ChinaChemicals and materials2026 – ongoingHengli Chemical Fiber
AI visual inspection and production-quality feedback
Hengli Chemical Fiber reported that AI inspection reduced checks from 15 seconds to 2.5 seconds per yarn package
Problem
Manual yarn-package inspection was slow and prone to misclassification. Delayed quality feedback also slowed responses to production problems.
Approach
Hengli Chemical Fiber deployed a quality-control system combining machine vision with deep learning. It detected exterior defects and sent quality data to production teams for AI-assisted process improvements. The system was rolled out internally across different chemical-fiber production lines.
Results
Takeaway
The deployment linked defect inspection to production feedback. Its reported results covered both inspection speed and product quality.
Categories
- Size
- Large enterprise
- Industry
- Chemicals and materials
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Computer visionPredictive analytics and ML
- Adoption
- Built in-house
- Evidence
- Company's own claim
Sources
Source summaries
China Textile described Hengli's deployed visual inspection system and its internal rollout. It reported checks taking 2.5 seconds instead of 15 seconds and a product defect-rate reduction of about 50%.
Full details are in the original sources.