Examinando por Autor "Mejía-Gutiérrez R."
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Ítem Analysis of relevant variables to monitor a photovoltaic charging station through the Function to Data Matrix (FDM) method(Institution of Engineering and Technology, 2018-01-01) Cárdenas-Gómez I.; Fernández-Montoya M.; Mejía-Gutiérrez R.The growth of the electric vehicle industry has brought the development of charging stations and the need for good performance of such systems. The large amount of information that can be monitored in these systems can represent a problem for a good operation in terms of control, computational cost and time. For this reason, it is necessary to make a selection of variables that allows to decrease the data-set’s size without compromising the quality of information, needed for a proper information management system. There are several methods for prioritizing variables, such as the Function to Data Matrix (FDM). This method takes into account the functional analysis of the system, as well as the operative states and their relationship with the basic functions and variables. This enables to obtain a Variable Relevance Indicator (VRI) to define which variables have a higher importance under a particular perspective based on the main function of a system. This article presents the process of analyzing a photovoltaic charging station through the FDM method in order to define the most relevant information to be deployed in a future remote monitoring system. © 2018 Institution of Engineering and Technology. All rights reserved.Ítem Experiences in implementing design heuristics for innovation in product design(Springer-Verlag France, 2018-08-01) Restrepo J.; Ríos-Zapata D.; Mejía-Gutiérrez R.; Nadeau J.-P.; Pailhès J.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)The aided decision processes are expected to improve the design tasks by the reduction of uncertainty, which is one of the principal aspects that interferes with designer choices. These methods can optimise the problem solution by the time reduction in the iterative decision-cycles that can be based on previous knowledge. This article is based in the utilisation of a knowledge based method in design heuristics, which are defined as a set of procedures that allows both, discovery and acquisition, of a solution for a particular problem by the implementation of a strategy, guided by knowledge derived from the experience. This is applied to design area by the extrapolation of technical or conceptual knowledge that has been previously applied and proven in similar problem-solving processes and providing reference points within designs processes as well. For this reason the research focuses on the development of a design case in order to evaluate the interaction between the user and the guided problem approach. The objective was the analysis between two different design processes by the comparison of the implementation of heuristics based method and conventional design techniques in a design case. The purpose was to compare the outcomes of both experiments, taking as a basis the following setup: The design case proposed was carried out by two different teams, where the first team was instructed to use conventional problem-solving approaches such as Pahl & Beitz and Ulrich & Eppinger and the second one was intended to use the heuristics based method. The design task given to both teams was the development of a methane production system by the use of organic waste with the incorporation of technologies to allow the variables control, in other words, an automated biodigester; this allows to have an outcome all teams easy to comparable between each other. Each team performed the task separately, in order to avoid external influence in the process. All of this to proof that with the aid of tools based on heuristic strategies might enhance the innovation and diversification in design alternatives and strengthens conceptual exploration by providing more detailed concepts in early stages of the process. © 2017, Springer-Verlag France SAS.Ítem A Multi-Agent Platform to Support Knowledge Based Modelling in Engineering Design(Springer, 2020-01-01) Mejía-Gutiérrez R.; Fischer X.; Mejía-Gutiérrez R.; Fischer X.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)Nowadays engineering design process requires the involvement of multiple partners from multiple disciplines throughout the Product Life Cycle (PLC). Consequently, the construction of numerical models became a difficult task due to the distribution of experts. This article proposes an agent based approach to support a coherent know-how elicitation, to enrich design problem analysis, based on the re-use of experiences and their storage in a standardized knowledge base. A set of Tutor-Agents (TAs) aid experts in the knowledge modelling process focusing on Variables, Domains and Constraints as a key component of engineering knowledge. A shared and coherent knowledge base is the main purpose of the proposed Multi-Agent System (MAS). The interaction among agents enables to highlight potential incoherencies during the modelling process to avoid inconsistent information. The Multi-Agent approach is implemented in a software prototype and a knowledge base can then be constructed, providing standardized Product Life Cycle (PLC) constraints (based on the product related knowledge) for creating models to be analyzed by traditional inference engines such as Optimization solvers, Constraint Satisfaction programming, etc. © 2020, Springer Nature Switzerland AG.Ítem Optimization of V-Trough photovoltaic concentrators through genetic algorithms with heuristics based on Weibull distributions(Elsevier Ltd, 2018-02-15) Arias-Rosales A.; Mejía-Gutiérrez R.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)Photovoltaic V-Troughs use simple and low-cost non-imaging optics, namely flat mirrors, to increase the solar harvesting area by concentrating the sunlight towards regular solar cells. The geometrical dispositions of the V-Trough's elements, and the way in which they are dynamically adjusted to track the sun, condition the optical performance. In order to improve their harvesting capacity, their geometrical set-up can be tailored to specific conditions and performance priorities. Given the large number of possible configurations and the interdependence of the multiple parameters involved, this work studies genetic algorithms as a heuristic approach for navigating the space of possible solutions. Among the algorithms studied, a new genetic algorithm named “GA-WA” (Genetic Algorithm-Weibull Arias) is proposed. GA-WA uses new heuristic processes based on Weibull distributions. Several V-Trough performance indicators are proposed as objective functions that can be optimized with genetic algorithms: (i) Ce? (average effective concentration); (ii) Cost (cost of materials) and (iii) Tsp (space required). Moreover, from the integration of these indicators, three multi-objective indices are proposed: (a) ICOE (Ce? versus Cost); (b) MICOE (Ce? versus Cost and Ce? versus Tsp combined) and (c) MDICOE (similar to MICOE but with discretization considerations). The heuristic parameters of the studied genetic algorithms are optimized and their capacities are explored in a case study. The results are compared against reported V-Trough set-ups designed with the interactive software VTDesign for the same case study. It was found that genetic algorithms, such as the ones developed in this work, are effective in the performance indicators improvement, as well as efficient and flexible tools in the problem of defining the set-up of solar V-Troughs in personalized scenarios. The intuition and the more holistic exploration of a trained engineer with an interactive software can be complemented with the broader and less biased evolutionary optimization of a tool like GA-WA. © 2017 Elsevier LtdÍtem A Remote Monitoring System for Charging Stations with Photovoltaic Generation(Springer Verlag, 2019-01-01) Sánchez S.; Cárdenas-Gómez I.; Mejía-Gutiérrez R.; Osorio-Gómez G.This work aims to develop a prototype of a monitoring system for a Photovoltaic Charging Station (PVCS) installed in Universidad Eafit. The design is proposed according to the context of remote areas, which are off-grid or where utility grid’s quality is low, and considering the possibility of having standalone charging stations installed in such places. The proposed system integrates several hardware components and communication protocols by making use of Internet of Things (IoT) and Cloud Platform technology. The presented solution is a low-cost infrastructure and enables real-time monitoring and data storing for future analysis. © 2019, Springer Nature Switzerland AG.