'GreenMoldAI: Sustainable Optimization of Plastic Composite Injection Processes for Automotive Excellence'
▶Summary
The project aims to achieve early defect detection in plastic composite injection manufacturing, leading to cost reduction, increased efficiency, and sustainability. It leverages machine learning ...
▶Objectives
The project aims to achieve early defect detection in plastic composite injection manufacturing, leading to cost reduction, increased efficiency, and sustainability. It leverages machine learning for optimized processes, supports the use of recycled materials, and aligns with climate agreements. The collaborative consortium approach involves key partners for impactful results.
▶Activities
Implementation activities include: Develop machine learning algorithms. Collect and preprocess data on pressure, temperature, viscosity. Train algorithms for defect classification. Collaborate with consortium partners. Promote European Green Deal goals and sustainable practices, . Conduct community workshops and training. Share results through workshops, media, and online platforms. Engage with stakeholders for feedback and continuous improvement.
▶Impact
Expected results: Early defect detection in plastic injection. Cost reduction, efficiency improvement. Integration of sustainable practices. Trained machine learning algorithms. Enhanced collaboration within the consortium. Knowledge transfer and skill development. Increased awareness in the community. Publications and presentations showcasing project outcomes.