Dynamic Estimation Model for Collaboration Potential in Cloud Manufacturing based on Markov Random Fields
DC Field | Value | Language |
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dc.contributor.author | Ahn, Gilseung | - |
dc.contributor.author | Hur, Sun | - |
dc.date.accessioned | 2021-06-22T09:04:10Z | - |
dc.date.available | 2021-06-22T09:04:10Z | - |
dc.date.issued | 2020-06 | - |
dc.identifier.issn | 1598-7248 | - |
dc.identifier.issn | 2234-6473 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1080 | - |
dc.description.abstract | In cloud manufacturing (CM), various manufacturing enterprises collaborate to produce highly customized manufacturing services with the support of cloud computing. Since the collaboration between enterprises in CM is one of the main factors in determining degrees of customer satisfaction and resource waste, it is important to estimate the collaboration potential between enterprises. The collaboration potential between enterprises in the CM is defined as the expected customer satisfaction for the manufacturing service and the product that the manufacturer provides through collaboration. This paper develops a Markov random field (MRF) model to estimate the collaboration potential between enterprises based on their rating histories in the CM. From the illustrative example, it is verified that the proposed model can be applied to solve a task allocation problem considering relationships among enterprises in CM. | - |
dc.format.extent | 7 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | KOREAN INST INDUSTRIAL ENGINEERS | - |
dc.title | Dynamic Estimation Model for Collaboration Potential in Cloud Manufacturing based on Markov Random Fields | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.doi | 10.7232/iems.2020.19.2.301 | - |
dc.identifier.scopusid | 2-s2.0-85090892795 | - |
dc.identifier.wosid | 000547461200001 | - |
dc.identifier.bibliographicCitation | INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS, v.19, no.2, pp 301 - 307 | - |
dc.citation.title | INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS | - |
dc.citation.volume | 19 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 301 | - |
dc.citation.endPage | 307 | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002600056 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.subject.keywordAuthor | Cloud Manufacturing | - |
dc.subject.keywordAuthor | Collaboration Potential | - |
dc.subject.keywordAuthor | Markov Random Field | - |
dc.subject.keywordAuthor | Task Allocation Problem | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE09361095 | - |
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