Quality Control innovative project for the Automotive industry
Inline and Real-Time quality inspection solution for all the automotive parts on an aluminum production line.
Innovative project " EIT-Manufacturing-RIS-Intrapreneurship": Inline and Real-Time quality inspection solution for aluminium automotive parts, with the use of Artificial Intelligence and Machine Learning.
Basic description
The innovative project “EIT-Manufacturing-RIS-Intrapreneurship” uses Artificial Intelligence and Machine Learning in order to provide INLINE and REAL-TIME quality inspection for all the automotive parts on an aluminum production line.
The system’s profound impact on the manufacturing process includes substantial improvements in productivity and environmental footprint through scrap minimization.
Furthermore, increases part production capacity and ensures business continuity and stability through its intelligent nature.
THE PROBLEM
Machined aluminum parts for the automotive industry, often suffer from structural defects.
These defects are reflected to the surface and to deviations from the expected Computer-aided designs (CAD).
Deviations from this strict quality assurance framework have a significant societal, environmental and financial impact and trigger cascading clauses on the whole automotive value chain (tiers, automotive brands, insurance companies).
THE SOLUTION
A holistic state-of-the-art inline Quality Control system for inspecting aluminum parts before down streamed to assembling operations.
The proposed solution uses Artificial Intelligence and Machine Learning in order to provide INLINE and REAL-TIME quality inspection for all parts on the production line.
Furthermore, it incorporates Active Leaning technologies in order to be able to generalize in a variety of aluminum parts while minimizing human intervention.
THE IMPLEMENTATION METHODS
The main solution:
- Performs 360 surface inspection through a state-of-art Artificial Intelligence and Machine Vision system using computer vision and machine learning.
- Incorporates 3D sensors for combing (multi-modal fusion) surface evidence with data representing the actual mesh of the parts thus assessing the most significant fidelity parameters.
The takeaways
Artificial Intelligence
Machine Learning
Industry 4.0
Real-time defect detection
Real-time production monitoring
Innovative quality control solution
Generalization in a variety of aluminum parts
The Benefits
The profound impact on AI-driven factory transformation will enable manufacturers and other supply chain stakeholders to redefine the industrial processes towards substantial improvements in productivity (through improved efficiency) and environment performance (through scrap minimization).
Furthermore, increasing part production capacity while reducing high-scale claims through intelligent quality control, ensures business continuity, stability and prosperity. Taking over manual or semi-supervised quality control tasks, increases personnel safety and sets a solid ground on human resource upskilling.
Project ID
Start Date: July 2022
Duration: 6 months
