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Integrated chip detection at Watts Industries Germany

Chips (swarf) on the thread of floor heating distribution pipes cause leaks and require rework or generate waste. Manual random testing is inefficient. Defective workpieces indicate, for example, wear and tear on the processing tools, so early detection is crucial. Each further process step involving defective workpieces causes unnecessary costs. The aim is to automatically detect chips on the workpiece within a few seconds without lengthening the overall process.

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AI and IoT potential workshop for Exner's high-quality process valves

Exner Process Equipment GmbH recognized the transformative potential of Artificial Intelligence (AI) and the Internet of Things (IoT) but faced challenges in identifying meaningful and profitable applications for these technologies in its industrial processes.

A Smarter Way to Monitor Your Equipment with IBM's Asset Monitoring and prenode Edge AI

In partnership with IBM, we helped them to overcome data challenges and enhanced asset monitoring with our decentralized AI solution, prenode mlx. By integrating mlx into IBM’s existing infrastructure, our joint showcase, Hammer-Rig, successfully addresses privacy concerns and data silos while leveraging federated machine learning to achieve accurate predictions of overheating events. Through this collaboration, IBM experiences significant positive business impacts. We are confident that our cooperation will pave the way for an integrated AI solution in the future of the smart manufacturing industry.

Driving TRUMPF's Equipment-as-a-Service (EaaS) business model with prenode remote operations solution

In partnership with TRUMPF, we successfully implemented an innovative technology that transforms Equipment-as-a-Service (EaaS) model in the sheet metal industry. With this collaboration, we have effectively tackled TRUMPF's challenges and introduced a remote operations solution that seamlessly combines live monitoring and remote access capabilities, enabling swift and efficient troubleshooting. By optimizing real-time operations, enhancing cost transparency, and driving profitability, this innovative technology holds immense potential for the sheet metal sector and beyond. Furthermore, our remarkable collaboration has won the prestigious Microsoft Intelligent Manufacturing Award (MIMA) 2023 in the "SCALE!" category.

Revolutionizing Predictive Maintenance for WEISSER Precision Turning Machines with prenode Decentralized Machine Learning Solution

In collaboration with the WEISSER Group and the Hahn-Schickard-Gesellschaft, we developed a ground-breaking predictive maintenance solution for WEISSER precision turning machines. Our cooperation project “KIOWA“ aimed to leverage prenode's decentralized machine learning software (mlx) to predict maintenance events and optimize the performance of WEISSER machines.

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