ISI - Use Case "AI for detecting quality defects in screw production"

The ISI project offers companies the opportunity to explore new digital technologies and adapt them to their specific needs for subsequent implementation within their businesses. In the use case of partner Cedoon, an AI-based solution for the automated quality control of screws was developed. The goal is to reduce manual inspection processes, detect production defects early, and increase efficiency in quality assurance. At its core is an image recognition system that uses machine learning and deep learning methods to visually analyze and automatically evaluate screws. This includes the use of autoencoders for anomaly detection and transfer learning with pre-trained neural networks to identify even the smallest deviations in material structure, thread form, and surface finish. The solution is based on the analysis of image data, which is processed for training the models. The aim is to reliably classify defective and faulty components and to easily integrate the technology into existing production processes.

More about the project: https://isi.fotec.at/usecases/cedoon/ 

Project by: https://www.fotec.at/de/home/innovative-software-systems/

Business

Artificial Intelligence & Data