Case Study
Tuesday, September 23
09:15 AM - 09:45 AM
Live in Berlin
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This Presentation highlights the integration of Artificial Intelligence (AI), data quality, and Manufacturing Execution Systems (MES) within the framework of a modern predictive maintenance program. It explores how AI can harness data to enable proactive maintenance strategies, improve asset performance, and optimize maintenance schedules. The crucial role of data quality in ensuring the accuracy and reliability of AI-driven predictive maintenance is emphasized. Furthermore, the abstract highlights the significance of MES as a central platform for managing and analyzing maintenance data, facilitating real-time monitoring, and enabling informed decision-making. Join us to explore the synergies between AI, data quality, and MES in the context of a modern predictive maintenance program, and discover how this integration can enhance operational efficiency, reduce downtime, and maximize asset reliability.
This presentation covers: