With the digital transformation of industry, more and more data are being generated. Artificial Intelligence (AI) and Machine Learning enable engineers and data scientists to structure, analyze and evaluate the enormous volume of data. The application scenarios range across the lifecycle: Smart recommendations, generative design, anomaly detection, and preventive maintenance optimize the way and pace with which products are designed and produced.
To make use of industrial-grade AI applications in a reliable and value-adding way, they must interact seamlessly with software and automation and the corresponding IT infrastructure. Therefore, collaboration and open ecosystems are crucial to leveraging the great potential of these technologies.
Manufacturing companies need a digital transformation to secure their competitiveness, enable modern work 4.0 and gain future viability. How this can be achieved? Find out in this panel.
Also, our panelists will discuss about the manufacturing process of semiconductors and electronics. How these can be supervised by cameras taking photos interpreted by AI to distinguish scrap from good parts and identify the source of any damages. These methods are executed at the edge but trained centrally using an ever-evolving stock of training images—more about the process and tools in the live session on December 8th.