Augmented Reality for Precast Concrete Manufacturing: A Comparative Study to Evaluate Positioning Accuracy and Efficiency

Augmented reality (AR) has gained popularity in academia and industry, with previous studies highlighting its advantages in facilitating architectural design, construction management, and site safety. However, limited research has explored the use and effects of AR in off-site construction. This study develops a handheld video see-through AR application to facilitate positioning tasks in manufacturing precast concrete panels. The study first compares two common AR tracking methods, image and plane tracking, in positioning tasks. Results showed that image tracking is more suitable for a close-range task on formworks, such as installing embedded components, due to its flexibility in realigning virtual models. Plane tracking, on the other hand, is better for inspecting the entire wall due to richer texture information from the camera’s view. Next, this study presents a between-subject experiment involving 72 participants to assess the efficiency of AR in positioning tasks, with a control group using a traditional tape measure and an experimental group using the AR application. The findings demonstrated that AR reduces task completion time and mental and physical load. However, positioning accuracy and size perception with handheld AR are not as reliable as the traditional method due to tracking inaccuracies and view angle issues. Notably, although improving accuracy with a tape measure requires additional time, AR shows potential to overcome the traditional speed–accuracy trade-off. The results suggest that AR performance relies more heavily on system-level factors, such as tracking and registration accuracy, rather than human factors that typically introduce error in traditional methods. This study demonstrates the empirical evidence of using AR in positioning tasks for precast concrete manufacturing.

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Publication Details

Journal
Journal of Computing in Civil Engineering
Published
2026-06-09
DOI
https://doi.org/10.1061/jccee5.cpeng-7211
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
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article

Augmented Reality for Precast Concrete Manufacturing: A Comparative Study to Evaluate Positioning Accuracy and Efficiency

Brian H.W. Guo, Mostafa Babaeian Jelodar, Zhidong Xu, Vicente A. González et al.
Journal of Computing in Civil Engineering
BIM and Construction Integration
article

Augmented Reality for Precast Concrete Manufacturing: A Comparative Study to Evaluate Positioning Accuracy and Efficiency

Brian H.W. Guo, Mostafa Babaeian Jelodar, Zhidong Xu, Vicente A. González, Zhenan Feng
article en

Abstract

Augmented reality (AR) has gained popularity in academia and industry, with previous studies highlighting its advantages in facilitating architectural design, construction management, and site safety. However, limited research has explored the use and effects of AR in off-site construction. This study develops a handheld video see-through AR application to facilitate positioning tasks in manufacturing precast concrete panels. The study first compares two common AR tracking methods, image and plane tracking, in positioning tasks. Results showed that image tracking is more suitable for a close-range task on formworks, such as installing embedded components, due to its flexibility in realigning virtual models. Plane tracking, on the other hand, is better for inspecting the entire wall due to richer texture information from the camera’s view. Next, this study presents a between-subject experiment involving 72 participants to assess the efficiency of AR in positioning tasks, with a control group using a traditional tape measure and an experimental group using the AR application. The findings demonstrated that AR reduces task completion time and mental and physical load. However, positioning accuracy and size perception with handheld AR are not as reliable as the traditional method due to tracking inaccuracies and view angle issues. Notably, although improving accuracy with a tape measure requires additional time, AR shows potential to overcome the traditional speed–accuracy trade-off. The results suggest that AR performance relies more heavily on system-level factors, such as tracking and registration accuracy, rather than human factors that typically introduce error in traditional methods. This study demonstrates the empirical evidence of using AR in positioning tasks for precast concrete manufacturing.

Journal of Computing in Civil EngineeringVol. 40(5)
University of Alberta (CA), University of Canterbury (NZ), Massey University (NZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 9%
BIM and Construction Integration
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