This course is targeted toward developing Lean Six Sigma process improvement project leaders.It provides a background on the Lean Six Sigma methodology and covers the tools and techniques necessary for leading successful process improvement projects.Students will bring a “live” process improvement project and supporting data (if available) to class where we will develop a clear project definition, conduct data analysis using inexpensive tools that require basic Excel knowledge and get a great start on an actual project.Upon completion of the course, an exam and a project, students will qualify for a Lean Six Sigma Green Belt certification.Between sessions, students will have homework that will be reviewed at the beginning of the next session.

Day 1- Introduction and Define Introduction to Six Sigma Methodology
History of Six Sigma
How is Six Sigma different from Total Quality or other Quality programs?
What is Six Sigma?
Value of Six Sigma
How does it work?
Key elements of Six Sigma
Approaches to Six Sigma
The project selection process – when to use each approach
Key organizational drivers and metrics
Organizational goals and Six Sigma projects
Enterprise strategy
LEAN concepts and tools
Value stream mapping
Identifying value-added and non-value added activities
Theory of constraints
Design for Six Sigma (DFSS) in the organization
How does Quality Function Deployment fit in the DFSS process?
Road maps for DFSS
Introduction to DMAIC (Define-Measure-Analyze-Improve-Control)

Day 2 – Define (continued) and Measure Process elements – define and describe process components and boundaries
Owners and stakeholders – the Voice of the Customer
Identifying and analyzing customers
Using the SIPOC
Methods for collecting customer feedback
Analyzing customer feedback
Translating feedback into requirements – CTQ (Critical to Quality)
Developing the project charter and problem statement
Defining the project scope
Introduction to management planning tools
Defining team roles and responsibilities for a Six Sigma project team
Team stages and dynamics
Project planning
Project risk analysis
Communication techniques and documentation
Defining key project metrics
Calculating process performance metrics – COPQ, DPMO, Yield
Team tools
Process modeling – “as is”

Day 3 – Measure (continued) and Analyze Collecting and summarizing data
Types of data and measurement scales
Data collection methods
Assuring data accuracy and integrity
Populations and samples – when to use each
Central limit theorem and sampling distribution
Measures of dispersion and central tendency
Probability concepts and distributions
Interpreting diagrams
Measurement system analysis
Process capability studies
Process performance vs. specification
Process capability indices
Process performance indices
Short-term vs. long-term capability
Computing the Sigma level
Applying sampling plans
Multi-vari studies
Interpret correlation coefficient and its statistical significance
Basics of hypothesis testing
Tests for means, variances and proportions
Paired-comparison tests
ANOVA – Analysis of variance
Chi Square

Day 4 - Improve and Control and Closeout Introduction to Improve
Design of experiments
DOE Terms
Interpreting main effects
Implement and validate solutions
Statistical Process Control – objectives and benefits
Understanding how rational subgrouping is used
Deliverables Review
Validate Savings
COPQ Review
Introduction to Control
Selection and application of control charts
Analysis of control charts
Control Plan Key Deliverables
Control Plan Components
Transition Plan Execution
Project Close Out
Exam Review
Wrap up

Details

Meets for 4 sessions: March 14, 21, 28, and April 04, 2017.

When

03/14/17 - 04/04/17 8:30 AM - 4:30 PM Eastern Time