Process layout
Process Overview
This implementation combines Omron AMR logistics robots with an AI-based palletizing system to achieve logistics automation. The customer showed strong interest in adopting an AI-powered logistics automation system to strengthen future competitiveness and to maximize cost savings and operational efficiency through automated palletizing and material handling.
This solution autonomously transports and loads various types of goods, improving efficiency and accuracy in inbound and outbound operations, while reducing physical workload for operators and ensuring workplace safety.
Project Background and Objectives
The customer aimed to optimize logistics operations and reduce costs by adopting an AI-driven automation solution to enhance future logistics competitiveness. In particular, automation was urgently needed for repetitive and heavy palletizing tasks and material transport operations.
The objective of this project is to maximize outbound operation efficiency using AMRs and industrial robots, ensure operator safety, and enable real-time tracking and management of goods. Through this, the customer sought to improve productivity at the logistics site and secure long-term stability and flexibility in future logistics operations.
Components
| Robot | Omron AMR logistics robot: A mobile robot equipped with autonomous driving and obstacle avoidance capabilities. It can freely perform material handling tasks by coupling and decoupling carts as needed. |
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| Peripherals |
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Workflow
| STEP 1. | Outbound command: When the operator presses the outbound button, the AMR receives an outbound task from the warehouse management system and autonomously drives to the designated location |
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| STEP 2. | Cart preparation and locking: The AMR identifies the cart and secures it with a hook to complete stable transport readiness |
| STEP 3. | Arrival at picking station: The AMR moves to the picking station and prepares for palletizing for loading |
| STEP 4. | Palletizing: The industrial robot stacks boxes onto the cart in an optimized pattern using an AI algorithm |
| STEP 5. | Full cart pickup: When the cart is full, the AMR automatically detects it and proceeds to retrieve it to the designated outbound area |
| STEP 6. | Arrival at outbound area and dispatch: The AMR arrives at the outbound area, detaches the cart, and tracks inventory status in real time through the inbound/outbound management system |
| STEP 7. | Task completion and return to charging: After the task is completed, the AMR automatically returns to the charging station to prepare for the next task. |
Features
Supports a wide range of logistics and manufacturing environments: Not only standardized boxes, but also various non-standard products can be loaded onto carts and transported.
Cart and AMR separation available: Full carts can be stored at the post station, allowing the AMR to continue additional tasks.
Enhanced safety system: Safety light curtains and fences separate the operator and AMR work areas to prevent accidents, and the system can automatically stop when an operator approaches via the light curtain.
AI palletizing efficiency: AI-based algorithms optimize stacking patterns for various box types, maximizing space utilization.
Results
| Key Benefits | Improved efficiency: Palletizing and transport tasks are automated, increasing work speed and reducing operator fatigue.
Cost reduction: Automating the logistics process enables labor cost savings and more efficient operations.
Enhanced safety: Safety light curtains and autonomous driving functions minimize accident risks during operation.
Optimized inventory tracking: A real-time tracking system enables efficient management of outbound status and location tracking. |
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| Client Feedback | The customer commented, βWith the introduction of AMRs and palletizing robots, not only has the physical workload for operators been reduced, but logistics efficiency has also improved significantly. In particular, the well-established safety system has created an environment where workers can focus on their tasks with greater confidence.β |
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