BASF optimizes plastic recycling using AI
BASF, in collaboration with partners Endress+Hauser, TechnoCompound, and various German universities, launched an advanced initiative to optimize mechanical recycling of plastics using artificial intelligence. By integrating spectroscopic methods with AI models, plastic waste composition can now be identified in real-time, improving the quality and efficiency of recycling processes. This project, funded partly by Germany's Federal Ministry of Education and Research, aims to address significant challenges in the consistency of recycled plastic output and contribute to sustainability in the circular economy.
- Organization
- BASF
- Industry
- Manufacturing
- Location
- Germany
- Published
- December 2024
Reported outcomes
Strategic outcomes
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- BASF
- Provider
- Microsoft
- Maturity
- Unknown
- Linked source
- BASF
No explicit deployment-stage evidence found.
Primary read
Use case focus
Showing 3 of 5
- 1Real-time identification of plastic waste composition using AI vision and spectroscopy
- 2AI-driven optimization of additive use and process control in mechanical recycling
- 3Automated quality assurance and sorting of recycled plastics
- Lack of real-time analysis tools for determining the composition of mechanically recycled plastics during processing
- Inconsistent quality of recycled plastic output due to variable input materials and contamination
- High demand for high-quality recycled plastics not met by current mechanical recycling processes
- Difficulty in efficiently steering the recycling process and optimizing additive use
- Integrated spectroscopic measuring techniques with AI algorithms to analyze plastic waste in real time
- Developed AI models to interpret material composition, grades, and contaminants during recycling
- Implemented AI-driven process control to recommend additives and adjust recycling in real time
- Collaborated with partners for data collection, model development, and process optimization
- Enabled real-time identification of plastic waste composition during the recycling process
- Improved the quality and consistency of recycled plastics
- Increased efficiency of recycling operations by precise process management
- Supported higher recycling rates and strengthened the circular economy
- Enhanced capability to produce high-value products from recycled plastics
Sources & evidence1
- Customer explicitly identified
- Independent source available
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jul 22, 2026.
The same organization appears in newer AI deployment evidence.
- Same organization re-documented as recently as 2025.
- Cited source last checked Jun 12, 2026 — ok (0/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
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