[en] This thesis report proposes new methodologies in the field of statistical quality control (SQC), specifical!y those techniques adapted to data obtained by sensors, continuously monitored with respect to time, and which are included in the framework of the brach of statistics called Functional Data Analysis ( FDA). All the methodologies, techniques and programs proposed have been developed to provide possible solutions to real problems in the industry and in the laboratories of experimental analysis. All these problems have their starting point in the need to find solutions for the detection of anomalies related to electrical consumption, thermal comfort and air quality in commercial and public buildings, on the one hand, and, on the other hand, the detection of atypical sensors or laboratories in the framework of interlaboratory studies. In particular, NERXUS company, statistical consultancy in energy efficiency, FRIDAMA, of facilities related to climate control, and L:qus, developer of web platforms and management of Big Data in buildings, contacted the author and directors of this PhD thesis to show their problems through practical case studies related to the detection of anomalies in fully sensorized buildings. Given the functional nature of the data, a new methodology of FDA control charts based on the concept of data depth was proposed. On the other hand, the germ of the development of new FDA approaches to Mandel's h and k statistics for the detection of atypical laboratories within an interlaboratory study (ILS) is the participation of the directors Salvador Naya and Javier Tarrío in several ILS studies, which allowed to contact with members of the American Society for Testing and Materials or ASTM International (organization of international standards that develops and publishes voluntary agreements of technical standards for materials, products, systems or services). In fact, those profesionals in charge of interlaboratory studies organized by the ASTM conveyed their interest in the development of new methodologies for detecting atypicallaboratories from the FDA context, given the functional nature of a large part of the experimental data currently obtained through the new available instrumentation (spectra, thermograms, etc.). As a result of this contact, it was established that one of the final objectives of this thesis was the development of these FDA approaches for possible inclusion within the ASTM standards. In order to provide solutions to the problerns raised, the author has proposed the development, programming and application of approximations, from the FDA perspective, of basic tools of SQC such as, on the one hand, the control charts, the most important and representative tool of the Çontrol" stage of Six Sigma methodology of process improvement, and, on the other hand, the Mandel's h and k statistics, developed for the detection of atypical laboratories, taking into account that their graphical output is the most used technique in this field for the detection of laboratories whose data are anomalous. Specifically, in Chapter 1, the. main concepts of the SQC (the branch of statistics in which this thesis is circumscribed), with special mention to reproducibility and repeatability (R & R) studies, interlaboratory studies and control charts, are introduced. It also includes a small introduction to metrology 4.0 and some of the new challenges of industrial statistics, in terms of process control and monitoring, which recent advances in sensorization and data acquisition propose. Given the functional nature of the data defining the problems to be solved in this thesis, the Chapter 2 provides a brief description of functional data analysis, an area in which the proposed methodologies are developed. AIso in the Chapter 2, we introduce those real case studies whose resolution is sought through the development and application of the methodologies proposed in this thesis, in addition to the description of the databases. In the Chapter 3 of this thesis, a procedure has been designed for the detection of laboratories that provide inconsistent results (with respect to the other laboratories) within an interlaboratory study. The main contribution of this procedure is the identification of laboratories that obtain atypical results, with respect to those obtained by others, from the original experimental curves, whether spectra or thermograms,..

[gl] Nesta memoria de tese propóñense novas metodoloxías no eido do control estatístico da calidade (CEC), especificamente, apórtanse novas técnicas adaptadas a datos obtidos mediante o uso de sensores, monitorizados continuamente con respecto do tempo, e que se atinxen dentro da rama da estatística denominada análise de datos funcionais (FDA). Todas as metodoloxías, técnicas e programas propostos foron deseñados para proporcionar solucións alternativas a problemas reais na industria e nos laboratorios de análise. Todos estes problemas teñen o seu cerne na necesidade de atopar solucións para a detección de anomalías relacionadas co consumo eléctrico, o confort térmico ea calidade do aire nos edificios comerciais e públicos, por un lado, e a detección de sensores ou laboratorios atípicos no marco dos estudos interlaboratorio, por outro. En particular, as empresas NERXUS, consultoría estatística sobre a eficiencia enerxética, FRIDAMA, adicada ás instalacións de climatización e [Sigma]qus, que desenvolve plataformas web e xestión de Big Data en edificios, contactaron co autor e directores desta memoria de tese para mostrar os seus problemas e proporcionar datos a través de casos de estudo prácticos relacionados coa detección de anomalías en edificacións totalmente sensorizadas. Dada a natureza funcional dos datos, propúxose unha nova metodoloxía de gráficos de control FDA baseada no concepto de profundidade de datos. Por outra banda, o xerme do desenvolvemento dos novos enfoques FDA para os coñecidos estatísticos h e k de Mandel (ata agora só definidos para o caso escalar) para a detección de laboratorios atípicos dentro dos estudos interlaboratorio é a participación dos directores Salvador Naya e Javier Tarrío en varios estudos ILS, o que permitiu o contacto con membros da merican Society for Testing and Materials ou 'ASTM (organización de estándares internacionais que desenvolve e publica acordos voluntarios de normas técnicas tanto para materiais, produtos, sistemas ou servizos). De feito, os responsábeis a cargo dos estudos ILS organizados pola ASTM transmitiron o seu interese no desenvolvemento de novas metodoloxías para a detección de laboratorios atípicos no contexto FDA, dada a natureza funcional de gran parte dos datos experimentais obtidos actualmente grazas a nova instrumentación dispoñible (espectros, termogramas, etc.). Como consecuencia inmediata deste contacto, fixouse coma un dos obxectivos finais da presente tesis de doutoramento o desenvolvemento destes enfoques FDA para a súa posible inclusión dentro das normas ASTM. Co galo de proporcionar solucións aos problemas propostos, proponse o desenvolvemento, programación e posta en marcha de aproximacións, desde a perspectiva da análise de datos funcionais (FDA), de ferramentas básicas do control estatístico da calidade como son, por unha banda, os gráficos de control, con certeza a técnica estatística máis importante da etapa "Controlar" , no marco da metodoloxía Seis Sigma e, por outra banda, os estatísticos h e k de Mandel, desenvolvidos para a detección de laboratorios atípicos, sendo a súa representación gráfica a técnicas máis utilizada no ámbito dos 1LS para a detección de laboratorios cuxos datos son anómalos. Especificamente, no Capítulo 1, introdúcense os principais conceptos da CEC, a rama da estatística na que se circunscribe a presente memoria de tese, facendo especial mención a estudos de reproducibilidade e repetibilidade (&R), os estudos lLS e os gráficos de control. Tamén se inclúe unha breve introdución á metroloxía 4.0 e aos novos retos da industria industrial, no que se refire ao control e monitorización...