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MTConnect를 활용한 수치제어 프로그램의 에너지 예측 모델링

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dc.contributor.author신승준-
dc.contributor.author우정엽-
dc.contributor.author서원철-
dc.contributor.author정여진-
dc.date.accessioned2022-07-14T03:37:30Z-
dc.date.available2022-07-14T03:37:30Z-
dc.date.created2021-05-14-
dc.date.issued2017-05-
dc.identifier.issn1225-9071-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/152378-
dc.description.abstractIn the metal-cutting industry, energy prediction is important for environmentally-conscious manufacturing because it enables a numerical anticipation of the energy consumption from the input of the process parameters, and therefore it contributes to the increasing of the energy-efficiency of the machine-tool operations. This paper proposes an energy-prediction modeling approach for numerical-control programs based on historical machine-monitoring data that have been collected from machine-tool operations. The proposed approach can create accurate energy-prediction models that forecast the energy that is consumed by the execution of a numerical-control program. Also, it can create machine-specific energy-prediction models that accommodate the variety of shop-floor machining contexts. For this purpose, it uses MTConnect to represent the machine-monitoring data to embody an interoperable data-collection environment regarding the shop floor. This paper also presents a case study to show the feasibility and practicability of the proposed approach.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국정밀공학회-
dc.titleMTConnect를 활용한 수치제어 프로그램의 에너지 예측 모델링-
dc.title.alternativeEnergy Prediction Modeling for Numerical Control Programs Using MTConnect-
dc.typeArticle-
dc.contributor.affiliatedAuthor신승준-
dc.identifier.doi10.7736/KSPE.2017.34.5.355-
dc.identifier.scopusid2-s2.0-85021199366-
dc.identifier.bibliographicCitation한국정밀공학회지, v.34, no.5, pp.355 - 362-
dc.relation.isPartOf한국정밀공학회지-
dc.citation.title한국정밀공학회지-
dc.citation.volume34-
dc.citation.number5-
dc.citation.startPage355-
dc.citation.endPage362-
dc.type.rimsART-
dc.type.docType정기학술지(Article(Perspective Article포함))-
dc.identifier.kciidART002220190-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorData analytics-
dc.subject.keywordAuthorEnergy prediction-
dc.subject.keywordAuthorMachine tool-
dc.subject.keywordAuthorMachine-learning-
dc.subject.keywordAuthorMTConnect-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07159344&language=ko_KR&hasTopBanner=true-
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