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- Title
Training Simulator for Manual Lathe Operation Using Motion Capture – Addition of Teaching Function and Evaluation of Training Effectiveness –.
- Authors
Hashimoto, Nobuyoshi
- Abstract
Numerous training simulators have been developed using virtual reality (VR) owing to their various advantages. Systems for training machine operations with physical movements face differences in the operational feel between actual and virtual machines. Moreover, virtual training is problematic in safety education because trainees in safe virtual environments can exhibit unsafe behavior in reality. To solve these problems, a previous study developed a virtual reality (VR) system to train a lathe operation with mixed reality using a motion capture system. This study included a function to teach the procedure and safety precautions for straight turning operations using a lathe. To evaluate the training effectiveness of this system, an experiment was conducted to compare learning using a video. Testees were divided into a simulator group, who learned with the system, and a video group, who learned with the video material. Work on the actual lathe by each testee after learning, was evaluated. Consequently, the actual work by the testees who used this system had fewer errors and shorter standstill times in which they attempted to recollect the next phase task. Although the number of trainees was small, this relationship had a statistical advantage. In the actual work, all the testees in the video group entered the danger area; however, only half of the testees in the simulator group entered the danger area. Therefore, a trainee using a simulator can remember the work process more reliably and accurately and perform it safely. Moreover, trainees who have undergone training several times should be able to perform actual work without making operational errors or engaging in unsafe behaviors.
- Subjects
TRAINING manuals; SYNTHETIC training devices; MIXED reality; LATHES; VIRTUAL machine systems; LATHE work; MOTION capture (Human mechanics)
- Publication
Journal of Robotics & Mechatronics, 2023, Vol 35, Issue 1, p145
- ISSN
0915-3942
- Publication type
Article
- DOI
10.20965/jrm.2023.p0145