Manual assembly processes remain a fundamental aspect of the manufacturing industry, primarily due to the dexterity and adaptability of human workers. However, the repetitive and physically demanding nature of these tasks highlights the need for an ergonomic and well-balanced workload, as poor ergonomics can also contribute to errors. This paper aims to automate the assembly line balancing process for a real-world case study. A new multi-objective Assembly Line Balancing Problem (ALBP) formulation is proposed, minimizing both workload variance and variance in workers’ energy expenditure across workstations while accounting for daily fluctuations in the number of operators. The proposed metabolic and time-sensitive assembly line balancing method integrates caloric considerations to reduce long-term risks of Work-Related Musculoskeletal Disorders (WMSDs). Using a graph-based approach, the framework ensures that precedence constraints are met while optimizing task assignments to minimize cycle time and metabolic cost per operator. To improve accuracy in estimating energy expenditure, this study employs the Methods-Time Measurement - Universal Analyzing System (MTM-UAS), which decomposes tasks into standardized motion elements. The methodology is validated through a real-world case study at Bosch Thermotechnology in Portugal, assigning tasks while minimizing the trade-offs between worker fatigue and production goals. The code to validate this study is publicly available at https://github.com/joaorafaelalmeida/line-balancing-algorithm.

Solving the pump scheduling problem in Water Supply Systems (WSS) is essential for reducing energy costs and ensuring operational efficiency. This study applies the Smart Dynamic Local Search (Smart-DLS), a hybrid optimization framework, as a decision support tool to reduce the costs of five days of continuous pumping operation in a real WSS. Smart-DLS integrates deterministic local search with an intelligent shaking process, enhancing solution robustness and scalability while efficiently exploring the solution space. The results demonstrate that Smart-DLS achieved an approximately 19% cost reduction while ensuring tank-level compliance and offering flexible solutions that balance cost efficiency and pump wear reduction. These outcomes demonstrate the Smart-DLS as an effective decision support tool for real-time WSS optimization.

This work presents a flexible scheduling system for Automated Guided Vehicles (AGVs) that seamlessly adapts to single and multi-vehicle environments with varying load capacities. By integrating an auction-based task allocation mechanism with Traveling Salesman Problem (TSP) route optimization, the proposed system efficiently distributes tasks while minimizing overall travel distance and energy consumption. The auction model enables AGVs to bid based on computed costs derived from solving a pickup-and-delivery TSP variant that incorporates capacity constraints, thus ensuring optimal resource utilization and balanced workload distribution. Computational experiments demonstrate significant improvements in task completion times and route efficiency in dynamic scenarios, highlighting the system’s potential for scalable deployment in modern industrial automation settings. Future work will address enhancements in conflict-free routing and dynamic task allocation to further align the model with real-world applications.

In recent years, bibliometrics has been widely used as a methodology for the analysis of scientific production, proving to be an excellent instrument for supporting scientific policy decisions. In this paper, we present a bibliometric analysis of the 12 editions of the Global Engineering Education Conference (EDUCON). Several indicators were used, namely number of submitted articles, the rate of accepted submissions, number of article citations, and the number of references per article, among other indicators. We also intend to add the comparison of the results obtained in the ten first editions held in-site and the last two editions, which have the particularity of having been carried out fully online, evaluating, by this way, the impact of the COVID-19 pandemic crisis to EDUCON. The results show an increase in the number of papers submitted and published over the years, evidencing a growing notoriety of the conference. The same growth tendency is visible regarding the number of authors involved in the conference. Regarding the impact of the online editions, data from the next edition is still required to establish better comparisons and conclusions.

In this paper we present a bibliometrics analysis of the 10 editions of the Global Engineering Education Conference (EDUCON). EDUCON is a conference of the IEEE Education Society for region 8. It started in 2010 and since then it is organized annually. With this study we intend to analyze the growth of the conference, namely through the evolution of the number of submissions/publications, and the number of citations per article. We also intend to analyze the number of references per article. A descriptive statistics of these indicators is done along the paper. With an initial set of 10 editions, it will be possible to investigate the impact of future editions, by performing a sliding-frame analysis, i.e. replacing the oldest by the newest edition and analyzing how this impacts the presented charts.