Zero Defect project – using AI and Big Data to predict quality defects
Zero Defect: AI and Big Data to predict quality defects – and save raw materials
EIT Manufacturing’s Zero Defect project seeks to provide a solution to reduce waste of energy and raw materials due to quality defects.
[EIT Success story 2020]
Each year, billions of products with defects are produced, leading to unnecessary waste of raw materials and energy. By predicting defects and recommending process parameters and actions to maximize product quality, the Zero Defects project aims to help reduce waste of raw materials, energy and other resources, while supporting shopfloor staff and product developers/engineers in optimising their work.
What is the solution?
The Zero Defects project provides a digital tool to predict defects. The tool leverages Artificial Intelligence (AI) and Big Data for consistent quality and predicts quality defects before they even occur.
What are the benefits for the plants and society?
• Predicting defects, reducing waste and optimising resources.
• Significant reduction of wasted material and energy.
• “One example from our pilot: in the use case of wood-based panels production (at one production plant), an estimated 245 tons of wood could be saved on the first year of introduction of the system through the reduction of defects.” – Ana Machado Silva, Lead partner representative.
EIT Knowledge triangle in action?
The project was developed by a consortium involving academic and industrial partners:
• Manufacturing expertise: Sonae Arauco
• IoT architecture systems from InnoWave and INESC-TEC
• Decision Support Systems: LMS and INESC-TEC
• Artificial Intelligence and Machine Learning: FEUP and LMS