Monitoring and controlling processes are often more complex than simple statistical analytic quality tools can handle. Sometimes the process data is too complex, behaves unpredictably, or even just contains too many things to measure. This session will show how to utilize next generation statistical analytic quality tools to cover challenges such as:
- Handling Data Problems (Missing Data & Outliers) - Screening Multiple Process Behaviors Over Time (Process Screening) - Understanding When Processes are Just Starting to Change (Process Drift) - Meeting Capability Assumptions & Options if Not Normal (Non-Normal Capability) - Seeing the Best Window of Variation to Use (Short vs. Long Views) - Comparing Multiple Capabilities (Goal Plots & Process Performance Charts) - How to Manage Up Results (Graph Building Tricks & Tips) This session will utilize data from common industry situations to demonstrate these next generation statistical analytic quality tools.
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