Content area

Abstract

Smart factory is a manufacturing facility equipped with modern information and communication technologies, and it is considered as an innovative manufacturing paradigm in the era of 4th industrial revolution. However, conventional technology-oriented smart factory education programs often focus on specific technologies, and many undergraduates and practitioners have trouble in understanding concepts, elements and features of entire smart factory system. In order to address this problem, this paper proposes a cyber learning factory for operations management-oriented smart factory education and training, developed by applying 3D factory simulation software, FlexSim. The cyber learning factory is implemented by incorporating three key components, information system, database and virtual manufacturing facility provided by 3D factory simulation software such as FlexSim. Since overall smart factory system can be virtually implemented in a single cyber space, the cyber learning factory can provide hands-on experiences for understanding, designing and optimizing smart factory. Consequently, the cyber learning factory can be used to train both operations managers of manufacturing companies and information systems architects of IT companies, and this paper will provide significant insights into the operations management-oriented smart factory education and training.

Details

Title
Application of FlexSim software for developing cyber learning factory for smart factory education and training
Author
Kim, Jun Woo 1 ; Park, Jin Sung 1 ; Kim, Soo Kyun 2 

 Dong-A University, Department of Industrial and Management Systems Engineering, Busan, South Korea (GRID:grid.255166.3) (ISNI:0000 0001 2218 7142) 
 Paichai University, Department of Game Engineering, Daejeon, South Korea (GRID:grid.412439.9) (ISNI:0000 0004 0533 1423) 
Pages
16281-16297
Publication year
2020
Publication date
Jun 2020
Publisher
Springer Nature B.V.
ISSN
13807501
e-ISSN
15737721
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2289865626
Copyright
© Springer Science+Business Media, LLC, part of Springer Nature 2019.