Examinando por Materia "Systematic methodology"

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    From functional prototypes to industrial products
    (Springer-Verlag France, 2017-05-01) Hernández-Pérez, J.C.; Osorio-Gómez, G.; Mejía-Gutiérrez, R.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)
    Nowadays, engineering programs with Problem Based Learning methodologies, develop functional prototypes for demonstration purposes. Most of these ideas, many of them promising, are left behind once the academic term is over. Only a slight percentage of them are followed by an industrialization process, which is not formalized and it is based on third-party experiences. Even if well-known product design methodologies include some methods and activities oriented to evolve the product along its life cycle, they are not suitable for academic projects or they leave out some aspects of the local context. This has been an unexploited area, with high potential as there is no transcendence with academic projects; especially after all the time, effort, and creativity employed into a potentially profitable idea. In this way, the authors propose a methodology intended to allow the transition from academic functional prototype to a product ready to be industrialized according to the capabilities of the local context. Emerging economies, where industrial capabilities may be limited. The development of the methodology has been applied in a case study of an individual electric vehicle. This vehicle was developed with students and researchers within the Design Engineering Research Group (GRID) and it is intended to transport the persons responsible to distribute mail, and packages internally in the University campus. The object of such a case is to study the feasibility to promote this vehicle from functional prototype to a product ready to be industrialized under local industrial constraints. © 2015, Springer-Verlag France.
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    Optimizing performance in spark ignition engines with simulation metamodels
    (Springer-Verlag France, 2019-01-01) Zutta E.; Acosta D.; Diaz G.; Zutta E.; Acosta D.; Diaz G.; Universidad EAFIT. Departamento de Ingeniería de Procesos; Procesos Ambientales (GIPAB)
    This work develops a systematic methodology able to identify the desired work points, the metamodels were evaluated varying air–fuel ratio, ignition timing, compression ratio, and combustion duration using design of computer experiments and RSM. It provide the possibility to determine optimal control parameters, according to selected objectives and operating constraints. This methodology is able to automatically identify the optimal engine calibration with less computational effort. Only in this way, the reliability of an integrated metamodel/optimizer approach can be included in a general-purpose that is to identify the engine calibration that minimizes motor vehicle emissions according to European emission standards (European Union in Off J Eur Union 50, 2007). As long as it improves mean effective pressure and reduces exergy destruction due to heat transfer and combustion process. Since, in internal combustion engines, more than 30–40 % of fuel energy wastes through the exhaust and just 12–25 % of the fuel energy converts to useful work. So, researchers are motivated to recover the heat from the waste sources in engines using the ways which not only reduce the demand of fossil fuels, but also reduce the harmful greenhouse gases and help to energy saving (Hatami et al. in Neural Comput Appl 25(7–8):2079–2090, 2014). The advantages of this contribution include the ability to study a wide range of parametric space and to independently evaluate physical and chemical processes, and detailed in-cylinder information, which is normally not available or is inaccessible in experiments. The uncertainty of the information in this unexplored design region can be quantified. Finally, the problem of optimizing involves three optimization fronts, energetic, economic and ecological (Chica and Torres in Int J Interact Des Manuf 12(1):355–392, 2018). © 2019, Springer-Verlag France SAS, part of Springer Nature.
  • No hay miniatura disponible
    Ítem
    Optimizing performance in spark ignition engines with simulation metamodels
    (Springer-Verlag France, 2019-01-01) Zutta E.; Acosta D.; Diaz G.; Universidad EAFIT. Departamento de Ingeniería de Procesos; Desarrollo y Diseño de Procesos
    This work develops a systematic methodology able to identify the desired work points, the metamodels were evaluated varying air–fuel ratio, ignition timing, compression ratio, and combustion duration using design of computer experiments and RSM. It provide the possibility to determine optimal control parameters, according to selected objectives and operating constraints. This methodology is able to automatically identify the optimal engine calibration with less computational effort. Only in this way, the reliability of an integrated metamodel/optimizer approach can be included in a general-purpose that is to identify the engine calibration that minimizes motor vehicle emissions according to European emission standards (European Union in Off J Eur Union 50, 2007). As long as it improves mean effective pressure and reduces exergy destruction due to heat transfer and combustion process. Since, in internal combustion engines, more than 30–40 % of fuel energy wastes through the exhaust and just 12–25 % of the fuel energy converts to useful work. So, researchers are motivated to recover the heat from the waste sources in engines using the ways which not only reduce the demand of fossil fuels, but also reduce the harmful greenhouse gases and help to energy saving (Hatami et al. in Neural Comput Appl 25(7–8):2079–2090, 2014). The advantages of this contribution include the ability to study a wide range of parametric space and to independently evaluate physical and chemical processes, and detailed in-cylinder information, which is normally not available or is inaccessible in experiments. The uncertainty of the information in this unexplored design region can be quantified. Finally, the problem of optimizing involves three optimization fronts, energetic, economic and ecological (Chica and Torres in Int J Interact Des Manuf 12(1):355–392, 2018). © 2019, Springer-Verlag France SAS, part of Springer Nature.