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In multihead weighers, packaging processes seek to find the best combination of passage hoppers whose product content provides a total package weight as close as possible to its (nominal) label weight. The weighing hoppers arranged in these machines dispense the product quantity that each package contains through computer algorithms designed and executed for this purpose. For its part, in the packaging process for double-layered multihead weighers, all hoppers are arranged in two levels. The first layer comprises a group of weighing hoppers, and the second comprises a set of booster hoppers placed uprightly or diagonally to each weighing hopper based on design of the machine. In both processes, the initial machine configuration is the same; however, the hopper selection algorithm works differently. This paper proposes a new packaging process optimization algorithm for double-layer upright and diagonal machines, wherein the hopper subset combined has previously been defined, and the packaging weight is expressed as actual values. As part of its validation, product filling strategies were implemented for weighing hoppers to assess the algorithm in different scenarios. Results from the process performance metrics prove that the new algorithm improves processes by reducing variability. In addition, results reveal that some machine configurations were also able to improve their operation.

The application of time series models for forecasting environmental variables such as precipitation is essential for understanding climatic patterns and supporting sustainable urban planning in environments characterized by high or moderate levels of risk. This study aims to evaluate and optimize time series forecasting models for rainfall prediction in Barranquilla, Colombia. To this end, five models were applied, namely, Simple Moving Average (SMA), Weighted Moving Average (WMA), Exponential Smoothing (ES), and multiplicative and additive Holt–Winters models, using 139 monthly precipitation records from the IDEAM database covering the period 2013–2025. Model accuracy was evaluated using Mean Absolute Error (MAE) and Mean Squared Error (MSE), and nonlinear optimization techniques were applied to estimate smoothing and weighting parameters for improved accuracy. The results showed that optimization significantly enhances model performance, particularly in the multiplicative Holt–Winters model, which achieved the lowest errors, with a minimum MAE of 75.33 mm and an MSE of 9647.07. The comparative analysis with previous studies demonstrated that even simple models can yield substantial improvements when properly optimized. Furthermore, forecasts optimized using MAE were more stable and consistent, whereas those optimized with MSE were more sensitive to extreme variations. Overall, the findings confirm that seasonal models with optimized parameters offer superior predictive capacity, making them valuable tools for hydrological risk management.

Los enfoques de prevención de riesgos en actividades, funciones o procesos se han convertido en piezas fundamentales a la hora de minimizar la ocurrencia de eventos que son perjudiciales para las compañías. Cada producto no conforme está estrechamente ligado con eventos no deseados relacionados con uno o algunos de los factores que intervienen en el proceso. La identificación, análisis, evaluación, tratamiento, comunicación y monitoreo de estos eventos no deseados garantizarán el incremento de la calidad en los productos y la productividad en el proceso productivo. En este artículo, proponemos un diseño metodológico para la prevención de riesgos en procesos productivos. La metodología propone una forma novedosa de combinar el uso de herramientas estadísticas de calidad y la norma ISO 31000 de gestión de riesgos. La validación fue hecha sobre un proceso de envasado de productos lácteos. Las conclusiones de esta investigación muestran que el diseño metodológico propuesto es suficientemente flexible para ser adaptado a cualquier tipo de proceso de fabricación que se desea monitorear y mejorar.

The increasing challenge of waste disposal and the growing demand for reliable renewable energy sources are particularly critical in developing countries. Waste-to-Energy technologies have emerged as a promising approach to harness the energy potential of waste in an economically viable and environmentally sustainable manner. This study provides a global overview of scientific developments and technological trends in Waste-to-Energy through a bibliometric analysis of 1869 documents retrieved from the Web of Science database, covering the period 2017–2021 and focusing on the field of bioenergy. Here, the term bioenergy is used in a broad sense, encompassing energy recovery from both biogenic waste (e.g., food waste, agricultural residues) and non-biogenic waste (e.g., plastics, synthetic polymers) under the Waste-to-Energy framework. The analysis revealed that developing countries prioritize specific technologies for energy recovery: anaerobic digestion for organic waste, incineration for non-biodegradable mixed waste, and pyrolysis and gasification for carbon-rich waste streams such as biomass and plastics. Landfilling is mentioned solely as a final disposal route for inert materials, not as an energy recovery pathway. Additionally, research highlights the potential benefits of synergistic combinations of raw materials in improving product quality and reducing pollution in Waste-to-Energy processes. This bibliometric and content-based review supports future research efforts by identifying key trends, influential contributions, and critical implementation challenges. The findings underscore the role of Waste-to-Energy technologies as valuable tools in sustainable waste management strategies, especially in regions where improving energy access and reducing environmental impact are pressing concerns.

Los enfoques de prevención de riesgos en actividades, funciones o procesos son fundamentales para minimizar eventos perjudiciales en las empresas. Este artículo propone un diseño metodológico para la prevención de riesgos en procesos productivos, combinando herramientas estadísticas de calidad y la norma ISO 31000. La validación se realizó en un proceso de envasado de productos lácteos, mostrando que el diseño es adaptable a cualquier proceso de fabricación, mejorando la calidad y productividad.