95 INDUSTRIALS & MANUFACTURING is safe, scalable and trusted,” says Chien. “Our role is to empower the Physical AI ecosystem, to help customers and partners accelerate innovation, operationalise solutions, and scale with enterprise-grade intelligence and trust.” This platform-centric approach is reflected in initiatives such as the open Azure Physical AI toolchain, which integrates Nvidia’s Physical AI Data Factory Blueprint with Azure services to support the full lifecycle of robotics data. “What stood out to me at Hannover Messe is how concrete the conversations have become,” says Chien. “A year ago, these were conceptual. This year, they were about deployment timelines, architecture decisions and operational readiness.” He highlights a series of sessions involving Microsoft and partners including Wandelbots, Teradyne Robotics, Hexagon, Nvidia, BMW and KUKA, all exploring different aspects of what it means to operationalise physical intelligence at scale – from orchestration platforms to humanoid robotics and humanrobot collaboration models. In particular, he notes a shift in focus towards the execution layer: the systems required to bridge the gap between simulation and production. “In our HMI masterclass with Wandelbots on operationalising physical intelligence, the discussion centred on the execution and orchestration layer, which is the missing piece between a promising model and a productionready system,” says Chien. “That’s the gap the open-source Azure Physical AI Toolchain is designed to close, giving developers a blueprint to move from simulation through deployment and continuous improvement.” As the industry moves towards more intelligent and autonomous systems, Chien argues that manufacturers need to rethink how they approach robotics – not as isolated projects, but as scalable platforms integrated into broader operational strategies. “The value I’m seeing today is in the foundation layers,” he says. “Companies investing in cloud-based robotics platforms, operational data pipelines and simulation environments are already seeing faster deployment cycles, better fleet-level visibility and more consistent operations across sites. “The manufacturers moving fastest are the ones treating data as a strategic asset, approaching robotics as a platform rather than a project, and building ecosystem relationships early. And increasingly, the picture I see emerging across these conversations is one where humans, robots and AI agents work together as coordinated systems. That’s the shift to get ready for.” “Coretek integrates Microsoft AI with industrial robotic and IoT systems to create intelligent, responsive manufacturing environments. Using Microsoft Azure IoT Hub, AI Foundry and computer vision models, we deliver real-time equipment health monitoring, predictive maintenance and autonomous quality inspection. A large automotive parts manufacturer in Michigan, USA, deployed AI-powered robotic process monitoring across its production floor, reducing unplanned downtime by 35 per cent and improving defect detection accuracy by 28 per cent. By unifying machine data with generative AI insights, Coretek enables manufacturers to move from reactive maintenance to proactive operations – maximising throughput, safety and profitability at scale.” Brian Barnes Chief Technology Officer, Coretek We asked Coretek how it is leveraging Microsoft’s AI technology to help manufacturers leverage robotic solutions in order to drive efficiency, analyse data and operate equipment Partner perspective “ Robots are becoming adaptive systems that can sense, reason and act in real-world conditions”
RkJQdWJsaXNoZXIy NzQ1NTk=