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. |
Unauthorized copying or reproduction of any content on Marosol may violate the Unfair Competition Prevention Act and Copyright Act.
Recommended Solution
From Mixed Box Sorting to Palletizing with Hyundai Robotics' Industrial Robots! Automotive Parts Factory Automation
Real-world Case Study: Automotive Parts Factory Automates Shipping Process with Palletizing Robots | Daedong Door Implementation Story
Piece Picking using Yaskawa and Mech-Mind
This automation solution combines logistics and sorting automation by utilizing Mech-Mind 3D Vision and the Yaskawa GP8 robot to classify and transfer a diverse range of unstructured objects. By leveraging a highly cost-effective 3D vision system to recognize both the position and geometry of items, the robot can easily sort products even if their locations change or multiple types of objects are mixed together. This is the ideal solution for environments with diverse workpieces or for companies looking to automate manual tasks with minimal changes to their existing workspace. The project was implemented to automate order picking in fulfillment centers and eliminate the manual labor required for sorting individual packaged goods. Furthermore, it aims to achieve high-efficiency sorting for unstructured and mixed-SKU inventory. *Note: This content is based on a demo; actual deployment may require additional equipment based on specific customer requirements.
Part Transfer using Autonomous Lift-Conveyor
This logistics robot solution utilizes an autonomous lift-conveyor to perform material transport tasks between manufacturing processes. By using vision technology to recognize workpiece information, the system can stack items in matching locations based on their category. Conversely, when a work command is received, it can retrieve necessary items from storage racks and move them to the discharge position. The integration of a linear track allows the robot to cover a wide operational area, enabling comprehensive inbound/outbound inventory management.
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. |
Unauthorized copying or reproduction of any content on Marosol may violate the Unfair Competition Prevention Act and Copyright Act.
Recommended Solution
From Mixed Box Sorting to Palletizing with Hyundai Robotics' Industrial Robots! Automotive Parts Factory Automation
Real-world Case Study: Automotive Parts Factory Automates Shipping Process with Palletizing Robots | Daedong Door Implementation Story
Piece Picking using Yaskawa and Mech-Mind
This automation solution combines logistics and sorting automation by utilizing Mech-Mind 3D Vision and the Yaskawa GP8 robot to classify and transfer a diverse range of unstructured objects. By leveraging a highly cost-effective 3D vision system to recognize both the position and geometry of items, the robot can easily sort products even if their locations change or multiple types of objects are mixed together. This is the ideal solution for environments with diverse workpieces or for companies looking to automate manual tasks with minimal changes to their existing workspace. The project was implemented to automate order picking in fulfillment centers and eliminate the manual labor required for sorting individual packaged goods. Furthermore, it aims to achieve high-efficiency sorting for unstructured and mixed-SKU inventory. *Note: This content is based on a demo; actual deployment may require additional equipment based on specific customer requirements.
Part Transfer using Autonomous Lift-Conveyor
This logistics robot solution utilizes an autonomous lift-conveyor to perform material transport tasks between manufacturing processes. By using vision technology to recognize workpiece information, the system can stack items in matching locations based on their category. Conversely, when a work command is received, it can retrieve necessary items from storage racks and move them to the discharge position. The integration of a linear track allows the robot to cover a wide operational area, enabling comprehensive inbound/outbound inventory management.