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자료유형
학술대회자료
저자정보
Yee Yeng Liau (Pusan National University) Kwangyeol Ryu (Pusan National University)
저널정보
대한산업공학회 대한산업공학회 추계학술대회 논문집 2021년 대한산업공학회 추계학술대회
발행연도
2021.11
수록면
711 - 718 (8page)

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The human-robot collaboration (HRC) is the main focus in Industry 5.0, which brings back humans to production. This study focuses on the novel application of the HRC system to improve the ergonomic risk and quality of the existing manual mold assembly. The execution of tasks assigned to robots is controlled by a human in most existing HRC systems. In other words, the robot is always waiting for the human command to execute the assigned tasks. Therefore, this study proposes a status-based task execution for HRC mold assembly operation to reduce the robot"s idle time and overall assembly time. We decompose the mold assembly operation into tasks, sub-tasks, and actions, then apply a Genetic Algorithm (GA) to assign each sub-task to humans and robots. We identify the manual sub-task status based on the executing action during the execution of the manual sub-tasks. Due to the limited assembly image dataset, we utilize a pre-trained YOLOv5l model to detect the sub-task status. Besides, we consider assembly position, components, and resource availability as conditions to determine early execution of the subsequent task based on the identified status. A robot"s idle time and overall assembly time can be reduced by allowing early sub-task execution because a robot can execute the task assigned before the human worker completes the executing manual sub-task. The outcome of this study contributes to the early task execution without human control during the collaboration between humans and robots.

목차

Abstract
1. Introduction
2. Background and Related Work
3. Status Recognition-based Task Execution
4. Experimental Result and Discussion
5. Conclusion and Future Works
References

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