Show simple item record

dc.contributor.authorLagos C.
dc.contributor.authorDuran C.
dc.contributor.authorCarrasco R.
dc.contributor.authorConstanzo R.
dc.contributor.authorSepulveda J.M.
dc.date.accessioned2020-09-02T22:21:11Z
dc.date.available2020-09-02T22:21:11Z
dc.date.issued2018
dc.identifier10.1109/ICCCC.2018.8390439
dc.identifier.urihttps://hdl.handle.net/20.500.12728/5027
dc.descriptionIn this work it is analyzed the case of Great Mining Chilean Enterprise show at present, due to the sustained increase of the energetic costs that in the last years have generated a decrease of the profitability. As a solution, it is proposed the creation of an intelligent system of management and supervision, that can predict the energetic consumption of electricity in a copper productive process of a concentrator plant. Based on the results found. The interview to experts and the protocols, it is generated a conceptual model for a system of intelligent management in mining (SGEP-M) that has an architecture that integrates the management software that mining uses (PI System) to a supervision system in real time that allows engineering decision making of short, medium and long term. It is proposed the implementation of a process of management and efficiency of electric energy for the SGEP-M system. © 2018 IEEE.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.sourceFilip F.G.Dzitac D.Dzitac I.Manolescu M.-J.Dzitac S.Oros H.
dc.subjectenergy management
dc.subjectmining industry
dc.subjectsupervision system
dc.subjectCopper
dc.subjectDecision making
dc.subjectEnergy management
dc.subjectIntelligent systems
dc.subjectMineral industry
dc.subjectNetwork architecture
dc.subjectConceptual model
dc.subjectElectric energies
dc.subjectEnergetic costs
dc.subjectEngineering decision making
dc.subjectIntelligent management
dc.subjectManagement software
dc.subjectProductive process
dc.subjectSupervision systems
dc.subjectEnergy management systems
dc.titleIntelligent management of the energy in copper mining, using predictive supervision systems
dc.typeConference Paper


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record