This case study explores the practical application of AI and IoT technologies in the context of pharmaceutical manufacturing to enhance machine health monitoring and optimize energy efficiency. By analyzing data from implemented projects, the session examines how condition-based insights can support a shift toward energy-centered maintenance strategies. Attendees will gain an understanding of the technical architecture, integration challenges, and measurable outcomes associated with these deployments — with an emphasis on reliability, sustainability, and regulatory considerations. In this session, you will learn how to:

• Apply AI models to monitor equipment condition and preempt mechanical degradation based on real-world operational data.
• Detect and quantify energy inefficiencies using IoT-connected systems within GMP-compliant environments.
• Evaluate the effectiveness of energy-centered maintenance strategies across production assets with regard to performance and sustainability metrics.