Less is More! Support of Parallel and Time-critical Assembly Tasks with Augmented Reality
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Manual assembly tasks require workers to precisely assemble parts in 3D space in parallel steps. Often, additional time pressure further increases the complexity of these parallel tasks (e.g. in adhesive bonding processes). The performance in parallel tasks is heavily influenced by the capacity of the working memory, which is often overwhelmed if rules and states of too many tasks have to be remembered or perceived. Therefore, we propose to use Augmented Reality (AR) to investigate how visual assistance with parallel tasks can affect worker performance in time and spatial dependent process steps. In a user study, we compare three conditions: AR instructions presented (a) One task, (b) Two tasks, and (c) Four tasks per step on a tablet. For instructions we used selected work steps from a standardized adhesive bonding process as a representative for common time-critical assembly tasks. Our results show that instructions with multiple displayed tasks simultaneously per step can improve the process time but also increase the error rate and task load. The work instructions with less displayed tasks per work step showed better subjective results among participants, which may increase motivation, especially among less experienced workers. Our results help designers and developers to design assistance systems for time-critical and simultaneously executable assembly tasks, while considering process times, error rate and task load.
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Number of citations to item: 5
- Jannike Illing, Uwe Gruenefeld, Wilko Heuten (2024): Keep Track! Supporting Spatial Tasks with Augmented Reality Overviews, In: ACM Symposium on Spatial User Interaction, doi:10.1145/3677386.3682093
- Lilian Cristina Peixe, Salvador Agati, Marcelo Da Silva Hounsell (2023): Manual Assembly Augmented Reality Systems Implementation: A Systematic Literature Mapping, In: Symposium on Virtual and Augmented Reality, doi:10.1145/3625008.3625011
- Prameet Ranjan Jha, Valentina Di Pasquale, Jason J. Saleem, Xiaomei Wang (2024): Taxonomy of performance shaping factors in manufacturing: A systematic literature review, In: Human Factors and Ergonomics in Manufacturing & Service Industries 5(34), doi:10.1002/hfm.21036
- Jen-Shuo Liu, Portia Wang, Barbara Tversky, Steven Feiner (2022): Adaptive Visual Cues for Guiding a Bimanual Unordered Task in Virtual Reality, In: 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), doi:10.1109/ismar55827.2022.00059
- Isaiah Nassiuma, Yee Mey Goh, Ella-Mae Hubbard (2024): Positive and Negative Reinforcement Nudges for Human-Robot Collaboration using a Mixed Reality Interface, In: Proceedings of the European Conference on Cognitive Ergonomics 2024, doi:10.1145/3673805.3673844
