Full metadata record

DC Field Value Language
dc.contributor.authorPark, BT-
dc.contributor.authorPark, MW-
dc.contributor.authorKim, SK-
dc.date.accessioned2024-01-21T11:33:26Z-
dc.date.available2024-01-21T11:33:26Z-
dc.date.created2021-09-05-
dc.date.issued2001-12-
dc.identifier.issn0268-3768-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/139989-
dc.description.abstractIn metal cutting processes, cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product. This paper presents a new methodology for continual improvement of cutting conditions. It is called GELCC (generation and evolutionary learning of cutting conditions). GELCC is a key component of an operation planning system for milling operations. It performs the following three functions. 1. The modification of recommended cutting conditions obtained from a machining data handbook. 2. The incremental learning of obtained cutting conditions using fuzzy ARTMAP neural networks. 3. The substitution of better cutting conditions for those learned previous by a proposed replacement algorithm. Various simulations illustrate the performance of GELCC. and then the simulation results for a given part are provided and discussed.-
dc.languageEnglish-
dc.publisherSPRINGER-VERLAG LONDON LTD-
dc.subjectOPTIMIZATION-
dc.subjectSYSTEM-
dc.subjectART-
dc.titleGeneration and evolutionary learning of cutting conditions for milling operations-
dc.typeArticle-
dc.identifier.doi10.1007/s001700170098-
dc.description.journalClass1-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, v.17, no.12, pp.870 - 880-
dc.citation.titleINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY-
dc.citation.volume17-
dc.citation.number12-
dc.citation.startPage870-
dc.citation.endPage880-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000169770700002-
dc.identifier.scopusid2-s2.0-0034802949-
dc.relation.journalWebOfScienceCategoryAutomation & Control Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.relation.journalResearchAreaAutomation & Control Systems-
dc.relation.journalResearchAreaEngineering-
dc.type.docTypeArticle-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusART-
dc.subject.keywordAuthorcomputer-aided process planning (CAPP)-
dc.subject.keywordAuthorcutting conditions-
dc.subject.keywordAuthorneural network-
dc.subject.keywordAuthoroperation planning-
Appears in Collections:
KIST Article > 2001
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE