This course is designed for those Six Sigma professionals who need to understand JMP's approach to data manipulation and analysis, measurement systems analysis, design of experiments and statistical process control in direct support of DMAIC breakthrough projects. Expectations are the participant has a working knowledge of statistics and Six Sigma concepts.
On-Site Course
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Public Course
Currently Unavailable
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Course Objectives:
Upon completion of the course the participants will be able to:
1. Understand and apply JMP to Six Sigma breakthrough projects
2. Use JMP for generating and reporting metrics and process capability
3. Determine appropriate sample sizes for studies using JMP
4. Evaluate measurement systems
5. Apply JMP to the manipulation and analysis of data
6. Create appropriate designed experiments using JMP
7. Demonstrate the impact and effectiveness of breakthrough solutions
8. Understand the links and application of JMP to iGrafx process modeling and simulation
9. Develop appropriate process controls using JMP
10. Introduce the participant to JMPs scripting capability
Course Outline:
Section I
Define
Preferences
Table organization and data types
Column commands
Row commands
Table commands
Saving graphs and files
Section II
Measure
Establishing project metrics in JMP
Cause and effect diagram
Summary statistics and confidence intervals
Variability studies, contour and surface plots
Sample size selection
Measurement systems analysis for variables
Measurement systems analysis for attributes
Distribution fitting for normal and non-normal data
Process capability analysis
Pareto analysis
Section III
Analyze
Nominal X Continuous Y Test mean and standard deviation
t test - paired
t test - two sample
Test for variances
One-way ANOVA
Nonparametric tests (optional)
N-way ANOVA Continuous X Continuous Y Simple linear regression
Multiple regression
ANCOVA Nominal X Nominal Y Test probabilities
Contingency analysis Continuous X and Nominal Y Logistics regression
iGrafx simulation data in JMP (optional)
Improve
Design of Experiments
Full factorial designs
Screening designs
Taguchi designs (optional)
Custom designs
Augmented designs
Optimization designs
Mixture designs (optional)
Rapid DOE features in iGrafx and JMP (optional)
Evaluating breakthroughs in JMP
Section IV
Section V
Control
Statistical principles for control charts
Control charts for variables
Xbar and R
Xbar and s
Individuals and Moving Range
Presummarize chart
Delta to target chart
z chart
Control charts for attributes
np
p
c
u
Creating standard reports and scorecards using JMP scripts
