Predictive maintenance plays a central role in increasing overall equipment effectiveness (OEE), asset availability, and total cost of ownership, and is gaining increasing strategic relevance. Unplanned tool downtime as well as conservative, rigid maintenance strategies have a direct impact on companies’ profitability. Predictive maintenance replaces these approaches with a data-driven, condition- and forecast-based maintenance process built on a central data platform.
In this white paper, you’ll learn:
- The role of predictive maintenance in the context of traditional maintenance strategies
- Key process objectives of predictive maintenance in semiconductor manufacturing
- A digitalization strategy for maintenance processes, and the phased implementation of predictive maintenance solutions
- Specific use cases, such as RAG-based knowledge assistance for maintenance personnel and digital fault and action management
- ROI analysis and economic assessment
- A central data platform as the technical foundation for scalable applications
The goal is to secure investments and develop digital solutions that create measurable added value in day-to-day operations. As a digitalization partner with deep expertise in highly automated production environments, ZEISS Digital Innovation helps companies turn this vision into operational reality at the intersection of expertise, data, and technology.