Abstract
A manual assembly has an important role in the manufacturing of products with small lot sizes and high variation. Becoming skilled manual labor requires knowledge transfers offered by human experts through a training process. To reduce the dependency of human experts, this paper introduces a framework called “Virtual Trainer” that incorporates the current state of the art marker-less RGB human pose estimation, activity detection for assembly step recognition, and training feedback through a multi-media presentation includes score evaluation and semantic description of trainee performance. Furthermore, the detailed transcript of each step and 3-D visualization compares to ideal movements also presented. The experimental design for evaluating the effectiveness and hypothesis is given.
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Singhaphandu, R., Huynh, VN., Pannakkong, W. (2020). Analysis and Feedback of Movement in Manual Assembly Process. In: Spohrer, J., Leitner, C. (eds) Advances in the Human Side of Service Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1208. Springer, Cham. https://doi.org/10.1007/978-3-030-51057-2_37
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DOI: https://doi.org/10.1007/978-3-030-51057-2_37
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