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Constructing a Control Chart Using Functional Data
dc.contributor.author | Flores, Miguel | |
dc.contributor.author | Naya, Salvador | |
dc.contributor.author | Fernández-Casal, Rubén | |
dc.contributor.author | Zaragoza, Sonia | |
dc.contributor.author | Raña, Paula | |
dc.contributor.author | Tarrío-Saavedra, Javier | |
dc.date.accessioned | 2020-03-17T10:35:50Z | |
dc.date.available | 2020-03-17T10:35:50Z | |
dc.date.issued | 2020-01-02 | |
dc.identifier.citation | Flores, M.; Naya, S.; Fernández-Casal, R.; Zaragoza, S.; Raña, P.; Tarrío-Saavedra, J. Constructing a Control Chart Using Functional Data. Mathematics 2020, 8, 58. https://doi.org/10.3390/math8010058 | es_ES |
dc.identifier.issn | 2227-7390 | |
dc.identifier.uri | http://hdl.handle.net/2183/25178 | |
dc.description.abstract | [Abstract] This study proposes a control chart based on functional data to detect anomalies and estimate the normal output of industrial processes and services such as those related to the energy efficiency domain. Companies providing statistical consultancy services in the fields of energy efficiency; heating, ventilation and air conditioning (HVAC); installation and control; and big data for buildings, have been striving to solve the problem of automatic anomaly detection in buildings controlled by sensors. Given the functional nature of the critical to quality (CTQ) variables, this study proposed a new functional data analysis (FDA) control chart method based on the concept of data depth. Specifically, it developed a control methodology, including the Phase I and II control charts. It is based on the calculation of the depth of functional data, the identification of outliers by smooth bootstrap resampling and the customization of nonparametric rank control charts. A comprehensive simulation study, comprising scenarios defined with different degrees of dependence between curves, was conducted to evaluate the control procedure. The proposed statistical process control procedure was also applied to detect energy efficiency anomalies in the stores of a textile company in the Panama City. In this case, energy consumption has been defined as the CTQ variable of the HVAC system. Briefly, the proposed methodology, which combines FDA and multivariate techniques, adapts the concept of the control chart based on a specific case of functional data and thereby presents a novel alternative for controlling facilities in which the data are obtained by continuous monitoring, as is the case with a great deal of process in the framework of Industry 4.0. | es_ES |
dc.description.sponsorship | This study has been funded by the eCOAR project (PC18/03) of CITIC. The work of Salvador Naya, Javier Tarrío-Saavedra, Miguel Flores and Rubén Fernández-Casal has been supported by MINECO grants MTM2014-52876-R, MTM2017-82724-R, the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2016-015, and Centro Singular de Investigación de Galicia ED431G/01 2016-19), through the ERDF. The research of Miguel Flores has been partially supported by Grant PII-DM-002-2016 of Escuela Politécnica Nacional of Ecuador | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C-2016-015 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 2016-19 | es_ES |
dc.description.sponsorship | Escuela Politécnica Nacional de Ecuador; PII-DM-002-2016 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2014-52876-R/ES/INFERENCIA ESTADISTICA COMPLEJA Y DE ALTA DIMENSION: EN GENOMICA, NEUROCIENCIA, ONCOLOGIA, MATERIALES COMPLEJOS, MALHERBOLOGIA, MEDIO AMBIENTE, ENERGIA Y APLICACIONES INDUSTRI | |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSION | |
dc.relation.uri | https://doi.org/10.3390/math8010058 | es_ES |
dc.rights | Atribución 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Functional data analysis | es_ES |
dc.subject | Statistical process control | es_ES |
dc.subject | Control chart | es_ES |
dc.subject | Data depth | es_ES |
dc.subject | Nonparametric control chart | es_ES |
dc.subject | Energy efficiency | es_ES |
dc.title | Constructing a Control Chart Using Functional Data | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Mathematics | es_ES |
UDC.volume | 8 | es_ES |
UDC.issue | 1 | es_ES |
UDC.startPage | 58 | es_ES |
dc.identifier.doi | 10.3390/math8010058 |
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