Abstract
In schools, due to narrow processing spaces and limited machines, students can only understand the operation and processing procedures of computer numerical control (CNC) machines through the unilateral operation and explanation of technicians or by group operation or observations in turn. Under the existing teaching restrictions, students can only obtain limited operating experience through the partial processing steps of group machine operation. Students are therefore not familiar with the operation of the machines and it is difficult to complete consistent operation procedures, resulting in fear and uncertainty in the operation of the machines. Therefore, this research used augmented reality (AR) technology to simulate the complete operation flow and processing information of CNC processing machines, and combined the practical teaching courses to deepen the students’ understanding of CNC machine operation.
In this study, a total of ten participants were recruited to conduct AR system operation experiments. The follow-up verification was conducted through real CNC machine operation and by filling in the System Usability Scale (SUS) to evaluate the experience feedback after using the AR-CNC training system. Finally, the results of this study showed that the AR-CNC training system could not only solve the problem of machining operation interruption caused by students’ rotating use of the CNC machine but also solve the hardware limitations of the actual machining space and the machine itself, so that every student could learn how to operate the CNC machine as if they were operating it in person.
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Acknowledgments
We are grateful to the Executive Yuan and Ministry of Science and Technology for funding under project No. MOST 107-2218-E-027-013-MY2.
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Lin, YT., Lee, IJ. (2020). Development of an Augmented Reality System Achieving in CNC Machine Operation Simulations in Furniture Trial Teaching Course. In: Chen, J.Y.C., Fragomeni, G. (eds) Virtual, Augmented and Mixed Reality. Industrial and Everyday Life Applications. HCII 2020. Lecture Notes in Computer Science(), vol 12191. Springer, Cham. https://doi.org/10.1007/978-3-030-49698-2_9
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DOI: https://doi.org/10.1007/978-3-030-49698-2_9
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