|
Course
Introduction
Define
Phase Revisited
-
Scoping
complex cross-functional projects
-
Use of
quality function deployment to understand the voice of
the customer
-
Benefits
calculation & tracking
-
Planning
for change
-
Managing
your Black Belt Project
|
Advanced
Data Collection Planning
-
Planning
data collection for Black Belt projects
-
Sampling
techniques re-visited
-
Gauge R&R
for variable and attribute data (bias & linearity)
-
Statistical process control for attribute and variable
data
-
Process
capability revisited
|
Advanced
Statistics
-
Basic
statistics and probability revisited
-
Probability distributions
-
The
central limit theorem
-
Dealing
with non-normal data
-
Planning
and communicating data analysis
|
Hypothesis
Testing
-
Use of
inferential statistics
-
Significance testing route map
-
Analysis
of variable and attribute data
-
Power &
sample size
-
Non-parametric techniques
|
Multi-Variable Regression
-
Introduction to multiple regression
-
Analysis
of multi-variable data
-
Further
diagnostic techniques
-
Signpost
to advanced regression techniques
|
|
Design of
Experiments
-
Introduction to designed experiments (DOE)
-
Applications of DOE techniques
-
Basic
system optimisation
-
Screening
techniques using DOE
-
Optimising
a worked example
|
Advanced
Design of Experiments
-
Review of
Full Factorial Designs
-
Benefits &
limitations of basic DOE techniques
-
Introduction to Fractional Factorial
-
Screening
Designs
-
Overview
of advanced techniques
|
Advanced
Design of Experiments (Contd)
-
Taguchi
techniques
-
Mixed &
multi-level experiments
-
Response
surface designs
(CCD, CCF & Box-Behnken designs)
-
Introduction to evolutionary experimentation
(EVOP techniques)
Note: All
DOE modules Include SimWare Simulations & Minitab Analysis,
as well as practical experimentation examples
|
Control
Intro to
DFSS
Review &
Next Steps Planning
|
