Production Equipment
Inspection Equipment Build
AI Vision Inspection Automation Equipment
WHY
Why Is It Needed?
Inspection equipment must be vertically integrated across mechanics, optics, controls, and inspection SW to be built and operated.
WHERE
Where Is It Used?
Target industries: Manufacturing broadly, including semiconductors, defense, and machinery
Target Customers
Companies reviewing their investment direction for inspection automation
KEY CAPABILITIES
Key Capabilities
01
H/W Engineering Suited for AI Judgment
H/W engineering to improve AI accuracy and deliver consistent inference
02
AI Model & AI Judgment Platform Development
Development of AI models that can judge n grades across m+ items
MODULES
Vision Inspection
Mechanics
Transfer / Adjustment / Inspection
Optics
Camera / Lighting
Controls
Process Integration / PLC
Inspection SW
Image Analysis
IMPACT
Benefits
Before vs. After
Review operators
Before 96
→
After 16
80people
↓
Before vs. After
Review inspection machines
Before 48
→
After 8
40units
↓
Before vs. After
Judgment accuracy
Before 70%
→
After 90%
20%
↑
01
Automated Loading & Unloading
Automates repetitive tasks from loading raw materials to unloading finished parts.
02
Minimized Product Damage & Handling Errors
Standardized alignment, gripping, and transfer conditions prevent drops, collisions, and mis-loading.
03
Higher Productivity & Operational Stability
Reduces labor cost and operator dependence and enables continuous production at a consistent cycle time.
CUSTOMER VOICE
Voice of the Customer
"Loading and unloading speed is now consistent, so wait times between processes have dropped and production flow is stable."
"Operators handle products by hand less often, so mis-loading and product damage have decreased."
"Loaders and unloaders link to equipment automatically and leave a history, making it easier to manage production status and root causes and to track quality."
WHY LG CNS
Why LG CNS
01
One-Stop Service from AI Technology Consulting to Development
02
Expertise in vision inspection AI development and specialists experienced in field deployment
03
AI model lightweighting and edge inference optimization to reduce H/W resources
REFERENCE