10 resultados para quality function development
em Universidad Politécnica de Madrid
Resumo:
onceptual design phase is partially supported by product lifecycle management/computer-aided design (PLM/CAD) systems causing discontinuity of the design information flow: customer needs — functional requirements — key characteristics — design parameters (DPs) — geometric DPs. Aiming to address this issue, it is proposed a knowledge-based approach is proposed to integrate quality function deployment, failure mode and effects analysis, and axiomatic design into a commercial PLM/CAD system. A case study, main subject of this article, was carried out to validate the proposed process, to evaluate, by a pilot development, how the commercial PLM/CAD modules and application programming interface could support the information flow, and based on the pilot scheme results to propose a full development framework.
Resumo:
Commercial computer-aided design systems support the geometric definition of product, but they lack utilities to support initial design stages. Typical tasks such as customer need capture, functional requirement formalization, or design parameter definition are conducted in applications that, for instance, support ?quality function deployment? and ?failure modes and effects analysis? techniques. Such applications are noninteroperable with the computer-aided design systems, leading to discontinuous design information flows. This study addresses this issue and proposes a method to enhance the integration of design information generated in the early design stages into a commercial computer-aided design system. To demonstrate the feasibility of the approach adopted, a prototype application was developed and two case studies were executed.
Resumo:
Este trabajo propone la aplicación de la metodología de despliegue de la función de calidad para definir los criterios de diseño de un robot deslizante para trabajar en tareas de inspección y mantenimiento en pozos petroleros. Dicho estudio analiza inicialmente el sistema y las diferentes opciones para la colocación de una estructura robótica evaluando alternativas y estudiando una estructura robótica para tal fin. Para ello se realizó una consulta por medio de encuesta a varios expertos en el tema con la finalidad de definir las características que debe tener el robot de acuerdo con los requerimientos críticos que tiene la aplicación. En este trabajo se muestran los resultados arrojados por la matriz QFD (Quality Function Deployment) cuando los datos de entrada son los proporcionados por el grupo de expertos encuestados. A partir de estos resultados es posible determinar los requisitos técnicos que debe reunir la estructura robótica que se desea diseñar.
Resumo:
Bread wheat quality constitutes a key trait for the demands of the baking industry as well as the broad consumer preferences. The role of the low molecular weight glutenin subunits (LMW-GS) with regard to bread quality is so far not well understood owing to their genetic complexity and to the use of different nomenclatures and standards for the LMW-GS assignment by different research groups, which has made difficult the undertaking of association studies between genotypes and bread quality. The development of molecular markers to carry out genetic characterization and allele determination is demanding. Nowadays, the most promising LMW gene marker system is based on PCR and high resolution capillary electrophoresis for the simultaneous analysis of the complete multigene family. The molecular analysis of the bread wheat Glu-B3 locus in F2 and F4:6 populations expressed the expected one-locus Mendelian segregation pattern, thus validating the suitability of this marker system for the characterization of LMW-GS genes in segregating populations, allowing for the successful undertaking of studies related to bread-making quality. Moreover, the Glu-B3 allele characterization of standard cultivars with the molecular marker system has revealed its potential as a complementary tool for the allelic determination of this complex multigene family.
Resumo:
1. Introduction 2. Air Quality Modeling system 3. Emission Inventories 4. Applications and Results 5. Conclusions
Resumo:
Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO2. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.
Resumo:
The plant cell wall constitutes an essential protection barrier against pathogen attack. In addition, cell-wall disruption leads to accumulation of jasmonates (JAs), which are key signaling molecules for activation of plant inducible defense responses. However, whether JAs in return modulate the cell-wall composition to reinforce this defensive barrier remains unknown. The enzyme 13-allene oxide synthase (13-AOS) catalyzes the first committed step towards biosynthesis of JAs. In potato (Solanum tuberosum), there are two putative St13-AOS genes, which we show here to be differentially induced upon wounding. We also determine that both genes complement an Arabidopsis aos null mutant, indicating that they encode functional 13-AOS enzymes. Indeed, transgenic potato plants lacking both St13-AOS genes (CoAOS1/2 lines) exhibited a significant reduction of JAs, a concomitant decrease in wound-responsive gene activation, and an increased severity of soft rot disease symptoms caused by Dickeya dadantii. Intriguingly, a hypovirulent D. dadantii pel strain lacking the five major pectate lyases, which causes limited tissue maceration on wild-type plants, regained infectivity in CoAOS1/2 plants. In line with this, we found differences in pectin methyl esterase activity and cell-wall pectin composition between wild-type and CoAOS1/2 plants. Importantly, wild-type plants had pectins with a lower degree of methyl esterification, which are the substrates of the pectate lyases mutated in the pel strain. These results suggest that, during development of potato plants, JAs mediate modification of the pectin matrix to form a defensive barrier that is counteracted by pectinolytic virulence factors from D. dadantii.
Resumo:
As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large cities across Europe, particularly for NO2. Modeling air quality in urban areas is rather complex since observed concentration values are a consequence of the interaction of multiple sources and processes that involve a wide range of spatial and temporal scales. Besides a consistent and robust multi-scale modeling system, comprehensive and flexible emission inventories are needed. This paper discusses the application of the WRF-SMOKE-CMAQ system to the Madrid city (Spain) to assess the contribution of the main emitting sectors in the region. A detailed emission inventory was compiled for this purpose. This inventory relies on bottom-up methods for the most important sources. It is coupled with the regional traffic model and it makes use of an extensive database of industrial, commercial and residential combustion plants. Less relevant sources are downscaled from national or regional inventories. This paper reports the methodology and main results of the source apportionment study performed to understand the origin of pollution (main sectors and geographical areas) and define clear targets for the abatement strategy. Finally the structure of the air quality monitoring is analyzed and discussed to identify options to improve the monitoring strategy not only in the Madrid city but the whole metropolitan area.
Resumo:
La mejora de la calidad del aire es una tarea eminentemente interdisciplinaria. Dada la gran variedad de ciencias y partes involucradas, dicha mejora requiere de herramientas de evaluación simples y completamente integradas. La modelización para la evaluación integrada (integrated assessment modeling) ha demostrado ser una solución adecuada para la descripción de los sistemas de contaminación atmosférica puesto que considera cada una de las etapas involucradas: emisiones, química y dispersión atmosférica, impactos ambientales asociados y potencial de disminución. Varios modelos de evaluación integrada ya están disponibles a escala continental, cubriendo cada una de las etapas antesmencionadas, siendo el modelo GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) el más reconocido y usado en el contexto europeo de toma de decisiones medioambientales. Sin embargo, el manejo de la calidad del aire a escala nacional/regional dentro del marco de la evaluación integrada es deseable. Esto sin embargo, no se lleva a cabo de manera satisfactoria con modelos a escala europea debido a la falta de resolución espacial o de detalle en los datos auxiliares, principalmente los inventarios de emisión y los patrones meteorológicos, entre otros. El objetivo de esta tesis es presentar los desarrollos en el diseño y aplicación de un modelo de evaluación integrada especialmente concebido para España y Portugal. El modelo AERIS (Atmospheric Evaluation and Research Integrated system for Spain) es capaz de cuantificar perfiles de concentración para varios contaminantes (NO2, SO2, PM10, PM2,5, NH3 y O3), el depósito atmosférico de especies de azufre y nitrógeno así como sus impactos en cultivos, vegetación, ecosistemas y salud como respuesta a cambios porcentuales en las emisiones de sectores relevantes. La versión actual de AERIS considera 20 sectores de emisión, ya sea equivalentes a sectores individuales SNAP o macrosectores, cuya contribución a los niveles de calidad del aire, depósito e impactos han sido modelados a través de matrices fuentereceptor (SRMs). Estas matrices son constantes de proporcionalidad que relacionan cambios en emisiones con diferentes indicadores de calidad del aire y han sido obtenidas a través de parametrizaciones estadísticas de un modelo de calidad del aire (AQM). Para el caso concreto de AERIS, su modelo de calidad del aire “de origen” consistió en el modelo WRF para la meteorología y en el modelo CMAQ para los procesos químico-atmosféricos. La cuantificación del depósito atmosférico, de los impactos en ecosistemas, cultivos, vegetación y salud humana se ha realizado siguiendo las metodologías estándar establecidas bajo los marcos internacionales de negociación, tales como CLRTAP. La estructura de programación está basada en MATLAB®, permitiendo gran compatibilidad con software típico de escritorio comoMicrosoft Excel® o ArcGIS®. En relación con los niveles de calidad del aire, AERIS es capaz de proveer datos de media anual y media mensual, así como el 19o valor horario más alto paraNO2, el 25o valor horario y el 4o valor diario más altos para SO2, el 36o valor diario más alto para PM10, el 26o valor octohorario más alto, SOMO35 y AOT40 para O3. En relación al depósito atmosférico, el depósito acumulado anual por unidad de area de especies de nitrógeno oxidado y reducido al igual que de azufre pueden ser determinados. Cuando los valores anteriormente mencionados se relacionan con características del dominio modelado tales como uso de suelo, cubiertas vegetales y forestales, censos poblacionales o estudios epidemiológicos, un gran número de impactos puede ser calculado. Centrándose en los impactos a ecosistemas y suelos, AERIS es capaz de estimar las superaciones de cargas críticas y las superaciones medias acumuladas para especies de nitrógeno y azufre. Los daños a bosques se calculan como una superación de los niveles críticos de NO2 y SO2 establecidos. Además, AERIS es capaz de cuantificar daños causados por O3 y SO2 en vid, maíz, patata, arroz, girasol, tabaco, tomate, sandía y trigo. Los impactos en salud humana han sido modelados como consecuencia de la exposición a PM2,5 y O3 y cuantificados como pérdidas en la esperanza de vida estadística e indicadores de mortalidad prematura. La exactitud del modelo de evaluación integrada ha sido contrastada estadísticamente con los resultados obtenidos por el modelo de calidad del aire convencional, exhibiendo en la mayoría de los casos un buen nivel de correspondencia. Debido a que la cuantificación de los impactos no es llevada a cabo directamente por el modelo de calidad del aire, un análisis de credibilidad ha sido realizado mediante la comparación de los resultados de AERIS con los de GAINS para un escenario de emisiones determinado. El análisis reveló un buen nivel de correspondencia en las medias y en las distribuciones probabilísticas de los conjuntos de datos. Las pruebas de verificación que fueron aplicadas a AERIS sugieren que los resultados son suficientemente consistentes para ser considerados como razonables y realistas. En conclusión, la principal motivación para la creación del modelo fue el producir una herramienta confiable y a la vez simple para el soporte de las partes involucradas en la toma de decisiones, de cara a analizar diferentes escenarios “y si” con un bajo coste computacional. La interacción con políticos y otros actores dictó encontrar un compromiso entre la complejidad del modeladomedioambiental con el carácter conciso de las políticas, siendo esto algo que AERIS refleja en sus estructuras conceptual y computacional. Finalmente, cabe decir que AERIS ha sido creado para su uso exclusivo dentro de un marco de evaluación y de ninguna manera debe ser considerado como un sustituto de los modelos de calidad del aire ordinarios. ABSTRACT Improving air quality is an eminently inter-disciplinary task. The wide variety of sciences and stakeholders that are involved call for having simple yet fully-integrated and reliable evaluation tools available. Integrated AssessmentModeling has proved to be a suitable solution for the description of air pollution systems due to the fact that it considers each of the involved stages: emissions, atmospheric chemistry, dispersion, environmental impacts and abatement potentials. Some integrated assessment models are available at European scale that cover each of the before mentioned stages, being the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model the most recognized and widely-used within a European policy-making context. However, addressing air quality at the national/regional scale under an integrated assessment framework is desirable. To do so, European-scale models do not provide enough spatial resolution or detail in their ancillary data sources, mainly emission inventories and local meteorology patterns as well as associated results. The objective of this dissertation is to present the developments in the design and application of an Integrated Assessment Model especially conceived for Spain and Portugal. The Atmospheric Evaluation and Research Integrated system for Spain (AERIS) is able to quantify concentration profiles for several pollutants (NO2, SO2, PM10, PM2.5, NH3 and O3), the atmospheric deposition of sulfur and nitrogen species and their related impacts on crops, vegetation, ecosystems and health as a response to percentual changes in the emissions of relevant sectors. The current version of AERIS considers 20 emission sectors, either corresponding to individual SNAP sectors or macrosectors, whose contribution to air quality levels, deposition and impacts have been modeled through the use of source-receptor matrices (SRMs). Thesematrices are proportionality constants that relate emission changes with different air quality indicators and have been derived through statistical parameterizations of an air qualitymodeling system (AQM). For the concrete case of AERIS, its parent AQM relied on the WRF model for meteorology and on the CMAQ model for atmospheric chemical processes. The quantification of atmospheric deposition, impacts on ecosystems, crops, vegetation and human health has been carried out following the standard methodologies established under international negotiation frameworks such as CLRTAP. The programming structure isMATLAB ® -based, allowing great compatibility with typical software such as Microsoft Excel ® or ArcGIS ® Regarding air quality levels, AERIS is able to provide mean annual andmean monthly concentration values, as well as the indicators established in Directive 2008/50/EC, namely the 19th highest hourly value for NO2, the 25th highest daily value and the 4th highest hourly value for SO2, the 36th highest daily value of PM10, the 26th highest maximum 8-hour daily value, SOMO35 and AOT40 for O3. Regarding atmospheric deposition, the annual accumulated deposition per unit of area of species of oxidized and reduced nitrogen as well as sulfur can be estimated. When relating the before mentioned values with specific characteristics of the modeling domain such as land use, forest and crops covers, population counts and epidemiological studies, a wide array of impacts can be calculated. When focusing on impacts on ecosystems and soils, AERIS is able to estimate critical load exceedances and accumulated average exceedances for nitrogen and sulfur species. Damage on forests is estimated as an exceedance of established critical levels of NO2 and SO2. Additionally, AERIS is able to quantify damage caused by O3 and SO2 on grapes, maize, potato, rice, sunflower, tobacco, tomato, watermelon and wheat. Impacts on human health aremodeled as a consequence of exposure to PM2.5 and O3 and quantified as losses in statistical life expectancy and premature mortality indicators. The accuracy of the IAM has been tested by statistically contrasting the obtained results with those yielded by the conventional AQM, exhibiting in most cases a good agreement level. Due to the fact that impacts cannot be directly produced by the AQM, a credibility analysis was carried out for the outputs of AERIS for a given emission scenario by comparing them through probability tests against the performance of GAINS for the same scenario. This analysis revealed a good correspondence in the mean behavior and the probabilistic distributions of the datasets. The verification tests that were applied to AERIS suggest that results are consistent enough to be credited as reasonable and realistic. In conclusion, the main reason thatmotivated the creation of this model was to produce a reliable yet simple screening tool that would provide decision and policy making support for different “what-if” scenarios at a low computing cost. The interaction with politicians and other stakeholders dictated that reconciling the complexity of modeling with the conciseness of policies should be reflected by AERIS in both, its conceptual and computational structures. It should be noted however, that AERIS has been created under a policy-driven framework and by no means should be considered as a substitute of the ordinary AQM.
Resumo:
Con esta tesis doctoral se pretende elaborar un modelo de Certificado de Calidad Cinegética independiente, de adhesión voluntaria y aplicable a todo tipo de espacios cinegéticos, de forma que posteriormente pueda convertirse en una metodología que sea empleada como instrumento válido de medición de la Calidad Cinegética y normalizada a través de una familia de Normas aprobadas por un organismo de normalización reconocido a nivel nacional o internacional. En primer lugar, se procedió a la realización de un riguroso y exhaustivo estudio de justificación siguiendo la metodología propuesta por la Norma UNE 66172:2003 IN, Directrices para la justificación y desarrollo de sistemas de gestión (equivalente a la Norma Internacional GUIA ISO/IEC 72:2001). A continuación, se procedió a la identificación y desarrollo de los parámetros de Ordenación Cinegética comunes a cualquier espacio cinegético en España y a la conceptualización de la Calidad Cinegética. Finalmente, se desarrolló un modelo estructurado en nueve Criterios y treinta y cuatro Indicadores de Calidad Cinegética, y un proyecto de familia de Normas para la Certificación de la Calidad Cinegética. ABSTRACT This doctoral thesis aims to produce a model of Hunting Quality Certificate independent, of voluntary adherence and applicable to all types of hunting areas, so that later it can become a methodology to be used as a valid instrument for measuring Hunting Quality and standardized through a family of standards approved by an organization of standardization recognized at a national or an international level. First, we proceeded to carry out a rigorous and comprehensive justification study following the methodology proposed by the UNE 66172: 2003 IN, Guidelines for the justification and development of management systems standards (equivalent to the International Standard GUIA ISO / IEC 72: 2001). Then, we proceeded to the identification and development of Hunting Management parameters common to any hunting area in Spain and the conceptualization of Hunting Quality. Finally, a model structured into nine Criteria and thirty-four Indicators of Hunting Quality and a draft of a family of standards for Hunting Quality Certification were developed.