File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.conferencePlace US -
dc.citation.conferencePlace Washington -
dc.citation.endPage 1029 -
dc.citation.startPage 1024 -
dc.citation.title 2014 IEEE International Conference on Big Data, IEEE Big Data 2014 -
dc.contributor.author Song, Minseok -
dc.contributor.author Yang, Hanna -
dc.contributor.author Park, Minjeong -
dc.contributor.author Cho, Minsu -
dc.contributor.author Kim, Seongjoo -
dc.date.accessioned 2023-12-19T23:10:12Z -
dc.date.available 2023-12-19T23:10:12Z -
dc.date.created 2015-02-26 -
dc.date.issued 2014-10-27 -
dc.description.abstract Interests in manufacturing process management and analysis are increasing, but it is difficult to conduct process analysis due to the increase of manufacturing data. Therefore, we suggest a manufacturing data analysis system that collects event logs from so-called big data and analyzes the collected logs with process mining. There are two kinds of big data generated from manufacturing processes, structured data and unstructured data. Usually, manufacturing process analysis is conducted by using only structured data, however the proposed system uses both structured and unstructured data for enhancing the process analysis results. The system automatically discovers a process model and conducts various performance analysis on the manufacturing processes. -
dc.identifier.bibliographicCitation 2014 IEEE International Conference on Big Data, IEEE Big Data 2014, pp.1024 - 1029 -
dc.identifier.doi 10.1109/BigData.2014.7004336 -
dc.identifier.scopusid 2-s2.0-84988240403 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/46702 -
dc.identifier.url http://ieeexplore.ieee.org/xpl/abstractAuthors.jsp?arnumber=7004336 -
dc.language 영어 -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title A system architecture for manufacturing process analysis based on big data and process mining techniques -
dc.type Conference Paper -
dc.date.conferenceDate 2014-10-27 -

qrcode

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