Exploring augmented reality for worker assistance versus training. (October 2021)
- Record Type:
- Journal Article
- Title:
- Exploring augmented reality for worker assistance versus training. (October 2021)
- Main Title:
- Exploring augmented reality for worker assistance versus training
- Authors:
- Moghaddam, Mohsen
Wilson, Nicholas C.
Modestino, Alicia Sasser
Jona, Kemi
Marsella, Stacy C. - Abstract:
- Abstract: This paper aims at advancing the fundamental understanding of the affordances of Augmented Reality (AR) as a workplace-based learning and training technology in supporting manual or semi-automated manufacturing tasks that involve both complex manipulation and reasoning. Between-subject laboratory experiments involving 20 participants are conducted on a real-life electro-mechanical assembly task to investigate the impacts of various modes of information delivery through AR compared to traditional training methods on task efficiency, number of errors, learning, independence, and cognitive load. The AR application is developed in Unity and deployed on HoloLens 2 headsets. Interviews with experts from industry and academia are also conducted to create new insights into the affordances of AR as a training versus assistive tool for manufacturing workers, as well as the need for intelligent mechanisms that enable adaptive and personalized interactions between workers and AR. The findings indicate that despite comparable performance between the AR and control groups in terms of task completion time, learning curve, and independence from instructions, AR dramatically decreases the number of errors compared to traditional instruction, which is sustained after the AR support is removed. Several insights drawn from the experiments and expert interviews are discussed to inform the design of future AR technologies for both training and assisting incumbent and futureAbstract: This paper aims at advancing the fundamental understanding of the affordances of Augmented Reality (AR) as a workplace-based learning and training technology in supporting manual or semi-automated manufacturing tasks that involve both complex manipulation and reasoning. Between-subject laboratory experiments involving 20 participants are conducted on a real-life electro-mechanical assembly task to investigate the impacts of various modes of information delivery through AR compared to traditional training methods on task efficiency, number of errors, learning, independence, and cognitive load. The AR application is developed in Unity and deployed on HoloLens 2 headsets. Interviews with experts from industry and academia are also conducted to create new insights into the affordances of AR as a training versus assistive tool for manufacturing workers, as well as the need for intelligent mechanisms that enable adaptive and personalized interactions between workers and AR. The findings indicate that despite comparable performance between the AR and control groups in terms of task completion time, learning curve, and independence from instructions, AR dramatically decreases the number of errors compared to traditional instruction, which is sustained after the AR support is removed. Several insights drawn from the experiments and expert interviews are discussed to inform the design of future AR technologies for both training and assisting incumbent and future manufacturing workers on complex manipulation and reasoning tasks. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 50(2021)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 50(2021)
- Issue Display:
- Volume 50, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 50
- Issue:
- 2021
- Issue Sort Value:
- 2021-0050-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-10
- Subjects:
- Augmented reality -- Electro-mechanical assembly -- Workforce training -- Workplace-based learning
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2021.101410 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 19711.xml