06
Six Sigma Process Optimization: Reducing Ink Delamination Defects
A DMAIC project that used a fractional factorial DOE, ANOVA, and regression to cut ink delamination defects from a baseline of 200,000 DPM to about 0.03 DPM.
- Six Sigma (DMAIC)
- Design of Experiments
- Statistical Analysis
- Baseline defects
- 200,000 DPM
- Optimized defects
- ~0.03 DPM
- DOE
- 6 factors, 48 runs
Overview
- Applied the DMAIC methodology to a high-defect process
- Validated the measurement system with Gage R&R before experimenting
- Optimized process settings, improving yield and process capability indices
Problem
The process was producing ink delamination defects at a baseline of 200,000 defects per million. I used the DMAIC framework to define the problem, measure current performance, identify root causes, and improve the process settings.
Measurement system
Before collecting experimental data, I ran a Gage R&R study to confirm the measurement system was reliable, so that conclusions drawn from the data would reflect the process rather than measurement noise.
Experiment design and analysis
I designed a fractional factorial DOE covering 6 factors in 48 runs, then used ANOVA and regression to identify which parameters drove delamination.
Results
- Defects reduced from 200,000 DPM to ~0.03 DPM
- Improved yield and process capability indices
- Data-driven process validation backed by a verified measurement system