Description: This program is designed for those who are committed to becoming practitioners of the Lean Six Sigma methodology. Theory, application and tools used to increase efficiency and improve quality are covered in-depth. Advanced methods of analysis are reviewed. Students will learn to work in teams and present and implement solutions.
Objectives:
- Implement both Lean and Six Sigma methodology
- Detail the tools used to identify potential improvements and track progress
- Explain how data to is used to identify and diagnose opportunities and then track improvements in processes
- Employ a variety of graphical analysis methods are used to understand opportunities and evaluate outcomes
- Detail how improvement projects teams are managed
- Explain how customer needs and feedback are incorporated into projects
Duration: Up to 6 months
At Successful Completion: Digital Badge & Certificate
Modules:
- Introduction to Lean
- Writing Effective Problem Statements
- Introduction to Kaizen
- Using the A3 Report for Rapid Improvement
- SIPOC Mapping
- Understanding and Implementing 5S/6S
- Implementing and Facilitating Lean Huddles
- Visual Workplace
- Standard Work
- Mapping the Process
- Spaghetti Diagrams
- Gemba
- Constructing Project Charters
- Change Management
- Brainstorming, Affinity Diagrams & Team Voting
- Cause & Effect Diagrams & the Five Whys
- Pareto Charts and the 80/20 Rule
- Value Stream Mapping
- Kanban and Material Management
- Work Leveling/Load Balancing
- Work Cell Design & Improved Office/Facility Layout
- Rapid Changeover Techniques/SMED
- Process Control Plans and Control Charts
- Introduction to Six Sigma
- Failure Modes and Effects Analysis
- Error-Proofing/Mistake-proofing
- Controlling the Process
- Assessing Process Capability
- Introduction to Basic Statistics
- The Normal Distribution
- The Standard Normal
- Testing for Normality
- Graphical Analysis – The Boxplot
- Graphical Analysis – The Histogram
- Graphical Analysis – The Scatter Plot
- Central Limit Theorem and Confidence Intervals
- Introduction to Hypothesis Testing
- Data Collection and Sampling
- MSA – Gauge R & R Studies
- MSA – Attribute Agreement Analysis
- Process Capability Measures – Continuous
- Process Capability Measures – Discrete
- Correlation and Simple Linear Regression
- Discrete & Continuous Probability Distributions
- Hypothesis Testing – Mean and Median
- Test for Equal Variance
- Analysis of Variance
- Proportion Testing
- Chi-Square Tests
- Voice of the Customer – Kano Analysis
- Voice of the Customer – Net Promoter Score
