The vision-based high-speed tray placement machine is a core piece of automated equipment designed
for precision manufacturing, employing an "eye-hand collaboration" system. Specifically developed to a
ddress the pain points of high-speed, high-precision tray placement of small, loose materials and irregularly
shaped workpieces, it has been widely deployed in various industries, including electronic chips, precision
hardware, and baking. It can completely replace traditional manual tray placement, truly achieving unmann
ed operation across the entire process.
The core competitiveness of this equipment stems from the deep synergy between the vision recognition
system and the motion execution mechanism. Equipped with a global shutter industrial camera of 5 mega
pixels or higher, and a customized ring-shaped coaxial LED light source, it utilizes deep learning image reco
gnition algorithms to accurately determine the material's position, placement angle, and orientation within
milliseconds. Positioning accuracy reaches sub-pixel level, with overall errors strictly controlled within ±0.05
mm.
Some high-end models also employ a dual-vision architecture of "upper camera initial positioning + lower
camera on-the-fly correction," performing a secondary verification of the material's posture after grasping it,
eliminating misplacement and omissions at the source, ultimately achieving a tray placement yield of over
99.9%. The motion actuator utilizes a high-speed linear motor drive, paired with a high-rigidity imported
linear guide rail and a flexible suction nozzle design adaptable to different materials. With a servo response
speed of only 1 millisecond, it can automatically adjust the gripping force according to material characteri
stics, ensuring a high-speed operation of 60-120 pieces per minute while effectively preventing scratches
and wear on chip pins and precision parts.
To address the diverse material characteristics of different industries, the equipment can flexibly select
from various feeding solutions such as flexible vibratory feeders and linear vibratory feeders. Randomly
stacked materials are automatically aligned and directly fed to the vision recognition station, eliminating
the need for manual pre-sorting. The equipment's high flexibility and adaptability significantly reduce
changeover costs for enterprises: it supports the storage of over 99 product recipes, and switching between
different material specifications requires no hardware replacement; simply retrieving the corresponding
parameters through the human-machine interface allows for quick debugging. It is compatible with dozens
of different product categories, including chips, TF cards, Type-C accessories, and baked goods.
Meanwhile, the equipment features an automatic defective product identification function. The vision syste
m can simultaneously detect defects such as dirt and dimensional deviations in the material appearance,
automatically sorting unqualified materials into dedicated material boxes for easy traceability in subseque
nt processes. At the production line integration level, the high-speed vision-based palletizing machine can
seamlessly connect with upstream forming machines and PCB depaneling machines, and downstream test
ing equipment, tunnel furnaces, and other front- and back-end equipment to form a complete fully autom
ated production chain. The equipment's built-in automatic loading and unloading mechanism can stack
more than 30 empty pallets at a time, automatically completing palletizing after the pallets are full, elimina
ting the need for frequent manual replenishment. A single machine can replace 3-4 skilled operators, with a
maximum hourly capacity of 8,000-10,000 pieces. While significantly reducing labor costs, it completely avo
ids the problems of accuracy deviation and instability caused by manual palletizing, making it a core prefer
red equipment for small-sized bulk material palletizing processes in the current intelligent manufacturing
upgrade process.
