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AI for Good Innovate for Impact
Use Case - 11: Industrial AI Quality Inspection Based on IndustryGPT
Multimodal Industrial Large Model
Organization: Shenzhen Smartmore Co.Ltd
Country: China
Contact Person(s):
Chi Zhang, chi.zhang@ smartmore .com
1 Use Case Summary Table
Item Details
Category Manufacturing: Intelligent inspection, smart manufacturing, industrial large
model application
Problem Traditional industrial quality inspection methods are plagued by inefficient
Addressed manual processes, cumbersome data annotation and cleaning, and slow
model training. These challenges hinder productivity and delay the adoption
of AI solutions, making it difficult for industries to achieve rapid implementa-
tion and application of intelligent quality control.
Key Aspects IndustryGPT, a large industrial model, revolutionizes industrial AI by solving
of Solution inefficient manual inspection and complex data challenges. It enables "devel-
opment through conversation" for rapid AI implementation.
It operates via the SMore ViMo intelligent cloud platform, an end-to-end
system for industrial intelligence[1]. IndustryGPT comprehends ML processes,
using natural language to drive ViMo recommendations and automate devel-
opment steps.
On the production line, IndustryGPT transforms the industrial quality inspec-
tion all-in-one machine, replacing manual checks. This system precisely
detects and screens products with significantly superior speed and accuracy.
Technology IndustryGPT industrial large model, intelligent inspection, smart manufactur-
Keywords ing, AIGC
Data Avail- Data is private
ability
Metadata Industrial images (over 3 million), equipment operation data, sensor data
(Type of Data) (visual, thermal imaging, gas concentration, vibration, sound), text data (over
50 billion tokens), defect annotation data, multi-industry knowledge bases
(five disciplines: optics/mechanics/electronics/computing/software, eight
industries).
In the application scenarios of IndustryGPT, the data type is primarily defect
image data.
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