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Artificial Intelligence Smart Robots are Conquering the Factory

From Sandro Kipar | Translated by AI 1 min Reading Time

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NTT DATA Deutschland SE
FAULHABER Drive Systems

Artificial intelligence makes the mechanical helpers more flexible, efficient, and reliable. Especially in conjunction with a digital twin, significant optimization potentials arise.

With the help of AI and edge computing, automated inventory monitoring is possible. Manual entries are increasingly becoming a thing of the past.(Image: bernarbodo/DigitalVision via Getty Images)
With the help of AI and edge computing, automated inventory monitoring is possible. Manual entries are increasingly becoming a thing of the past.
(Image: bernarbodo/DigitalVision via Getty Images)

Industrial robots are evolving from rigid automatons to intelligent systems. NTT Data demonstrates with four concrete application examples how modern robotic solutions with artificial intelligence (AI), edge computing, and generative AI (GenAI) optimize real production processes in real-time—thus driving the transformation towards the adaptive factory of the future.

  • Adaptive robot control: Thanks to high-resolution sensors, GenAI, and image processing systems, robots not only recognize their environment but also make independent decisions in case of production disruptions or material shortages. Integration into digital twins in the industrial metaverse allows simulations during ongoing operations without affecting physical facilities. Edge computing and 5G provide the necessary computing and communication power directly on the line.

  • Quality assurance in real-time: Sensors and AI immediately detect defects—whether in assembly, surfaces, or colors. Robots confronted with unknown objects use GenAI to independently develop action strategies—also based on external data sources. The result: less waste, higher throughput quality.

  • Predictive maintenance: Condition monitoring combined with AI detects anomalies at an early stage, such as with bearings or motors. GenAI extends this approach with optimization suggestions for operating points or alternative repair strategies—before a defect occurs.

  • Inventory and energy in focus: Automated inventory monitoring, connected with production planning, reduces costs and CO₂ emissions through precise material flow and energy savings.

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