Person:
Valencia Delfa, José Luis

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First Name
José Luis
Last Name
Valencia Delfa
URI
https://hdl.handle.net/20.500.14352/77459
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
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2018 - 201912020 - 20232
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Author: Villeta López, María Del Carmen × Item Type: Publication ×

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Now showing 1 - 3 of 3
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    Experimental Study for Improving the Repair of Magnesium–Aluminium Hybrid Parts by Turning Processes
    (Metals, 2018) Rubio, Eva; Villeta López, María Del Carmen; Valencia Delfa, José Luis; Sáenz de Pipaón, José
    One of the lightest metallic materials used in the aeronautics, aerospace, and automotive industries, among others, is magnesium, due to its excellent weight/strength ratio. Most parts used in these industries need to be made of materials that are rigid, strong, and lightweight, but sometimes the materials do not simultaneously satisfy all of the properties required. An alternative is to combine two or more materials, giving rise to a hybrid component that can satisfy a wider range of properties. The pieces machined in these industrial fields must satisfy stringent surface roughness requirements that conform to the design specifications. This work shows an experimental study to analyse the surface roughness reached in hybrid components made up of a base of magnesium alloy (UNS M11917) and two inserts of aluminium alloy (UNS A92024) obtained by turning. Its purpose is to determine the influence of the factors and their possible interactions on the response variable, the surface roughness Ra. The study is carried out using a design of experiments (DOE). A product of a full factorial 23 and a block of two factors 3 × 2 was selected. The factors identified as possible sources of variation of the surface roughness are: depth of cut, feed rate, spindle speed, type of tool, location with respect to the specimen (LRS), and location with respect to the insert (LRI). Data were analysed by means of the analysis of variance (ANOVA) method. The main conclusion is the possibility to carry out the repair and maintenance of parts of magnesium–aluminum hybrid components by dry turning; that is, without cutting fluids and, therefore, in the most sustainable way that the process can be carried out. In addition, different combinations of cutting parameters have been identified that allow these operations to be carried out in an efficient manner, reducing mechanization times and, therefore, also the direct and indirect costs associated with them.
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    Project number: 81
    La Matemática Financiera ante la incertidumbre y globalización de los mercados. Aplicación del MiFID II
    (2020) Elices López, Mercedes; Maestro Muñoz, Mª Luisa; Blanco García, Susana; Blanco Hernández, Mª Teresa; Fernández Ruiz, Antonio José; Fernández-Montes Romero, Antonio; Ricote Gil, Fernando; Segovia Vargas, María Jesús; Sánchez González, Mª Pilar; Espín Gutiérrez, Cristobal; Valencia Delfa, José Luis; Villeta López, María Del Carmen
    El proyecto tiene como objetivo actualizar las guías docentes al nuevo marco legal europeo de los mercados financieros y nuestra asignatura, en particular. Integraremos la perspectiva de estudiantes y profesores, en el proceso de evaluación de calidad de los contenidos.
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    Time series clustering using trend, seasonal and autoregressive components to identify maximum temperature patterns in the Iberian Peninsula
    (Environmental and Ecological Statistics, 2023) Arnobio Palacios Gutiérrez; María Villeta López; Valencia Delfa, José Luis; Villeta López, María Del Carmen; Jose Luis Valencia Delfa; María Villeta López; Duczmal, Luiz; Cocchi, Daniela
    Time series (TS) clustering is a crucial area of data mining that can be used to identify interesting patterns. This study introduces a novel approach to obtain clusters of TS by representing them with feature vectors that define the trend, seasonality and noise components of each series in order to identify areas of the Iberian Peninsula (IP) that follow the same pattern of change in regards to maximum temperature during 1931–2009. This representation allows for dimensionality reduction, and is obtained based on singular spectrum analysis decomposition in a sequential manner, which is a well-developed methodology of TS analysis and forecasting with applications ranging from the decomposition and filtering of nonparametric TS to parameter estimation and forecasting. In this approach, the trend, seasonality and residual components of each TS corresponding to a specific area in the Iberian region are extracted using the proposed SSA methodology. Afterwards, the feature vectors of the TS are obtained by modelling the extracted components and estimating their parameters. Finally, a clustering algorithm is applied to group the TS into clusters, which are defined according to the centroids. This methodology is applied to a climate database with reasonable results that align with the defined characteristics, enabling a spatial exploration of the IP. The results identified three differentiated zones that can be used to describe how the maximum temperature varied: in the northern and central zones, an increase in temperature was noted over time, whereas in the southern zone, a slight decrease was noted. Moreover, different seasonal variations were observed across the zones.