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ATN Lean Six Sigma Yellow Belt

Continual Improvement Lean Six Sigma

Course Length

16 Hours

Max Attendees

15

Course Description

The Lean Six Sigma Yellow Belt course is an introductory-level training program designed to provide participants with a foundational understanding of Six Sigma principles, methodologies, and tools. Day 1 of this course is equivalent to the Lean Six Sigma White Belt.  The course aims to equip individuals with the knowledge and skills of Lean Six Sigma methodologies necessary to contribute effectively to process improvement initiatives within their organizations. By acquiring Yellow Belt training, individuals can demonstrate their commitment to quality and their ability to contribute to the success of Lean Six Sigma projects. If the ATN Lean Six Sigma White Belt has been completed, the course length is only 8 hours.

Course Objectives
Day 1

  • Lean Tools hands-on simulation (Equivalent to “Intro to Lean Principles” class)
    • 8 Wastes
    • 5S
    • Visual Factory
    • Quick Changeover
    • Point of Use Storage
    • TPM
    • Plant Layout
    • Kaizen
    • Poke Yoke
    • Standard Work
    • Kanban
    • Takt Time
    • Work Leveling
    • Gemba Walk
  • Six Sigma hands on learning simulation (Equivalent to “Intro to Six Sigma” class)
    • Six Sigma defined
    • Introduction to DMAIC
    • Roles and responsibilities
    • Team management
    • Stakeholder management
    • Brainstorming techniques
    • Basic quality tools
    • Pareto
    • Cause and effect analysis
    • Histogram
    • Normal Distribution
    • Scatter diagram
    • Flow chart
    • DPU
    • DPMO
    • Introduction to project management
    • Data collection
    • Basic statistics

Day 2

  • Six Sigma hands on learning simulation
    • DMAIC
    • VOC/VOB
    • CTQ tree
    • Problem statement
    • SIPOC
    • Summary statistics
    • DPU/DPMO
    • Pareto
    • Precision vs Accuracy
    • 6Ms and variation
    • Fishbone diagram
    • Root cause analysis
    • Brainstorming countermeasures
    • Solution selection
  • Introduction to control charts
  • Special cause vs common cause variation
  • Introduction to MSA
  • Introduction to Regression Analysis
  • Introduction to Hypothesis Testing
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