Industry Challenges
In the manufacturing sector, soft package de-palletizing has traditionally been labor-intensive and costly due to:
- Heavy loads and high-volume operations
- Rising labor costs and recruitment difficulties
- Challenging working conditions in 24/7 shift environments
To address these pain points, a leading home appliance manufacturer partnered with LuminWave to implement an AI-powered, 3D vision-enhanced de-palletizing system.
Project Challenges & Solutions
✅ Oversized Pallets – Required handling extra-large pallets (2m × 2m × 2.3m), exceeding the limits of conventional systems. LuminWave optimized its camera architecture to accommodate these dimensions.
✅ Space Constraints – Tight facility space demanded precision equipment layout and compact hardware solutions.
✅ Ambient Light Interference – Skylights caused scattered sunlight issues, reducing visual accuracy. AI-based adaptive vision algorithms resolved this problem.
✅ Cost Efficiency – The client required a budget-friendly, high-performance solution, balancing cost and ROI.
Core Components
3D ToF Camera
Detection Range: 0.4-5m
Field of View (H × V): 70° × 50°
ToF Resolution: 640 × 480 dpi
RGB Resolution: 1600 × 1200 dpi
Ranging Accuracy: <1% (@2m ≤ 5mm)
Algorithm Software
Adaptability: Leverages AI deep learning and model training to accurately identify objects like cardboard boxes, jute bags, and metal rods.
Rapid Deployment: Achieves scenario adaptation with minimal training data.
Lightweight Architecture: Integrates universal algorithms and flexible APIs for seamless recognition and positioning.
Highlights of the Project
✅ 99.9% recognition accuracy
✅ Recognition cycle under 3 seconds
✅ Deployment completed in just 3 days
✅ Reliable performance in challenging light conditions
✅ Supports dual-pallet processing & adaptive empty pallet detection
By automating de-palletizing, LuminWave helps manufacturers reduce costs, increase efficiency, and future-proof operations in an increasingly labor-constrained environment.
