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In: ACM CHI Conference on Human Factors in Computing Systems (CHI 2020), Association for Computing Machinery

Augmented Reality Training for Industrial Assembly Work – Are Projection-based AR Assistive Systems an Appropriate Tool for Assembly Training?

Sebastian Büttner¹, Michael Prilla, Carsten Röcker²
Apr 2020

Augmented Reality (AR) systems are on their way to industrial application, e.g. projection-based AR is used to enhance assembly work. Previous studies showed advantages of the systems in permanent-use scenarios, such as faster assembly times. In this paper, we investigate whether such systems are suitable for training purposes. Within an experiment, we observed the training with a projection-based AR system over multiple sessions and compared it with a personal training and a paper manual training. Our study shows that projection-based AR systems offer only small benefits in the training scenario. While a systematic mislearning of content is prevented through immediate feedback, our results show that the AR training does not reach the personal training in terms of speed and recall precision after 24 hours. Furthermore, we show that once an assembly task is properly trained, there are no differences in the long-term recall precision, regardless of the training method.

Literatur Beschaffung: ACM CHI Conference on Human Factors in Computing Systems (CHI 2020), Association for Computing Machinery
@inproceedings{34,
author= {Büttner, Sebastian and Prilla, Michael and Röcker, Carsten},
title= {Augmented Reality Training for Industrial Assembly Work – Are Projection-based AR Assistive Systems an Appropriate Tool for Assembly Training?},
abstract= {Augmented Reality (AR) systems are on their way to industrial application, e.g. projection-based AR is used to enhance assembly work. Previous studies showed advantages of the systems in permanent-use scenarios, such as faster assembly times. In this paper, we investigate whether such systems are suitable for training purposes. Within an experiment, we observed the training with a projection-based AR system over multiple sessions and compared it with a personal training and a paper manual training. Our study shows that projection-based AR systems offer only small benefits in the training scenario. While a systematic mislearning of content is prevented through immediate feedback, our results show that the AR training does not reach the personal training in terms of speed and recall precision after 24 hours. Furthermore, we show that once an assembly task is properly trained, there are no differences in the long-term recall precision, regardless of the training method.},
booktitle= {ACM CHI Conference on Human Factors in Computing Systems (CHI 2020)},
year= {2020},
month= {Apr},
publisher= {Association for Computing Machinery},
address= {Honolulu, Hawaii, USA},
editor= {},
pages= {0},
organisation= {},
}

¹ Erstautoren
² Letztautoren