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- Publisher Website: 10.1016/j.autcon.2020.103355
- Scopus: eid_2-s2.0-85088397028
- WOS: WOS:000579044100011
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Article: Adopting lean thinking in virtual reality-based personalized operation training using value stream mapping
Title | Adopting lean thinking in virtual reality-based personalized operation training using value stream mapping |
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Authors | |
Keywords | Lean Personalized training Productivity Value stream mapping Virtual reality |
Issue Date | 2020 |
Citation | Automation in Construction, 2020, v. 119, article no. 103355 How to Cite? |
Abstract | Lean thinking has been proven effective in helping practitioners identify and eliminate wastes during engineering operations. However, systematic instructional mechanisms and training protocols based on individual trainee's performance are insufficient in existing training to define value-added activities for further productivity improvement in a training environment. This study aims to investigate how value stream mapping (VSM), as a lean tool, can be applied to help improve operation training performances through an immersive virtual reality (VR)-based personalized training program. A before–after experiment based on a virtual scaffolding erection scenario is established to simulate the training process. The training performance resulting from the VSM-based VR approach is compared with conventional VR training. Comparative results indicate that the waste time and errors reduce significantly. Compared with the conventional method, the overall productivity improvement of the erection process using VSM-based VR training is 12%. This demonstrates that integrating lean thinking into the operation training process can be a more effective approach for VR-based personalized operation training, provided that appropriate instructions are implemented. |
Persistent Identifier | http://hdl.handle.net/10722/326230 |
ISSN | 2023 Impact Factor: 9.6 2023 SCImago Journal Rankings: 2.626 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wang, Peng | - |
dc.contributor.author | Wu, Peng | - |
dc.contributor.author | Chi, Hung Lin | - |
dc.contributor.author | Li, Xiao | - |
dc.date.accessioned | 2023-03-09T09:59:04Z | - |
dc.date.available | 2023-03-09T09:59:04Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Automation in Construction, 2020, v. 119, article no. 103355 | - |
dc.identifier.issn | 0926-5805 | - |
dc.identifier.uri | http://hdl.handle.net/10722/326230 | - |
dc.description.abstract | Lean thinking has been proven effective in helping practitioners identify and eliminate wastes during engineering operations. However, systematic instructional mechanisms and training protocols based on individual trainee's performance are insufficient in existing training to define value-added activities for further productivity improvement in a training environment. This study aims to investigate how value stream mapping (VSM), as a lean tool, can be applied to help improve operation training performances through an immersive virtual reality (VR)-based personalized training program. A before–after experiment based on a virtual scaffolding erection scenario is established to simulate the training process. The training performance resulting from the VSM-based VR approach is compared with conventional VR training. Comparative results indicate that the waste time and errors reduce significantly. Compared with the conventional method, the overall productivity improvement of the erection process using VSM-based VR training is 12%. This demonstrates that integrating lean thinking into the operation training process can be a more effective approach for VR-based personalized operation training, provided that appropriate instructions are implemented. | - |
dc.language | eng | - |
dc.relation.ispartof | Automation in Construction | - |
dc.subject | Lean | - |
dc.subject | Personalized training | - |
dc.subject | Productivity | - |
dc.subject | Value stream mapping | - |
dc.subject | Virtual reality | - |
dc.title | Adopting lean thinking in virtual reality-based personalized operation training using value stream mapping | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.autcon.2020.103355 | - |
dc.identifier.scopus | eid_2-s2.0-85088397028 | - |
dc.identifier.volume | 119 | - |
dc.identifier.spage | article no. 103355 | - |
dc.identifier.epage | article no. 103355 | - |
dc.identifier.isi | WOS:000579044100011 | - |