An Intelligent Procedure for the Methodology of Energy Consumption in Industrial Environments

Simple item page
dc.contributor.authorMendia, Izaskun
dc.contributor.authorGil-Lopez, Sergio
dc.contributor.authorDel Ser, Javier
dc.contributor.authorGrau, Iñaki
dc.contributor.authorLejarazu, Adelaida
dc.contributor.authorMaqueda, Erik
dc.contributor.authorPerea, Eugenio
dc.contributor.editorAnalide, Cesar
dc.contributor.editorNovais, Paulo
dc.contributor.editorCamacho, David
dc.contributor.editorYin, Hujun
dc.contributor.institutionTecnalia Research & Innovation
dc.contributor.institutionIA
dc.contributor.institutionDIGITAL ENERGY
dc.date.issued2020-10-27
dc.descriptionPublisher Copyright: © 2020, Springer Nature Switzerland AG.
dc.description.abstractThe concern of the industrial sector about the increase of energy costs has stimulated the development of new strategies for the effective management of energy consumption in industrial setups. Along with this growth, the irruption and continuous development of digital technologies have generated increasingly complex industrial ecosystems. These ecosystems are supported by a large number of variables and procedures for the operation and control of industrial processes and assets. This heterogeneous technological scenario has made industries difficult to manage by traditional means. In this context, the disruptive potential of cyber physical systems is beginning to be considered in the automation and improvement of industrial services. Particularly, intelligent data-driven approaches relying on the combination of Energy Management Systems (EMS), Manufacturing Execution Systems (MES), Internet of Things (IoT) and Data Analytics provide the intelligence needed to optimally operate these complex industrial environments. The work presented in this manuscript contributes to the definition of the aforementioned intelligent data-driven approaches, defining a systematic, intelligent procedure for the energy efficiency diagnosis and improvement of industrial plants. This data-based diagnostic procedure hinges on the analysis of data collected from industrial plants, aimed at minimizing energy costs through the continuous assessment of the production-consumption ratio of the plant (i.e. energy per piece or kg produced). The proposed methodology aims to support managers and energy-efficiency technicians to minimize the plant’s energy consumption without affecting the production and therefore, increase its competitiveness. The data used in the design of this methodology are real data from a company dedicated to the design and manufacture of automotive components and one of the main manufacturers in the automotive sector worldwide. The present methodology is under the pending patent application EU19382002.4-120.en
dc.description.statusPeer reviewed
dc.format.extent12
dc.format.extent2134952
dc.identifier.citationMendia , I , Gil-Lopez , S , Del Ser , J , Grau , I , Lejarazu , A , Maqueda , E & Perea , E 2020 , An Intelligent Procedure for the Methodology of Energy Consumption in Industrial Environments . in C Analide , P Novais , D Camacho & H Yin (eds) , unknown . vol. 12490 , 0302-9743 , Springer , pp. 92-103 , 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 , Guimaraes , Portugal , 4/11/20 . https://doi.org/10.1007/978-3-030-62365-4_9
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-030-62365-4_9
dc.identifier.isbn978-3-030-62365-4; 978-3-030-62364-7
dc.identifier.isbn9783030623647
dc.identifier.otherresearchoutputwizard: 11556/1032
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85097184157&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofunknown
dc.relation.ispartofseries0302-9743
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsEnergy efficiency
dc.subject.keywordsSmart manufacturing
dc.subject.keywordsIntelligent systems
dc.subject.keywordsIndustry 4.0
dc.subject.keywordsBig data
dc.subject.keywordsCyber physical systems
dc.subject.keywordsEnergy efficiency
dc.subject.keywordsSmart manufacturing
dc.subject.keywordsIntelligent systems
dc.subject.keywordsIndustry 4.0
dc.subject.keywordsBig data
dc.subject.keywordsCyber physical systems
dc.subject.keywordsTheoretical Computer Science
dc.subject.keywordsGeneral Computer Science
dc.subject.keywordsSDG 7 - Affordable and Clean Energy
dc.subject.keywordsSDG 9 - Industry, Innovation, and Infrastructure
dc.subject.keywordsFunding Info
dc.subject.keywordsThis work has received funding support from the HAZITEK program of the Basque Government (Spain) through the NAIA (Ref. ZL-2017/00701) research grants. It is also appreciate the deference of the company GESTAMP, especially to Iñaki Grau, to provide data from several of its plants. Finally, Javier Del Ser acknowledged funding support from the Consolidated Research Group MATHMODE (IT1294-19), granted by the Department of Education of the Basque Government, as well as by ELKARTEK and EMAITEK programs of this same institution.
dc.subject.keywordsThis work has received funding support from the HAZITEK program of the Basque Government (Spain) through the NAIA (Ref. ZL-2017/00701) research grants. It is also appreciate the deference of the company GESTAMP, especially to Iñaki Grau, to provide data from several of its plants. Finally, Javier Del Ser acknowledged funding support from the Consolidated Research Group MATHMODE (IT1294-19), granted by the Department of Education of the Basque Government, as well as by ELKARTEK and EMAITEK programs of this same institution.
dc.titleAn Intelligent Procedure for the Methodology of Energy Consumption in Industrial Environmentsen
dc.typeconference output
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Mendia2020_Chapter_AnIntelligentProcedureForTheMe.pdf
Size:
2.04 MB
Format:
Adobe Portable Document Format
Download