WSC-MD30

PRODUCT INTRODUCTION

Collaborative palletizing robots are intelligent robots that work closely with human workers to improve production efficiency and flexibly adapt to different tasks. They are safely equipped with sensors and can learn and sense the environment autonomously. They are widely used in production lines in many industries such as cartons, medicine, and food. They revolutionize the intelligence of production lines and create a safer and more efficient working environment for workers.

WSC-MD30 Details

Product Details

Collaborative palletizing robots are intelligent robots that work closely with human workers to improve production efficiency and flexibly adapt to different tasks. They are safely equipped with sensors and can learn and sense the environment autonomously. They are widely used in production lines in many industries such as cartons, medicine, and food. They revolutionize the intelligence of production lines and create a safer and more efficient working environment for workers.

Widely used: widely used in food, medicine, 3C, daily chemicals, printing and other industries

Safe and stable: Industrial-grade force control sensor, with high reliability and safety; supports 10-level collision detection and sensor safety detection; safety functions will not be lost in the event of a single failure

Flexible deployment: integrated design, light and flexible, small footprint; new task settings for workstation deployment are simple and fast with high efficiency

Simple programming: Graphical programming, simple and efficient, you can easily use the robot without being proficient in programming languages. You can master the programming method in half an hour and complete simple programming in one hour.

Flexible production: Rapid switching between multiple functional scenarios, flexible production can be achieved through human-machine collaboration, dual-machine collaboration, multi-machine collaboration, etc.

Economical and practical: The investment cost can be recovered within 6-12 months on average.