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dc.contributor.authorPark, Ji-Hyung-
dc.contributor.authorSeo, Kwang-Kyu-
dc.date.accessioned2024-01-21T03:31:43Z-
dc.date.available2024-01-21T03:31:43Z-
dc.date.created2021-09-01-
dc.date.issued2006-04-
dc.identifier.issn1474-0346-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/135638-
dc.description.abstractIn a competitive and globalized business environment, the need for the green products becomes stronger. To meet these trends, environmental impact assessment besides delivery, cost and quality of products should be considered as an important factor in new product development stage. In this paper, a knowledge-based approximate life cycle assessment system (KALCAS) is developed to assess the environmental impacts of product design alternatives. It aims at improving the environmental efficiency of a product using artificial neural networks, which consist of high-level product attributes and LCA results. The overall framework of a collaborative design environment involving KALCAS is proposed, using engineering solution CO (TM) based on the distributed object-based modeling and evaluation (DOME) system. This framework allows users to access the product data and other related information on a wide variety of application. This paper explores an approximate LCA of product design alternatives represented by solid models in a collaborative design environment. (c) 2006 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCI LTD-
dc.titleA knowledge-based approximate life cycle assessment system for evaluating environmental impacts of product design alternatives in a collaborative design environment-
dc.typeArticle-
dc.identifier.doi10.1016/j.aei.2005.09.003-
dc.description.journalClass1-
dc.identifier.bibliographicCitationADVANCED ENGINEERING INFORMATICS, v.20, no.2, pp.147 - 154-
dc.citation.titleADVANCED ENGINEERING INFORMATICS-
dc.citation.volume20-
dc.citation.number2-
dc.citation.startPage147-
dc.citation.endPage154-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000237760300005-
dc.identifier.scopusid2-s2.0-33645846279-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Multidisciplinary-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.type.docTypeArticle; Proceedings Paper-
dc.subject.keywordAuthorartificial neural networks-
dc.subject.keywordAuthordesign alternatives-
dc.subject.keywordAuthorcollaborative design environment-
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KIST Article > 2006
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