AWARD
The winners of the Microsoft Intelligent Manufacturing Award 2025

AI-driven requirements management

The overall winner of this year’s MIMA has developed an AI-based solution for requirements engineering in the automotive sector. From unstructured text, their tool extracts, classifies, and maps customer requirements to existing features, significantly improving efficiency in handling up to 30,000 requirements per project. This solution, which will soon be rolled out at Continental Automotive, reduces manual effort in requirements extraction by up to 8x, significantly accelerating time to market and reducing R&D efforts. The advanced tool positions Continental ahead of competitors and optimizes the overall requirements management process, for Continental’s clients as well as its suppliers in the future.

AI solution for less water loss

The Nuremberg compan’s Water Loss Management addresses the critical global challenge of water scarcity with itsr AI-based solution to create a digital twin of water distribution grids. The technology detects, localizes, and even predicts leaks, as well as creating actionable insights via an operational, map-based dashboard to improve water quality and enhance grid performance. The promise of tackling a pressing socio-economic problem is already showing tangible effect: Notable success stories include reducing non-revenue water consumption in Denmark from 14% to 4%, early leak detection in a German industrial park, and improved network efficiency in Middle East. This solution not only lowers costs but also contributes to better water management and conservation, making it a versatile tool for global water sustainability efforts.

Predictive quality assurance through real-time control

The sensor technology experts have introduced a novel “dual approach for production process supervision”, combining AI and real-time process control to enhance quality and yield in manufacturing. Their predictive quality system uses more than 5,000 production parameters to create a “fingerprint” of defective items and achieve 99% accuracy in predicting potential returns. Meanwhile, the in-line process control system monitors and tracks components in real time, preventing defects and reducing waste. This innovative solution empowers workers with real-time feedback and support, demonstrating significant cost savings and scalability across production lines.

Combined virtual and physical metrology for manufacturing

Zeiss Digital Innovation has developed a “virtual metrology” solution for advanced precision manufacturing that integrates quality data on the shop floor. Their system predicts part quality in real time, allowing immediate process adjustments. This technology has shown significant productivity improvements and cost savings, with ROI typically achieved within six months. The solution's broad applicability, especially in brownfield applications, and positive customer impact highlight its effectiveness and scalability in precision manufacturing.

Predictive factory for food production

Cereal Docks, a multinational agrifood company, together with its technology partner MIPU, has implemented an AI-driven “predictive factory” manufacturing solution that enhances maintenance, reduces unexpected failures, and improves energy efficiency. Their project has led to a 10% increase in machine utilization, an 8-10% reduction in energy consumption, and the ability to predict 98% of failures six months in advance. This scalable solution uses existing data and contributes to sustainability by reducing CO2 emissions and avoiding food waste due to sudden machine failures. It demonstrates how leveraging existing production data and legacy systems and added IoT elements, combined with an integrated data analysis stack, can exploit significant potential beyond plain concepts or pilots.

Smart Factory combines innovation and sustainability

Philip Morris Manufacturing Technology Bologna has built a smart factory with a comprehensive digital architecture that includes AI and machine learning for real-time process optimization and predictive analytics. Their end-to-end digital ecosystem spans from tobacco farming to production and distribution, ensuring traceability and efficiency. The use of digital twin technologies and a focus on sustainability have led to significant reductions in energy and water consumption, with high recycling rates. The company’s ability to validate and deploy innovations across a global network demonstrates the scalability of their approach, which sees digital solutions as integral to the production network of tomorrow.