Across healthcare and life sciences, ensuring the right product is available to consumers at the right moment is mission critical. This applies to staples such as aspirin to recent vaccines for COVID where quality, shelf life, and availability are paramount. Pharma manufacturers strive for high quality standards and instantaneous product availability while being constrained by regulated manufacturing processes and strict product quality standards. All while managing raw material variability, increased labor and raw material costs, and inflexible supply chains.
In this dynamic environment, harnessing the power of AI-led digital transformation becomes not just an option, but a necessity. Medical device and pharma manufacturers are unlocking data using the Databricks Lakehouse Platform to turn once process-locked factories into agile factories, empowering manufacturing teams to gain significant value through improved Overall Equipment Effectiveness (OEE) and energy optimization.
By leveraging data and AI, leading organizations can de-risk supply chain and manufacturing processes, and build resilience for future demands. They can enable seamless OT connectivity, forecast production volume, predict production line performance, identify hindrances to production targets, pinpoint drivers of losses, and proactively detect potential energy leaks due to operational issues.
Here's what we'll cover:
- Industry trends shaping the future of healthcare and life sciences
- The role of data, analytics and AI enabling digital supply chain and manufacturing transformation
- How AI powered from the Databricks Lakehouse is helping improve planning accuracy, manufacturing efficiency, and energy consumption
- Deploying a Smart Manufacturing Command Center (SMCC)