Publicação
Context-Based Decision Support System for Energy Efficiency in Industrial Plants
| Resumo: | Industrial companies must actively pursue more energy efficiency in their processes, with impacts on both costs and the environment, and ultimately business performance. This article explores the influence of context around the manufacturing process on energy consumption. By creating awareness of this influence in a quantified way, it is possible, via a structured decision process, to find opportunities and derive solutions to improve energy performance. This work introduces a method developed in the scope of the LifeSaver project, which is based on the visualization of energy consumption data against benchmark/average values. The overall approach is supported by a software platform which offers a set of functionalities covering the complete approach, from the detection of the consumption pattern to the implementation of improvement solutions. The approach was tested in two industrial business cases. The first one illustrates the approach by showing the influence of the human factor on the energy performance in cement production. The second case deals with finding opportunities on the selection of the operation point, and its impact on peak load management. The proposed approach and developed system demonstrate a positive direct impact on reducing energy consumption and consequent carbon dioxide emissions. Furthermore, the operation of the implemented case studies has an important indirect effect on bringing awareness to the impact of small actions on general energy efficiency. |
|---|---|
| Autores principais: | Neves-Silva, Rui |
| Outros Autores: | Camarinha-Matos, Luís M. |
| Assunto: | context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868984103300235264 |
|---|---|
| author | Neves-Silva, Rui |
| author2 | Camarinha-Matos, Luís M. |
| author2_role | author |
| author_facet | Neves-Silva, Rui Camarinha-Matos, Luís M. |
| author_role | author |
| contributor_name_str_mv | UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias CTS - Centro de Tecnologia e Sistemas Molecular Diversity Preservation International (MDPI) RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Neves-Silva, Rui\"},{\"Person.name\":\"Camarinha-Matos, Luís M.\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias CTS - Centro de Tecnologia e Sistemas Molecular Diversity Preservation International (MDPI) RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Neves-Silva, Rui Camarinha-Matos, Luís M. |
| datacite.date.Accepted.fl_str_mv | 2022-03-25T00:00:00Z |
| datacite.date.available.fl_str_mv | 2022-08-03T22:25:49Z |
| datacite.date.embargoed.fl_str_mv | 2022-08-03T22:25:49Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| datacite.titles.title.fl_str_mv | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| dc.contributor.none.fl_str_mv | UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias CTS - Centro de Tecnologia e Sistemas Molecular Diversity Preservation International (MDPI) RUN |
| dc.creator.none.fl_str_mv | Neves-Silva, Rui Camarinha-Matos, Luís M. |
| dc.date.Accepted.fl_str_mv | 2022-03-25T00:00:00Z |
| dc.date.available.fl_str_mv | 2022-08-03T22:25:49Z |
| dc.date.embargoed.fl_str_mv | 2022-08-03T22:25:49Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/142837 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| dc.title.fl_str_mv | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Industrial companies must actively pursue more energy efficiency in their processes, with impacts on both costs and the environment, and ultimately business performance. This article explores the influence of context around the manufacturing process on energy consumption. By creating awareness of this influence in a quantified way, it is possible, via a structured decision process, to find opportunities and derive solutions to improve energy performance. This work introduces a method developed in the scope of the LifeSaver project, which is based on the visualization of energy consumption data against benchmark/average values. The overall approach is supported by a software platform which offers a set of functionalities covering the complete approach, from the detection of the consumption pattern to the implementation of improvement solutions. The approach was tested in two industrial business cases. The first one illustrates the approach by showing the influence of the human factor on the energy performance in cement production. The second case deals with finding opportunities on the selection of the operation point, and its impact on peak load management. The proposed approach and developed system demonstrate a positive direct impact on reducing energy consumption and consequent carbon dioxide emissions. Furthermore, the operation of the implemented case studies has an important indirect effect on bringing awareness to the impact of small actions on general energy efficiency. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/67506bfd-4254-4f3b-bb7f-4c034a334331/download |
| id | run_a44b5b18c6206ee4e2fabcd8f4ebbb50 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/142837 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/142837 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Neves-Silva, Rui Camarinha-Matos, Luís M. |
| publishDate | 2022 |
| repo_facet_str | urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL |
| reponame_str | Repositório Institucional da UNL |
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| spelling | engenIndustrial companies must actively pursue more energy efficiency in their processes, with impacts on both costs and the environment, and ultimately business performance. This article explores the influence of context around the manufacturing process on energy consumption. By creating awareness of this influence in a quantified way, it is possible, via a structured decision process, to find opportunities and derive solutions to improve energy performance. This work introduces a method developed in the scope of the LifeSaver project, which is based on the visualization of energy consumption data against benchmark/average values. The overall approach is supported by a software platform which offers a set of functionalities covering the complete approach, from the detection of the consumption pattern to the implementation of improvement solutions. The approach was tested in two industrial business cases. The first one illustrates the approach by showing the influence of the human factor on the energy performance in cement production. The second case deals with finding opportunities on the selection of the operation point, and its impact on peak load management. The proposed approach and developed system demonstrate a positive direct impact on reducing energy consumption and consequent carbon dioxide emissions. Furthermore, the operation of the implemented case studies has an important indirect effect on bringing awareness to the impact of small actions on general energy efficiency.application/pdfenContext-Based Decision Support System for Energy Efficiency in Industrial PlantsNeves-Silva, RuiCamarinha-Matos, Luís M.UNINOVA-Instituto de Desenvolvimento de Novas TecnologiasCTS - Centro de Tecnologia e SistemasMolecular Diversity Preservation International (MDPI)HostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptISSNIsPartOf2071-1050URNIsPartOfPURE: 43275843URNIsPartOfPURE UUID: 5c6eaeb3-67ec-42b7-b68a-395c5223ab51URNIsPartOfScopus: 85127578308URNIsPartOfWOS: 000780761100001URNIsPartOfORCID: /0000-0003-1338-0287/work/116781916DOIIsPartOf10.3390/su140738852022-08-03T22:25:49Z2022-03-252022-03-25T00:00:00ZHandlehttp://hdl.handle.net/10362/142837http://purl.org/coar/access_right/c_abf2open accesscontext awarenessdecision support systemsenergy efficiencymanufacturing industryGeography, Planning and DevelopmentRenewable Energy, Sustainability and the EnvironmentEnvironmental Science (miscellaneous)Energy Engineering and Power TechnologyManagement, Monitoring, Policy and LawSDG 7 - Affordable and Clean Energy6283398 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/67506bfd-4254-4f3b-bb7f-4c034a334331/download |
| spellingShingle | Context-Based Decision Support System for Energy Efficiency in Industrial Plants Neves-Silva, Rui context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| status | SINGLETON |
| subject.fl_str_mv | context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| title | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| title_full | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| title_fullStr | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| title_full_unstemmed | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| title_short | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| title_sort | Context-Based Decision Support System for Energy Efficiency in Industrial Plants |
| topic | context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| topic_facet | context awareness decision support systems energy efficiency manufacturing industry Geography, Planning and Development Renewable Energy, Sustainability and the Environment Environmental Science (miscellaneous) Energy Engineering and Power Technology Management, Monitoring, Policy and Law SDG 7 - Affordable and Clean Energy |
| url | http://hdl.handle.net/10362/142837 |
| visible | 1 |