was implemented in a real industrial setting, specifically in a multinational company that manufactures highly customizable electric motors according to customer requirements. After identifying the most critical components and their respective process diagrams, a prototype of the proposed framework was developed to calculate production time. Additionally, another prototype was developed to aid in visualizing the company’s workload. As a result of this work, various improvements were observed in the company, including a 42% reduction in the time required to create workflows and an increase in the reliability and dependability of process times. The framework significantly enhanced operational efficiency, streamlined production processes, and provided a robust solution for managing the complexities of custom manufacturing, demonstrating its effectiveness in a real-world industrial environment. Furthermore, this approach has the potential to be adapted for use in other industries facing similar challenges. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.