Projection-Based Augmented Reality for Lean Drone Assembly: Reducing Waste and Enhancing Learning Efficiency

This study explores the integration of Augmented Reality (AR) into Lean Manufacturing practices to enhance manual drone assembly training. Leveraging lean principles such as Jidoka, standardized work, and visual management, a projection-based AR system was developed featuring real-time task guidance, gesture control, and voice interaction. A structured methodology: Set up, Testing and Evaluation, was used to compare the performance of AR-assisted and traditional non-AR training. Participants across both conditions completed identical tasks, with results revealing that AR users completed tasks 22.3% faster and committed no defects, compared to several errors in the control group. Furthermore, learning curve analysis showed a 4.1% greater improvement in skill acquisition among AR users. By embedding lean tools directly into the AR interface, the system reduced waste related to waiting, over-processing, and errors, while enabling scalable, hands-free instruction. Although Vision-Language Model (VLM) integration remains a future enhancement, the current implementation demonstrates AR’s capacity to streamline training, improve consistency, and support workforce development within Industry 4.0-aligned environments.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.378
Primary Topic
Augmented Reality Applications
Type
article
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article

Projection-Based Augmented Reality for Lean Drone Assembly: Reducing Waste and Enhancing Learning Efficiency

Wessam Hamid, Rafiq Ahmad, M. A. G. Khan, David Gee et al.
Procedia Computer Science
Augmented Reality Applications
article

Projection-Based Augmented Reality for Lean Drone Assembly: Reducing Waste and Enhancing Learning Efficiency

Wessam Hamid, Rafiq Ahmad, M. A. G. Khan, David Gee, José Miguel Figarola
article en

Abstract

This study explores the integration of Augmented Reality (AR) into Lean Manufacturing practices to enhance manual drone assembly training. Leveraging lean principles such as Jidoka, standardized work, and visual management, a projection-based AR system was developed featuring real-time task guidance, gesture control, and voice interaction. A structured methodology: Set up, Testing and Evaluation, was used to compare the performance of AR-assisted and traditional non-AR training. Participants across both conditions completed identical tasks, with results revealing that AR users completed tasks 22.3% faster and committed no defects, compared to several errors in the control group. Furthermore, learning curve analysis showed a 4.1% greater improvement in skill acquisition among AR users. By embedding lean tools directly into the AR interface, the system reduced waste related to waiting, over-processing, and errors, while enabling scalable, hands-free instruction. Although Vision-Language Model (VLM) integration remains a future enhancement, the current implementation demonstrates AR’s capacity to streamline training, improve consistency, and support workforce development within Industry 4.0-aligned environments.

Procedia Computer ScienceVol. 277
University of Alberta (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Augmented Reality Applications
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Projection-Based Augmented Reality for Lean Drone Assembly: Reducing Waste and Enhancing Learning Efficiency — Wessam Hamid, Rafiq Ahmad, et al. · Procedia Computer Science (2026) | TGRS Research Map | TGRS