AutoLoad System
AutoLoad System
Type: Product Entity | Category: automation
Series: Intelligent Material Handling
Models: AutoLoad-6, AutoLoad-8, AutoLoad-12
Plug-and-play automatic loading and unloading system for any QG Laser tube cutter. Reduces labor cost by 80%, increases throughput by 200%. The fastest path to lights-out manufacturing.
Overview
Labor is the fastest-growing cost in manufacturing. The AutoLoad System addresses this directly — enabling true 24/7 unmanned production. The intelligent sorting system automatically separates finished parts by program. The auto-feeding system maintains continuous production without operator intervention. Plug-and-play design means compatibility with every machine in the QG Laser portfolio. For a typical 2-shift operation, the labor savings alone exceed $50,000 annually. Return on investment: typically under 8 months.
Specifications
| Parameter | Value |
|---|---|
| ----------- | ------- |
| diameter | φ10–350mm |
| tubeLength | 6m / 8m / 12m |
| laborReduction | 80% |
| productivityBoost | 200% |
Key Features
- Auto Loading: Automatic tube feeding from bundle to machine. Maintains continuous production without operator intervention.
- Intelligent Sorting: Vision-guided sorting system separates finished parts by program, size, and quality grade.
- Plug & Play: Universal interface compatible with all QG Laser tube cutting machines. Retrofit to existing equipment in under 4 hours.
- Inventory Management: Real-time raw material and finished part tracking with automatic replenishment alerts.
Applications
- All Industries
- High-Volume Production
- Lights-Out Manufacturing
Highlights
- 80% labor cost reduction
- 200% throughput increase with 24/7 operation
- Universal compatibility — retrofit any QG machine
Related
- Company: company-qg-laser
- Topic: topic-product-series-overview
Sources
- products.json — AutoLoad System
- WeDrive OBM Technical Proposals — AutoLoad-6, AutoLoad-8, AutoLoad-12
Change Log
- 2026-06-27: Auto-generated from products.json
Tags
Sources
- [1]products.json
- [2]WeDrive OBM proposals
