Federated Learning for Manufacturing
Modern manufacturing and production processes rely on automated quality assurance and predictive maintenance to achieve better accuracy, reliability and competitiveness [1]. Advancements in Machine Learning (ML) are pushing the boundaries of what is possible in...
An assessment of relevant AI techniques applied across the entire phases of the industrial equipment lifecycle
Artificial Intelligence (AI) is constantly playing a significant role in smart manufacturing as it continues to facilitate the predictability of events, patterns and behaviors within complex and dynamic industrial environments. This article provides an insight into...
How advances in computer vision provide clearer quality control
Quality professionals in manufacturing face the dread of discovering substantial product flaws and being unable to rapidly pinpoint the main cause. The rise of deep learning AI is proven to be a great solution for detecting and preventing such mistakes and to ensure...
Open toolkit for implementing Asset Administration Shell
Digital Twins in I4.0 Digital twins combine fragmented data into a unified view, solving interoperability issues. Industry 4.0 aims at the Implementation of Digital Twins using an Asset Administration Shell (AAS) to create a common language for digital representations...