The question is never "is this number bad", it is "did the process actually change". Control charts answer that with limits computed from the data rather than typed in, and capability studies say whether the process can meet the specification at all. Twenty-seven of the thirty analyses compute their figures in a deterministic engine, so the numbers do not move if the model is having a bad day.
What is in the box
- Control charts: I-MR, X-bar R, EWMA, CUSUM, attribute
- Process capability, including non-normal
- Sigma metrics and rolled throughput yield
- FMEA and control plan templates
- Free Cpk calculator
Lives at /dataforge once you are signed in
What you leave with
- A chart with limits you can defend
- A capability figure and what it means
- An FMEA and a control plan
- A reaction plan for when it drifts
The agents that do this work
How the work is done
DMAIC
Define, measure, analyze, improve, control, with a gate between each.
- Project workspace
- Five tollgates
- Charter template
- Capability study
- Control plan
Root cause analysis
Get past the symptom to the thing that is actually causing it.
- Fishbone
- Five whys
- Pareto
- Multi-vari study
- Regression
The other five
- Value & ROIWe cannot show what the improvement work returned.
- Continuous ImprovementIdeas come in and nothing happens to them.
- Process OptimizationThe process is slow and nobody agrees on why.
- LeanThere is waste everywhere and no system for removing it.
- Operational ExcellenceImprovement happens in pockets and never becomes how we work.