Revista Facultad de Ingeniería Universidad de Antioquia

Bibliometric Study of the global application of collaborative robotics in industry

Jaime Andrés Delgado-Camayo — 2025-02-28

The collaborative robot is an industrial robot that operates collaboratively with humans, safely assisting them in their tasks and improving productivity. This study focuses on analyzing the bibliographic production of the application of collaborative robotics in industry, using a bibliometric study with Scopus metadata. These data were analyzed with the VOSviewer tool for generating visualization networks, by bibliographic mapping the worldwide scientific production. A total of 6309 publications were analyzed, with Chinese authors Wang L. and Wang Y. standing out as the main producers, with 24 publications, demonstrating the academic interest of that country in this subject. There was a positive trend in publications in the last ten years, with an increase of 288%, and the preferred publications are articles (91.3%). It was possible to identify that the most significant bibliographic production on collaborative robotics in industrial processes is more representative in developed countries such as China, Italy, Germany, and the United States. The work revealed the challenges faced by industries in Latin America in implementing Industry 4.0. Due to the absence of business policies and cooperative alliances, it is concluded that these industries in developing countries increase the gap in the integration of emerging technologies and that, due to a lack of knowledge and interest, sometimes they are free tools that can be linked in the company.

Computational modeling of epidemiological count data using Non-Homogeneous Poisson Processes and functional data

Santiago Ortiz — 2025-03-17

In this work, we introduce a novel methodology for modeling discrete count variables within the framework of stochastic processes. Our approach integrates two statistical areas: Non-Homogeneous Poisson Processes for the estimation and prediction of intensity functions based on explanatory variables and functional data estimation techniques. Through a comprehensive case study focusing on an infectious disease with viral characteristics, we demonstrate the potential of our methodology. We provide empirical evidence that our methodology offers a robust alternative for modeling count variables. Our findings support the utility of our approach in capturing the complex dynamics inherent in count data in infectious disease epidemiological phenomena.

Effectivity of UV-VIS/H2O2/TiO2 and biological treatments for recovering effluents from an industrial estate

Julie Joseane Murcia-Mesa — 2025-03-14

In the present study were evaluated a biological treatment and several Advanced Oxidation Technologies (AOTs), including TiO₂/UV-VIS, H₂O₂-UV-VIS and TiO₂/H₂O₂/UV-VIS for industrial wastewater treatment. The experiments were carried out both in a laboratory reactor and in a 120 L/s pilot plant with autonomous operation under solar energy. The individual application of the biological treatment using a commercial bacteria strain led to a significant decrease in total hydrocarbons, sulfates, total organic carbon (TOC), hardness, alkalinity, biochemical oxygen demand (BOD₅), and chemical oxygen demand (COD), in the starting industrial wastewater sample. It was also observed that the application of UV-VIS/H₂O₂/TiO₂ as combined treatments, is more effective than biological treatment and individual AOTs reducing certain quality parameters, such as conductivity, chlorides, nitrates, turbidity, fats and oils, total suspended solids, settleable solids, acidity, TOC, total coliform bacteria and in the removal of heavy metals (Zn, Cu, Cr, Ni, Fe, Pb). In addition, the use of a sequential treatment, initially applying a AOTs and subsequently a biological treatment, resulted in an improvement in the removal of contaminants such as chlorides, heavy metals (Fe, Pb), nitrates and hardness. Thus, the results suggest that the sequential combination of AOTs and biological treatment is an effective strategy for the recovery of industrial wastewater, achieving a greater reduction of contaminants compared to the application of each treatment separately, thus improving the final quality of the treated water.

Anomaly classification in IIoT edge devices

Martha Lucía Rodríguez-López — 2025-03-17

An early Industrial Internet of Things (IIoT) Anomaly Detection reduces maintenance costs, minimizes machine downtime, increases safety, and improves product quality. A multi-class classifier that detects events, failures, or attacks is much more efficient than a simple binary classifier, as it relieves a human operator of the task of identifying anomaly causes, thereby avoiding wasted time that could compromise process performance and security. With these issues in mind, this paper aims to determine whether it can differentiate between a failure that generates a temperature increase in an IIoT device processor, a denial-of-service attack on an MQTT broker, and an event caused by an application executing on the IIoT edge device. Data used to perform the classification comes from a Raspberry Pi 3, specifically from its CPU (e.g., temperature, load,
free memory, Wi-Fi sent and received packets). A k-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), and Multilayer Perceptron (MLP) algorithms were trained. Considering metrics such as false positive rate, false negative rate, accuracy, F1-score, and execution time, we concluded that SVM and MLP were the best methods for the case study because of their accuracy (78.6 and 76.1, respectively) and low execution time (17.3ms and 0.35ms).

Geothermal energy as a solution to heating demand: Economic analysis vs. conventional supply

Natalia Nuño-Villanueva — 2025-02-28

Renewable energies lead the energy transition towards a more sustainable and environmentally friendly energy system. Decarbonization and environmental policies, such as Europe’s 2030 Climate Target Plan, favor and encourage this change. Geothermal energy as a renewable energy can play a critical role in the decarbonization within the heating sector. It is an efficient, safe, and clean energy that is not being implemented with the same trend as its counterparts. This study addresses two issues in the implementation of geothermal energy: the calculation of thermal needs and the economic difference in implementation compared to conventional supplies. Therefore, this study presents a simple methodology for sizing calculations for housing developments and economic comparison of the same installation powered by natural gas or low-enthalpy geothermal energy. The comparative terms considered are the initial installation and the annual expense. This comparison seeks to calculate the payback period of the initial geothermal installation, which has been carried out considering various economic scenarios.

Mechanical performance of asphalt mixtures modified with rubber granules and recycled concrete aggregates

Juan Gabriel Bastidas-Martínez — 2025-03-14

The use of recycled-concrete-aggregate (RCA) in asphalt mixtures is considered a viable technique from a technical standpoint to provide a solution to the environmental problem of final waste disposal. Likewise, the use of crumb-rubber-modified asphalts (CRMA) could contribute to this end. This article evaluated the physical-mechanical behaviour of a hot-mix asphalt (HMA) manufactured with CRMA and partially replacing the coarse fraction of the coarse aggregate of natural (NA) with RCA. For this purpose, four HMA mix designs were conducted by Marshall test, considering NA and RCA, and using as binders an asphalt cement AC 60-70 and CRMA. The mechanical performance was measured by performing Marshall, Indirect-Tensile-Strength (ITS), resilient modulus (RM), and permanent deformation. Resistance to moisture damage was also measured by calculating the Tensile Strength Ratio (TSR). The results show that mixtures with RCA require higher asphalt content. When replacing NA with RCA, HMA decreases its mechanical strength under monotonic and cyclic loading. Likewise, its resistance to moisture damage decreases. Contrary to the above, CRMA tends to increase the mechanical performance of the mixtures. However, the CRMA content used in this study was insufficient to adequately cover and adhere to the RCA, generating a mix that undergo the worst performance.

Physical and chemical properties using commercial diesel and palm oil biodiesel blends

Oscar Hernando Venegas-Pereira — 2025-02-21

In different studies on the impact of fuel blends on the performance and polluting emissions of an internal combustion engine, it is necessary to identify some physical and chemical properties that allow understanding of the behavior of the results; however, obtaining such properties requires the use of special equipment that may incur additional costs. In this document, from some experimental tests, it has been possible to obtain the behavior of physical and chemical properties (density, boiling temperature, cetane index, kinematic viscosity, heat values, and adiabatic flame temperature) for different commercial diesel and palm oil Biodiesel blends. Additionally, the data obtained were statistically treated to obtain fit equations that predict the behavior of most of the properties studied for blend percentage values different from those tested.

Editorial

Maryory Astrid Gómez-Botero — 2025-12-10

The emergence of artificial intelligence in scientific production is forcing publishers and journals to redefine the rules of the game. Oscillating between fascination with its potential and concern for academic integrity, publishers and journals have begun to establish specific policies to ensure that these tools are used as a support—not a substitute—for human work. Today, understanding how each publisher regulates the use of AI is not a technical detail: it is a requirement for publishing rigorously and avoiding ethical or authorship issues in a rapidly evolving scientific ecosystem.