An AI-driven sorting system for multi-layer flexible packaging leverages advanced optical sensing and machine learning to enhance the recovery and classification of polyolefin-based materials. It aims to boost recycling efficiency and reduce contamination in existing sorting lines.
The AI-enabled hybrid sorting system is designed to revolutionize the recycling of multi-layer flexible packaging, particularly those made from polyolefin-based materials. By integrating advanced optical sensing technologies with machine-learning classification, this innovative system can accurately identify and separate complex packaging types, including metallized, inked, and coated flexibles. This solution aims to improve recovery efficiency, reduce material contamination, and provide higher-quality feedstock for recycling and conversion processes.
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Currently at Technology Readiness Level 3, the system has undergone initial concept validation. Future phases include data collection, model development, prototype integration, and comprehensive validation against standard sorting methods. The project is set to deliver measurable improvements in sorting accuracy and efficiency, with a roadmap for pilot-scale deployment.
Michigan State University is a major public land‑grant research university with a comprehensive academic portfolio and a large research enterprise. Industry partners engage through an on‑campus U.S. Department of Energy national user facility and shared core laboratories with user access. The university provides a chemical process scale‑up pilot plant on Michigan’s lakeshore, a research and technology park, and a Grand Rapids health innovation campus linking researchers with clinical partners. A statewide extension network supports field deployment and workforce training across Michigan’s manufacturing corridor. Research is backed by competitive federal funding from NSF, NIH, DOE, USDA, and DoD, while dedicated tech transfer and corporate engagement teams—supported by an affiliated research foundation—accelerate IP, licensing, startups, and sponsored research.