This presentation explores the foundational steps required to implement effective predictive maintenance in pharmaceutical manufacturing. Drawing on years of leadership in reliability and maintenance engineering, the session emphasizes the crucial role of standardized communication protocols, interoperable systems, and high-quality field-level data as prerequisites for AI-driven insights. By focusing on the language and connection of plant equipment, this talk demonstrates how to unlock the full potential of digitalization and AI across complex GMP environments. In this session, you will learn, how to:
- Establish robust data acquisition strategies from field equipment to enable condition-based and predictive maintenance.
- Lay a solid foundation for future AI applications by ensuring data quality, integrity, and contextual relevance.
- Bridge the gap between traditional maintenance operations and future-ready digital ecosystems in pharmaceutical plants.
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