Process layout
Process Overview
This palletizing automation solution uses the Hyundai Robotics HH050 and Mech-Mind 3D vision to detect mixed-size boxes, align them by size, and automatically stack them onto pallets. By leveraging a cost-effective 3D vision system, the cell can reliably palletize even when cartons of varying dimensions are mixed in the flow, ensuring stable operation.
Components
| Robot | Mech-Mind Mech-Eye Laser L (Industrial 3D camera) FOV: 1250 × 1460 @ 1.5 m; 2500 × 2890 @ 3 m Resolution: 2048 × 1536 (3 MP) Accuracy: 1.0 mm @ 2 m Scan time: 0.9–1.3 s Recommended scanning distance: 1.5–3 m Mech-Viz Intelligent Programming Environment: robot programming tool Hyundai Robotics HDR50-22 (HH050) Repeatability: ±0.06 mm |
|---|---|
| Peripherals | Tooling Vacuum gripper 3D Vision Mech-Eye Laser L (FOV: 1250 × 1460 @ 1.5 m; 2500 × 2890 @ 3 m, Resolution: 2048 × 1536 (3 MP), Accuracy: 1.0 mm @ 2 m, Scan time: 0.9–1.3 s, Recommended scanning distance: 1.5–3 m, Mech-Viz Intelligent Programming Environment: robot programming tool) Peripheral Equipment Robot base Vision mounting stand Box infeed stand Pallet fixing guide |
Workflow
| STEP 1. | Scan available pallet stacking space using 3D vision |
|---|---|
| STEP 2. | Pick each box and place it into the remaining pallet space based on its size |
| STEP 3. | Repeat until palletizing is complete |
Features
(Hyundai Robotics) Holds the #1 domestic market share with a strong sales and service network in Korea.
Since entering the domestic robot business in 1984, has secured a broad portfolio of solutions and product lineups.
Can deliver customer-tailored solutions through end-to-end execution across robot manufacturing, engineering, and installation.
Handles high payloads and a wide working envelope.
Payload: 50 kg; Reach: 2,239 mm
A single robot can handle most logistics box-handling tasks.
A reasonably priced 3D vision solution starting in the low KRW 20 million range.
Deep-learning-based 3D object recognition provides strong detection performance across a wide variety of objects.
Maintains reliable recognition even with strong reflections (e.g., from tape) or dark-colored products.
High capability to distinguish individual boxes even when cartons are tightly packed together.
Easy motion planning for collision avoidance and dense stacking.
Wide-area recognition supports palletizing tasks with stacking heights above 2 m.
Results
| Key Benefits | Reduced staffing requirements for box palletizing operations. |
|---|---|
| Client Feedback | In manual palletizing, operators had to repeatedly adjust and rework stacks to build tightly packed pallets with the robot cell, we were able to achieve satisfactory dense stacking as well. |
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