Why Your Connected Plant Still Isn’t Predictive
Five digital challenges you must solve
Many pharmaceutical manufacturing sites have achieved connectivity, the third level of the digital maturity model. Level 4 – a predictive plant – often remains out of reach, however. This interactive guide explores the five critical challenges...
Moving from Connected to Predictive
Challenge #1
Fragmented Data:
Challenge #2
Incomplete Process Understanding:
Challenge #3
Insights That Don’t Drive Actions:
Challenge #4
Reactive Reliability:
Challenge #5
Validation and Governance Barriers:
Pulling it Together
The Four Themes
Starting Points
Your 90-Day Roadmap
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Many pharmaceutical manufacturing sites have achieved connectivity, the third level of the digital maturity model. Level 4 – a predictive plant – often remains out of reach, however. This interactive guide explores the five critical challenges blocking plants from reaching Level 4 and how CAI can help you overcome them.
LEVEL 3
There is connectivity between systems and data flows freely but may lack context.
LEVEL 4
Real-time contextualized data enables forward-looking analytics, while AI and other tools allow for predictive operations.
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Challenge #3: Insights that don't drive actions
Analytics must move past just visibility to guide responses and decisions
Moving from connected to predictive
Before reaching Level 4, first you must understand the maturity scale and where you are right now
Challenge #4: Reactive reliability
Predictive insights allow for early interventions to avoid failures
Challenge #5: Validation and governance barriers
Adequate frameworks enable deployment of AI at scale
Challenge #1: Fragmented data
Predictive operations require high-quality, aligned and contextualized data
Challenge #2: Incomplete process understanding
Understanding what variables affect quality outcomes is critical
Pulling it together
Addressing the four fundamental gaps to reach Level 4
Next steps and about CAI
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