Solutions

Air Academy Associates Lean Six Sigma Black Belt

Course Length

160 Hours

Max Attendees

Course Description

Recognized throughout industry and proven within hundreds of companies, Air Academy Associates’ Lean Six Sigma Black Belt program teaches the tools and methodologies of DMAIC (Define, Measure, Analyze, Improve, Control) and simple, but effective, approaches to applying statistics. These tools are essential in establishing a knowledge-based approach for a continuous improvement culture throughout your organization. Students will apply the knowledge learned through exercises, simulations, and project work assigned by your company between the 1st and 2nd weeks and the 3rd and 4th weeks of the course. Students should have a project selected before beginning the class (Laptop needed for statistical software).

Upon completion of the class, students will have the option of becoming a certified Lean Six Sigma Black Belt. Air Academy is one of the most recognized Lean Sigma certifications in the country. The cost includes the exam fee and the project evaluation fee.

Course Objectives

Week 1

Project master strategy – DMAIC
What is value and the concepts of a value stream
IPO diagrams
Types of data – variable vs. attribute
Measures of data – mean, std, Cp, Cpk
Process flow diagrams, cause, and effects diagrams, constant vs. noise variables
COPQ
Quality measures of attribute data – FPY, RTY
Project selection/Project charter
Project teamwork
Change management
Understanding the voice of the customer (HOQ)
IPO to SIPOC diagram
Process mapping
Graphical analysis of data
- Pareto, histogram, box plots, scatter plot
Numerical measures of data
- Location – mean, median
Dispersion – variance, std
Measures of quality for variables data
- Cp, Cpk, sigma level, dpm, sigma capability
Measures of quality for attribute data
- FPY, dpu, dpmo, sigma capability
MSA

Week 2

Identifying potential causes of variation
CE diagram, brainstorming, process observation
7 classic types of wastes
Value added vs. Non-Value Added
Analyzing work
TAKT time, Cycle Time, Operator Loading
Central Limit Theorem
Confidence intervals
- Mean
- Proportions
Sample size
- Mean
- Proportions
Narrowing the focus – Nominal voting, Effort/Impact, Pairwise Comparison techniques
Hypothesis testing
- t-test
- f-test
- Test of proportions
- χ² test for independence
Workplace organization 5S
POKE YOKE
SMED
Batch vs. single piece flow
Cellular manufacturing
KANBAN
FMEA
Kaizen
Control charts
- X bar R
- IMR
- P chart
- C charts
Long term and short-term capability
Control plans
Project documentation

Week 3 (Existing GB’s moving to BB would start at week 3)

Value added vs. Non-value added
Time value maps
Value stream mapping
Simple linear Regression
Design of Experiments
Graphical analysis of data
Interactions
Graphical analysis of data
Interactions
Screening designs
Fractional factorial designs
DOE using a non-manufacturing process
3 level designs
- Screening
- Full factorial
Qualitative vs Quantitative factors
Testing for non-linear factors
Mixed factor mixed level data
Residual analysis
Working with historical data
All pairs testing
DOE Rules of Thumb (ROT)
- Sample size
- Design selection
- Statistical significance for mean and standard deviation models
- R², adjusted R² and tolerance values
Additional Lean improvement tools
- TPM
- OEE
- Flow and Pull
- Theory of constraints
- Kanban/Inventory
- Little’s Law
Advanced statistics
- Probability
- Distributions
  - Normal
  - Binomial
  - Poisson
Transforming non-normal data
ANOVA
Using hypothesis test for paired data and 1 sample tests
Mixed factor mixed level part 2
Historical data analysis
- Coding
- Screening
High throughput (all pairs) testing
Advanced DOE
- Randomization techniques
- Multiple responses
- Robust designs
- Use of interactions
- Modeling using screening designs
- DOE Pro surface contour plots
- DOE Pro multiple response optimizer