Recently, the demand for renewable energy and electric vehicles has increased significantly for sustainable growth. Busbars are essential for electric vehicles, and the current busbar production process causes worker fatigue and musculoskeletal strain due to manual visual inspection and heavy box transportation, and product quality varies depending on the worker's skill level. To solve this problem, this paper proposes an automation system utilizing multi-axis robots and vision inspection technology. After the introduction of the automation system, productivity increased by 20.8%, the defect rate decreased by 19.1%, and labor costs were reduced by 66.7%. These results show that the automation system improves production efficiency, improves product quality, and increases economic benefits. This study suggests the possibility of automation that can simultaneously improve productivity and quality in the electric vehicle battery manufacturing process, and provides important basic data for optimizing future manufacturing practices.

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Research on Methods of Automatic Inspection System for Inspecting Busbar

  • So-Young Kwon,
  • Young-Hyung Kim,
  • Jong-Ik Park,
  • Hyeon-Chan Seong

摘要

Recently, the demand for renewable energy and electric vehicles has increased significantly for sustainable growth. Busbars are essential for electric vehicles, and the current busbar production process causes worker fatigue and musculoskeletal strain due to manual visual inspection and heavy box transportation, and product quality varies depending on the worker's skill level. To solve this problem, this paper proposes an automation system utilizing multi-axis robots and vision inspection technology. After the introduction of the automation system, productivity increased by 20.8%, the defect rate decreased by 19.1%, and labor costs were reduced by 66.7%. These results show that the automation system improves production efficiency, improves product quality, and increases economic benefits. This study suggests the possibility of automation that can simultaneously improve productivity and quality in the electric vehicle battery manufacturing process, and provides important basic data for optimizing future manufacturing practices.