ISMAR Poster

1. 50%
of all answers of the survey regarding the
general perception of AR-assistance in
assembly were rated “very good” to “good”
Also the mean assembly time was lower with AR assistance than without.
RESULTS AND DISCUSSION
A User Study on AR-assisted Industrial Assembly
Florian Schuster, Uwe Sponholz, Bastian Engelmann, Jan Schmitt*
FHWS University of Applied Sciences Würzburg-Schweinfurt | Institute Digital Engineering | idee.fhws.de
CURRENT SITUATION
• Industrial like assembly scenario in the FHWS c-Factory
• App development for AR-assistance with Microsoft HoloLens
• Toy truck assembly with/without AR-assistance
by a group of n=28 participants
• Study on AR acceptance with a survey after
assembling the trucks
• Additional evaluation of the assembly time
• Empirical data collection to validate the
simplified acceptance model
In order to evaluate the acceptance of AR for assembly scenarios systematically,
a simplified model is developed considering existing general approaches (TAM
and UTAUT) of acceptance. This model makes the acceptance by production
employees measurable and statistically evaluable. Subsequently, a study is
conducted to test formulated hypotheses.
Acceptance model
The acceptance model can be used to
explain certain constructs after the
described change and adaptation.
The empirically collected data in c-
Factory explain 74.8 % of the variance
in user behavior. The significance
measure is at the 0.1 level.
Research Hypotheses and their influence (?) on the acceptance model
H1: The intention of use has a positive influence on the usage behavior (+)
H2: Voluntariness has a positive influence on the intention to use (+)
H3: The image of a technology has a positive influence on the intention of use (+)
H4: Computer anxiety negatively influences the intention to use (-)
H5: The computer self-efficacy positively influences the intention of use (+)
H6: Facilitating circumstances influence the intention to use positively (+)
H7: The social impact has a positive influence on the intention of use (+)
OBJECTIVES METHODOLOGY AND SYSTEMATICS
The utilization of modern assistance system e.g. Augmented Reality
(AR) has reached into industrial assembly scenarios. Beside the
technical realization of AR assistance in the assembly scene the worker
must accept the new technology. Only both, user acceptance and
technical user-interface design leads to an optimized overall system.
A proprietary model for acceptance measurement is developed, which includes and
synthesizes previous models (TAM and UTAUT) and simplifies them considerably for the
purpose of industrial assembly. Following, a laboratory experiment is set-up in the FHWS
c-Factory, which is a smart, IoT-based production environment. A survey and an assembly
cycle time measurement is conducted to collect data to characterize AR assistance. The
study participants assemble a toy truck once without and once with AR support.
Insights to
AR-assisted
toy truck
assembly
* corresponding author
Institute Digital Engineering
jan.schmitt@fhws.de
+49 (0) 9721-8594