Process capability analysis in high-stakes manufacturing demands rigor and consistency – yet execution is routinely undermined by non-normal data, measurement noise, process instability, and uneven statistical expertise. This presentation introduces a fully automated JMP process capability workflow and scorecard methodology designed to eliminate these barriers systematically.
Using the JMP 19 Workflow Builder, we have synthesized 20 analytical platforms into a unified system that minimizes human error and lowers the barrier for users with limited statistical backgrounds. We demonstrate how this systematic approach addresses four critical pillars:
- Distributional intelligence: Handling non-normal data through automated goodness-of-fit, best curve fitting and tolerance interval analysis.
- Metrology integration: Quantifying the hidden impact of gauge R&R precision on reported capability.
- Stability validation: Integrating Control Chart Builder to ensure process stationarity prior to index calculation.
- Economic simulation: Using simulation capabilities to calculate the ROI of process improvements.
A highlight of this session is our creative simulation study. We introduce a methodology to quantify the improvement degree by comparing measurement noise (P/T ratio) against true process shifts (Pp/Cp). It allows leadership to make data-driven decisions on whether to invest in better metrology or fundamental process engineering, prioritizing improvement investments through this ROI simulation framework.
Attendees leave with a blueprint of our grouped script and workflow package, a proven framework that has transformed continuous improvement strategies in semiconductor environments, establishing a repeatable, defensible standard for capability analysis at scale.
Presenters
Skill level
- Beginner
- Intermediate
- Advanced
