Lean Six Sigma module                 Management     Quality Analysis

Competition is forcing firms to eliminate non-value added work and output inconsistency. While the concept of Lean addresses the former problem by removing process waste, the Six Sigma methodology solves the latter problem by minimizing process variation. This comprehensive course on all aspects of Lean and Six Sigma, gives you hands-on experience with essential quality improvement tools and techniques.

Students who successfully execute a Lean Six Sigma Project for an organization with documented evidence of process improvement results will also be eligible to receive a Lean Six Sigma Black Belt certification.

Prerequisite

an undergraduate degree in a technical subject OR a college-level course in statistics.

Course Content
  • Define Phase

    • Introduction to Six Sigma

    • Six Sigma Fundamentals

    • How to Select Projects

    • Scoping Your Project (High-level process maps, COPIS)

    • Project Mandates – Building Your Business Case

    • Building Your Project Team

 

  • Measure Phase

    • Process Mapping

    • Root Cause Analysis (Fishbone Diagrams, Tree Diagrams, etc.)

    • FMEAs

    • Data Collection (Sampling Strategies, Sample Size, Data Collection Sheets)

    • Static Statistics

    • Graphical Tools (Pareto's, Histograms, Box Plots, etc.)

    • Dynamic Statistics

    • Process Capability (Cp, Cpk, Pp, Ppk)

    • Measurement System Analysis/Gage R & R

 

  • Analyze Phase

    • Multi-Vari Analysis

    • Inferential Statistics

    • Introduction to Hypothesis Testing

    • Hypothesis Testing Normal Data (Z-, T-, and F-Tests; ANOVAs)

    • Hypothesis Testing Non-Normal Data (1-Sample Sign, 1-Sample Wilcoxon, Mood’s Median, Proportions tests)

    • Hypothesis Testing Discrete Data (Goodness of Fit, Chi Square Contingency Tables)

  • Improve Phase

    • ​Lean Tools (5S, Cellular Design, Plant Layout, POUS, Kanbans, etc.)

    • Correlation

    • Simple Linear Regression

    • Multiple Linear Regression

    • Design of Experiments (Full Factorials)

 

  • Control Phase

    • Human Side of Change

    • Dealing with Resistance

    • Improved Process Capability Analysis

    • Poka-Yoke

    • Risk Analysis

    • Statistical Process Control (SPC)

    • Six Sigma Control Plans

  • Test Preparation