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Energy Consumption Analysis and Efficiency Enhancement in Manufacturing Companies Using Decision Support Method for Dynamic Production Planning (DSM DPP) for Solar PV Integration

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Energy Consumption Analysis and Efficiency Enhancement in Manufacturing Companies Using Decision Support Method for Dynamic Production Planning (DSM DPP) for Solar PV Integration

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dc.contributor.author Skéré, Simona es_ES
dc.contributor.author Bastida-Molina, Paula es_ES
dc.contributor.author Hurtado-Perez, Elias es_ES
dc.contributor.author Juzénas, Kazimieras es_ES
dc.date.accessioned 2023-11-07T19:02:16Z
dc.date.available 2023-11-07T19:02:16Z
dc.date.issued 2023-10-02 es_ES
dc.identifier.uri http://hdl.handle.net/10251/199448
dc.description.abstract [EN] The Industrial Revolution brought major technological progress and the growth of manufacturing, which resulted in significant changes in energy use. However, it also brought about new environmental issues such as increased energy needs, unstable electricity costs, and worsened greenhouse gas effects. Nowadays, it is crucial to analyze energy use to stay competitive. Manufacturers, highly dependent on electricity, can save energy and enhance efficiency by improving production methods. This article presents the findings of a research study conducted on a Lithuanian manufacturing company, aiming to investigate its electricity consumption over a 15-month period from 2022.01 to 2023.03¿detailed data about the monthly consumption of the six most powerful machines and their active and standby hours are presented. The total electricity consumption of those matched 173.62 MWh. Employing the Decision Support Method for Dynamic Production Planning (DSM DPP), which was previously developed and refined, the study examines the potential for time savings and, subsequently, energy savings, through process reorganization. A detailed three-month production orders observation period demonstrates tangible time savings while using the proposed DSM DPP¿time savings of approximately 5% can be achieved. Compared to that, production might achieve a 20% productivity increase with advanced technology implementation, so 5% is a great result for an easily adaptable method. Based on this, changes in energy consumption and CO2 emissions due to electricity consumption are calculated and presented knowing that the company uses energy from the grid. Adaptation of the replanning method resulted in a reduction of electricity use by 175 kWh and a reduction of CO2 consumption by 27 kgCO2. With proper production planning, energy and CO2 consumption can be decreased, which is a high priority in today¿s world. es_ES
dc.description.sponsorship This research was prepared during the ERASMUS+ funded traineeship es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Machines (Basel) es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Energy consumption es_ES
dc.subject CO2 emissions es_ES
dc.subject Production planning es_ES
dc.subject Decision support method es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title Energy Consumption Analysis and Efficiency Enhancement in Manufacturing Companies Using Decision Support Method for Dynamic Production Planning (DSM DPP) for Solar PV Integration es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/machines11100939 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny es_ES
dc.description.bibliographicCitation Skéré, S.; Bastida-Molina, P.; Hurtado-Perez, E.; Juzénas, K. (2023). Energy Consumption Analysis and Efficiency Enhancement in Manufacturing Companies Using Decision Support Method for Dynamic Production Planning (DSM DPP) for Solar PV Integration. Machines (Basel). 11(10):1-21. https://doi.org/10.3390/machines11100939 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/machines11100939 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 21 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 10 es_ES
dc.identifier.eissn 2075-1702 es_ES
dc.relation.pasarela S\502100 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Universitat Politècnica de València


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