INTRODUCTION FOR LEAN SIX SIGMA GREEN BELT

Six sigma is a customer focused defined, problem solving methodology supported by statistical tools to reduce variation. Six sigma reduces variation through continuous process improvement leading to customer satisfaction. Six sigma is a combination of waste elimination to reduce cost and at the same time variation reduction to improve process capability and quality. SS Green Belt program is directed towards engineers that implement SS concepts in their day to day work and responsibilities. SS Green Belt participants are expected to lead improvement projects at their workplace.

LEARNING OUTCOME OF LEAN SIX SIGMA GREEN BELT

• Ability to use a structured approach to process improvement
• Ability to use DMAIC methodology – Define, Measure, Analyse, Implement & Control
• Skills to predict, prevent and control defects in a process
• Understanding of the elements of waste
• Skills to achieve sustainable quality improvement through process improvement
• Understanding of the tools of process discovery
• Understanding of variation in processes
• Skills to reduce variation in processes and achieve predicted outcomes
• Ability to identify, measure and analyse process potential
• Usage of inferential statistics
• Usage of hypothesis testing
• Understanding when to use which Six Sigma methodology
• Ability to use Capability Analysis to control processes
• Knowledge of the interdependence of Lean tools
• Skills to prevent, identify and control defects
• Understanding and use of statistical process control
• Skills to train, document, monitor, respond, and align systems
• Skills to provide sustainable & cost-effective improvement in processes

COURSE CONTENT

Session A

• Phase 1 – Project Selection
  • Course Logistics (rules, program layout, expectations)
  • What is Six Sigma? (introductory overview)
  • Project Selection
  • Project Planning and Charters
  • Internal Process Measures (KPI’s) & baseline setting
  • Introduction to DMAIC project management
  • VSM ( Value Stream Mapping)
  • Assessment
• Phase 2 – Define and Measure
  • Introduction to Minitab 17
  • Basic Statistical Concepts
    • Sampling power & size
    • Mean & average
    • Standard deviation
    • Process capability analysis
    • Machine capability
    • Graphs
  • Control Charts
    • Variable charts
    • Attributive charts
  • The Define Phase
  • Process Mapping
  • MSA (Measurement System Analysis)
    • GR&R (Gage repeatability & reproducibility)
    • Variable & attributive GR&R
  • Project presentation
  • Assessment

Session B 

• Phase 3 – Analyze and Improve
  • The Analyze Phase
  • Root Cause Problem Solving Tools
    • Fishbone
    • 5 Why’s
    • FTA
    • Is/Is not analysis
    • DOE (Design of Experiments) with Minitab 17
  • Basic Experimental Design (Hypothesis Testing)
  • Linear Regression
  • More DOE with Minitab 17
    • Steps to DOE
    • Noise factors
    • Randomization
    • Blocking
    • Repetition & replication
  • FMEA (Failure Mode Effect Analysis)
  • The Improve Phase
  • Assessment
  • Project presentation
• Phase 5 – Control
  • The Control Phase
  • Basic Cost Benefit Analysis
  • The Control Plan Strategy
  • Error proofing
  • Visual management
  • Levels of Control
  • Review and Wrap-up
  • Certification Test
  • Certification Project
• Final project presentation

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