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NTT Data And Schneider Electric Collaborate On Industry 4.0

Kuka showcased robots in a 'smart factory' at Hanover Fair in 2018.

On April 22, 2018, at the Hanover Fair in Germany, Kuka showcased several robots in a 'smart factory,' highlighting new developments in artificial intelligence. The evolution of computing power has led to smarter devices, from smartphones to airport kiosks and digitally-connected traffic lights, all driven by Artificial Intelligence (AI) for better living.

Industry 4.0, as defined by McKinsey, marks the digitization of the manufacturing sector through data, connectivity, analytics, human-machine interaction, and robotics. NTT Data and Schneider Electric have collaborated on a data fusion initiative to empower Industry 4.0 devices with edge computing, private 5G, IoT, and modular datacenters to support generative AI applications at the edge.

The integration of NTT Data's Edge-as-a-Service with Schneider Electric's EcoStruxure aims to handle compute-intensive tasks like machine vision and predictive maintenance at the edge. This partnership enables the deployment of edge datacenters in remote locations, addressing high compute demands and infrastructure needs.

NTT Data's Edge Advantage report indicates that 70% of enterprises are accelerating edge adoption to solve business challenges. The first private 5G-enabled EcoStruxure datacenter deployment is at Marienpark in Berlin, an innovation zone spanning 74 acres.

As AI-enriched data accounts for a third of enterprise network traffic and is projected to dominate digital interactions by 2030, investing in edge computing infrastructure is crucial for Industry 4.0 success. The collaboration between NTT Data and Schneider Electric aims to assist global clients in adopting connected devices, industrial solutions, and edge computing infrastructure to gain valuable data insights.

Camille Mendler from Omdia emphasizes the importance of investing in digital resources at the edge for real-time data-driven intelligence. The increasing use of generative AI in robotics and other applications necessitates enhanced computing power at the edge, bringing devices closer to core enterprise applications.

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