3. Producción
Browse
8 results
Search Results
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimization model applied to the distribution of COVID-19 vaccines in Lima and Callao(Springer, 2022-01-01)Currently, Peru has started a vaccination plan to face the crisis generated by Covid-19; however, it has not been the most efficient. The current study seeks to reduce vaccine distribution times and costs in Lima and Callao by applying a mathematical optimization model. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimization model to consolidate the hose load in a Peruvian agribusiness(Springer, 2022-01-01)Transportation represents around 30% of the total cost of a product. Therefore, the distribution of the load and the route must be optimized and chosen correctly, respectively. The present investigation addresses the optimization of the hose load in 40-foot containers by using mathematical optimization. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Mechanical analysis and optimized performance of G-code driven material extrusion components(Elsevier BV, 2022-12-19)In this work an end-to-end optimization procedure to maximize the mechanical performance of Additive Manufacturing (AM) components is presented. Material Extrusion (ME) is the selected demonstrative AM technology, but the approach is applicable to other AM processes where the manufacturing toolpaths of the geometry of the printed component are described in G-Code format. The proposed methodology is integrated into the AM workflow and drives a two-step optimization process in order to select the optimal printing orientation for a user defined case. The G-Code file containing the manufacturing toolpaths is used as input. This approach allows to operate as close as possible to the geometry of the actual component, avoiding the use of the STereoLithography (STL) geometry. A voxelized mesh is built from the G-Code by solving a modified 2.5D Shortest Path Problem (SPP) and high-fidelity Finite Element (FE) simulations are performed with the resulting mesh. A printing pattern-based material model that distinguishes three different zones of the printed component is used. Due to the orthotropic nature of the ME process, the Tsai–Wu failure criterion is applied to obtain the indicators of the mechanical performance of the component. These computed metrics are used to drive an optimization process where a robust criterion based on the Machine Learning (ML) algorithm Anomaly Detection (AD) is applied in order to select the optimal build direction from a prespecified span of orientations. Two test cases and one case study illustrate the performance of the proposed methodology. The results validate the approach against experiments, indicate that the selected optimization criterion is robust against factors alien to the actual physical problem and show that the accuracy of the voxelized method greatly improves the “traditional” STL-based simulations. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimization for vibration analysis in rotating machines(European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ), 2022-09-01)A not stable mechanical movement transmission between systems produces equilibrium losses, such as a rotor of motors that are coupled in rotating machines. This can be studied as a disturbance “vibration” either as characteristic of the movement transmission due to controlled displacement over rotors, which transmits the movement. Therefore, in this research is presented an analysis for an optimal control of the rotor axis displacement that includes “vibration” as the part of the movement transmission. It implies mathematical modelling and specific sensors selections to correlate the vibration in this control task. Furthermore, in order to verify the proposed analysis, it was simulated and tested in a hybrid magnetic bearing system. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing employees’ job motivation using BWM method and fuzzy goal programming: A case study of a petrochemical company(Emerald Publishing, 2022-09-23)Recognizing the factors affecting employees’ job motivation is one of the necessities that can improve people’s performance and increase their effectiveness. This study aims to determine the factors affecting job motivation and to examine effective strategies to increase motivation through identifying internal and external factors. Design/methodology/approach: In this descriptive study, the statistical population was the employees of the largest petrochemical company in Iran. The questionnaire was randomly distributed to the organization’s employees and managers based on Herzberg’s motivation-hygiene theory. To analyze the obtained data, first, the best and the worst factors were identified using SPSS software and then were ranked using best–worst method (BWM). Findings: The results demonstrated that the highest rank among the motivational factors of employees is related to working environment conditions and the lowest rank is related to career advancement and development indicator. In the second stage, the best strategies for motivational factors were determined using the fuzzy goal programming method. The findings showed that 12 out of the 17 proposed solutions have the highest motivation among employees, the implementation of which can increase employee productivity in the petrochemical company under study. Originality/value: Further to the best of the authors’ knowledge, job motivation factors in the petrochemical industry have never been examined and ranked by using the BWM method so far. Also, the goal programming approach has never been applied to determine strategies for increasing job motivation and ultimately productivity. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Genetic algorithms-based size optimization of directly and indirectly coupled photovoltaic-electrolyzer systems(Elsevier Ltd, 2022-10-15)Since relatively high costs and low efficiencies are usually associated with photovoltaic-electrolyzer (PV-EL) systems, the coupling of a PV system to an EL one is a critical aspect when sizing PV-EL systems. Accordingly, using a genetic algorithms-based optimization approach and considering a hydrogen production target of 100 g per day, the size of different directly and indirectly coupled PV-EL systems is optimized in this work. The referred optimization processes are carried out for five PV-EL system configurations, one related to directly coupled systems and four (one per each DC/DC converter topology accounted for) to indirectly coupled ones. In addition, seeking to maximize hydrogen production, minimize losses, and increase system efficiency, four objective functions are assessed. Some of the results highlight that, when using system cost and overall efficiency as objective functions, properly sized indirectly coupled PV-EL systems feature lower implementation costs than directly coupled ones. In addition, the differences in the overall efficiencies characterizing the optimum directly and indirectly coupled PV-EL systems so determined are relatively small (>1%). One of the original contributions of this work relates to the fact that this is one of the first works dealing with optimization processes of both directly and indirectly coupled PV-EL systems, where optimum system configurations are compared with each other. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, REASONING COVARIATIONALLY WITH GEOGEBRA: AN APPROACH TO THE OPTIMIZATION OF FUNCTIONS(Didáctica de la Matemática: Pensamiento Numérico, 2026-04-06)El estudio tuvo por objetivo analizar la relación entre las acciones mentales de razonamiento covariacional y los esquemas de uso que movilizaron dos estudiantes al resolver una tarea de optimización con GeoGebra. Se consideran aspectos teóricos del razonamiento covariacional y de la aproximación instrumental, y el estudio de caso como método de investigación. La construcción de un jardín rectangular con GeoGebra pone en evidencia el razonamiento covariacional de los estudiantes, cuando asocian o no herramientas como deslizadores y puntos para variar sus dimensiones dinámicamente. Abordar situaciones de cambio utilizando GeoGebra favorece el razonamiento covariacional de los estudiantes.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Mathematical modeling in calculus: two technological approaches to an optimization problem(National University, Costa Rica, 2025-01-01)[Objective] The study aimed to analyze the modeling process conducted by university students when solving a problem involving the notion of function optimization. [Methodology] Mathematical modeling is approached from the perspective known as models and modeling, utilizing the modeling cycles from Blum, Leiß, and Borromeo-Ferri, as well as the extended cycle for the use of digital technologies, to describe the processes students conduct during their resolution. The research design is an instrumental multiple case study. The paper reports the work of two second-semester students from the Business Administration program at a university in Lima, Peru, enrolled in the Calculus course during the first semester of 2022. Data was collected using worksheets, GeoGebra files, and semi-structured interviews. [Results] Results show that students developed skills in three areas: in the real world, by understanding that the cost of wiring varies according to the length and type of cable; in the mathematical world, by creating and using a mathematical model to optimize a function by applying prior knowledge on calculus; and in the computational world, by using GeoGebra to apply these concepts. [Conclusions] It is concluded that GeoGebra is a solid tool for developing modeling problems since its interface allows connecting the numerical, algebraic, geometric, and variational fields, providing a better interpretation of the phenomenon of change underlying an optimization problem.1