Using High Precision Robot Arm to Create Intelligent Production Line for Charging Station
Under the large context of “Double Carbon”, the new energy vehicle has got fast development. As the powerful supporting industry, the intelligent charging station has a broad development prospect. However, the current workshop is difficult to meet the requirement for current increasing, it is urgent to improve the current intelligent production system by high precision robot arm.
Under the cooperation and delivery in time by Huiling Tech, the first intelligent production line for charging station has started to work in Shanghai.
Under this improvement of production line by Huiling Tech, it has some advantages from the aspect of technology.
1)Feeding without carton.
2)The MES tracing system which is developed HITBOT Robot.
3)Use HITBOT 6-axis robot arm to realize visual inspection.
After improvement of this intelligent charging station, the design speed had been reached in the first trial-production, it has improved about more 50m/min than before. With the improving, the estimating max production speed can be up to 400m/min.
Feeding without Carton
HITBOT has divided carton into pre-folding and final box, taking the pre-folding package as the basement, pushing products into the package, then to sealing the carton, which has advoid products having any vibration inside the carton.
MES Tracing System
Many tasks can be accurately completed at the same time, such as achievement, arrangement, delivery, collection, count, analytics, feedback. Use data management to improve product performance, to meet customer’s special requirement.
Use HITBOT 6-axis robot arm to realize visual detection
HITBOT high precision robot arm offers a double-visual 6-axis robot system. It connects the left and right CCD cameras to capture images. The data is then delivered to a computer for analysis. This process provides accurate positioning data for cargo. It also saves data standards and measurement values. Digital positioning statistics significantly improve object detection precision.