Examinando por Materia "Sistemas complejos"
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Ítem Exploring the role of system operation modes in failure analysis in the context of first generation cyber-physical systems(Universidad EAFIT, 2018) Ruíz Arenas, Santiago; Horváth, Imre; Mejía Gutiérrez, Ricardo; Rusák, ZoltanÍtem Information management method based on a Knowledge Management (KM) approach for Human Supervisory Control Systems(Universidad EAFIT, 2017) Fernández Montoya, Mauricio; Mejía-Gutiérrez, RicardoWith the increasing level of technological developments, technical systems have become more and more complex – This complexity allows systems to perform a greater number of tasks in a more efficient and fast way -- These tasks enable the system to achieve an objective that can be related to, either the materialization of a product, the provision of a service or the satisfactory execution of a mission -- These Complex Systems (CS), can be an industrial plant or process, as well as aerospace systems, energy facilities, military industry, civil industry, aircraft, transportation, sports, etc. They all have in common, that a great amount of tasks may be automated, but anyway, they need human supervision through the so-called “Operators” (who are the qualified personnel in charge of maintaining the stability of the process) -- This operators must perform a constant monitoring and control, mainly through Human Machine Interfaces (HMI) and this Human-Machine interaction is studied by the field of Human Supervised Control (HSC) -- As CS have become more critical, they require the monitoring of more subsystems and variables, making them more susceptible to failures due to errors of the human operators -- From the literature study, it is evident that in order to avoid such errors, three aspects become relevant: i) the level of automation of the processes have a direct influence on the flow of information between the CS and the Operators, ii) the ergonomics of the graphical interfaces its critical to facilitate the interpretation of that information and iii) methodologies for a systematic CS design become necessary to guarantee tasks accomplishment -- These aspects become more critical, because CS generally integrates heterogeneous subsystems and components, which increases considerably the amount of information available to operators -- The problem is that Operators, who are experts in their disciplines, use a preferred set of data, linked to their particular knowledge (without considering the full set of variables of the whole system), to perform monitoring and control tasks -- It was also found in the literature that CS designers do not have a clear or formal guideline for selection and weighting of the relevant data. Consequently, this project proposes an information management method based on a Knowledge Management (KM), to select and weight mission data in Human Supervision Control Systems (HSC) -- The method is based on the functional analysis of the process, as well as the generation of functions from its main objective -- This method was applied in a case study, where an analysis was performed around a mission control of a solar vehicle, that compete in the Bridgestone World Solar Challenge 2015 -- It was found that the number of relevant variables to monitor the competition was small, compared to the big set of available variables -- Another finding, was that the set of relevant variables is strongly influenced by the Operating States (OS) of the vehicle throughout the different moments of the competition -- Although there are some variables that are consistently stronger than others in all OS, in general, the variables’ importance presents a variable behavior between OS, concluding that the relevance of the variables is dynamicÍtem Optimal dismantling of criminal networks. A perspective from the mathematical and computational modeling(Universidad EAFIT, 2016-11-22) Sarmiento Bahoque, Tomas Angel; Cantillo Palacio, John Fredys; Realpe Gómez, John Eduardo; Montoya Martínez, Javier AntonioÍtem Structural Damage detection and Reliability Estimation using a Multidimensional Monitoring Approach(Universidad EAFIT, 2016) Ortíz Galeano, Juan Orlando; Gutiérrez Carvajal, Ricardo Enrique; Betancur Giraldo, Germán René; Castañeda Heredia, Leonel Francisco; Zajac, Grzegorz; Gómez, JohnnyMany structural elements are exposed to load conditions that are difficult to model during the design stage, such as environmental uncertainties, random impacts and overloading amongst others, thus, increasing un programmed maintenance and reducing confidence in the reliability of the structure in question -- One way to deal with this problem is to monitor the structural condition of the element -- This approach requires supervising several signals coming from critical locations and then, performing an accurate condition estimation of the element based on the data collected -- Herein, this paper implements a method to diagnosis and evaluate the reliability of the bolster beam structure of the railway-vehicle during a fatigue test -- The results show that multidimensional monitoring not only provides an accurate diagnosis of the element, but also that this technique allows to estimate reliability correctlyÍtem Virtual validation of an automated greenhouse irrigation model based on a systems engineering approach(2014-03-27) Mejía Gutiérrez, Ricardo; Zuluaga Holguín, Daniel; Carvajal Arango, Ricardo; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ricardo Mejia (rmejiag@eafit.edu.co); Daniel Zuluaga (dzulua19@eafit.edu.co); Ricardo Carvajal (rcarvaj2@eafit.edu.co); Ingeniería de Diseño - GRIDIn the context of multidisciplinary complex systems design, modelling is a key aspect -- It allows designers to validate designs at early design stages -- Consequently, reducing the uncertainty regarding if the product fulfils the initial requirements, so they can go through the remaining development stages knowing that have found an optimal solution -- In this work, a virtual prototype of an automated greenhouse irrigation system is modelled and compared with the real system implementation, finding some differences and similarities between both system testing approaches -- The intrinsic dependence of experimentation and modelling is also discussed, as sometimes experimental data is needed to feed virtual models