Software

Moving beyond Melt Flow Index: select rheological measurements that match the deformation modes of injection molding and film blowing.

AI-assisted polymer design screens millions of candidates to identify chemically recyclable packaging polymers that still meet barrier and thermal targets.

AI control for recycled plastics stabilizes injection molding despite resin variability, reducing defects and improving operator confidence with explainable models.

A two-year program conducted by CEFLEX gathered information from 1,700 data points and over 600 packaging samples. As a result, a design guide was developed to ensure the practical recyclability of flexible packaging.

As manufacturers embrace Industry 4.0, collaborative robots leveraging machine learning (ML) bring autonomy and efficiency to the factory floor.

Rigid polyurethane composites with industrial waste fillers: mechanical strength, thermal conductivity, and machine-learning guided optimization.

Fouling comes from additive volatility and interfacial energetics. Early shifts in cavity-pressure and ejector-force trends reveal their growth and prompt planned interventions.

Fluorine-free polymers are redefining liquid cooling hardware, delivering chemical stability and dielectric strength without relying on PFAS.

Smart factories use data analytics, automation, and modular design to enhance efficiency, adaptability, and sustainability in plastics manufacturing.

Researchers are using machine learning (ML) to unlock the potential of an alternative welding technique for joining wood-plastic composites (WPCs).