LEGO smart factory modeling for manufacturing systems engineering education제조 시스템 엔지니어링 교육을 위한 레고 스마트팩토리 모델링

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dc.contributor.advisorJang, Young Jae-
dc.contributor.advisor장영재-
dc.contributor.authorYosephine, Vina Sari-
dc.date.accessioned2021-05-12T19:42:39Z-
dc.date.available2021-05-12T19:42:39Z-
dc.date.issued2020-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=924234&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/284292-
dc.description학위논문(박사) - 한국과학기술원 : 산업및시스템공학과, 2020.8,[v, 91 p. :]-
dc.description.abstractEducation in manufacturing is critical in this new age of digital transformation. It is important to provide students with an understanding of how technologies can be used to achieve the goals of the smart factory, rather than merely teaching them a collection of technological skills. The Korea Advanced Institute of Science and Technology (KAIST) created a Smart Factory & Manufacturing Data Analytics Education Platform to effectively teach students about the digital transformation of manufacturing. The goal of the laboratory is to impart technological perspectives of the Smart Factory to students by integrating three perspectives - Manufacturing system-
dc.description.abstractData analytics-
dc.description.abstractAnalytical decision-making in manufacturing. The platform was designed with the foundation of distinct learning theories such as cognitive load theory, constructivism, and connectivism to ensure maximum delivery and pedagogical impact on students. In this study, we report the pedagogical implication and lessons learned from the education platform and provide a new direction and curriculum for smart factory education.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectSmart Factory▼aCurriculum Design▼aLEGO▼aManufacturing Systems Engineering▼aLaboratory-
dc.subject스마트 팩토리▼a커리큘럼 설계▼aLEGO▼a제조 시스템 공학▼a공학 교육-
dc.titleLEGO smart factory modeling for manufacturing systems engineering education-
dc.title.alternative제조 시스템 엔지니어링 교육을 위한 레고 스마트팩토리 모델링-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :산업및시스템공학과,-
dc.contributor.alternativeauthor요세핀, 비나 사리-
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