Details

Can DEEP LEARNING be used as a universal tool for machine vision, just like a Swiss Army Knife? We at
AIT work at the forefront of machine learning and we know when deep learning is the appropriate tool for
solving your problem and when it’s not.
ADVANTAGES OF DEEP LEARNING
In the past, tasks like optical quality control required a solution that had to be custom-engineered every time anew. Change the process? Change everything. Deep learning can minimize that costly and labor-intensive process and at the same time increase speed and accuracy of Quality inspection. Deep Learning methods like CNNs (Convolutional Neural Networks) are methods that imitate the principles of the human brain to solve problems. CNNs are trained on a specific set of data. By analyzing a vast database, the software can spot and recognize patterns. Thus, in contrast to classical methods in which models are designed and cast into formulas, even blurred problems can be solved.
DEEP LEARNING CAN BE USED FOR
With the help of deep neural networks, one is able to solve various tasks in the field of industrial inspection, e.g.
• defect classification,
• error and anomaly detection, and
• substitution of complex imaging algorithms for better quality and runtime.

Video
https://youtu.be/WhKc1-KCl2I

Produktbeschreibung

Produktname
DEEP LEARNING IN INDUSTRIAL INSPECTION

Systemtyp

Eigenständige Software

Qualitätsprüfung

Ausschussmeldungen
Qualitätsmonitoring

Planen & Steuern

Fehlermöglichkeits- und Einflussanalyse (FMEA)
Advanced Quality Planning (APQP)

Branchenschwerpunkte

Automobilindustrie
Elektroindustrie
Kunststoffverarbeitung
Luft- und Raumfahrt
Maschinen- und Anlagebau
Medizintechnik
Metallverarbeitung

Firma

AIT Austrian Institute of Technology GmbH

Firmenportrait