Advanced simulations for predicting molding cycle times using PCR resin blends
This solution leverages advanced simulations to accurately predict injection molding cycle times for resin blends incorporating post-consumer recycled (PCR) materials. By developing enhanced models based on measured thermal properties, it improves manufacturing efficiency.
Overview
This innovative solution focuses on enhancing the accuracy of predictions for injection molding cycle times when using resin blends with post-consumer recycled (PCR) materials. Traditional linear mixture models fall short for materials like PET, where crystallinity significantly affects thermal properties. By utilizing measured thermal properties and sophisticated simulation software, this approach offers improved predictions that are crucial for optimizing the production process and reducing cycle times.
Technical specifications
- Enhanced modeling: Develops models that predict blend properties based on PCR proportion, crystallinity, and inherent properties of pure resins.
- Simulation tools: Utilizes Moldex3D software to simulate cycle times under various molding conditions, ensuring predictions closely match experimental results.
- Hybrid modeling: Collaborates with experts to integrate physics-based models with machine learning algorithms, enhancing prediction accuracy for cycle times.
- Key focus areas: Crystallinity, thermal conductivity, thermal diffusivity, and thermal expansion coefficients are measured and factored into models.
Technology readiness level
This technology is currently at TRL 2. Initial simulations and modeling efforts have been conducted, with further validation and development planned to refine and enhance prediction accuracy through both traditional and hybrid modeling approaches.
About Michigan State University
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.
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