DUETT

The DUETT project is aimed specifically at small and medium-sized enterprises (SMEs) in the plastics industry, to which two use cases will provide practical demonstrations of the potential and applications of modern, data-driven methods and artificial intelligence (AI) for process monitoring and quality assurance.

The project’s technical focus is on inline detection and classification of optical defects in injection-molded parts (Use Case 1) and on data-driven anomaly detection in recycled material processing (Use Case 2). Both use cases aim to optimize production processes using digital solutions, improve manufacturing quality and resource efficiency, and reduce scrap and CO₂ emissions.

The methods developed will be tested under real-world conditions in collaboration with the project advisory committee and evaluated for their applicability to SMEs. In addition, a knowledge and technology transfer concept is being developed that includes practical, adaptable tools and learning modules to help SMEs get started with digitalization and the use of AI.

DUETT contributes to the sustainable and future-oriented transformation of plastics processing by specifically leveraging digital methods and AI applications for quality assurance, process optimization, and the resource-efficient use of recycled materials.