ASQ Primer Six Sigma Green Belt

Key “take away”

• Basic Statistics – 5 Steps and the significance of statistics in fundamental analysis using normal distribution (Minitab based)
• Introduction to Six Sigma – its history and present perspective
• Define Phase –Problem definition, Six Sigma Metric, base lining, time series analysis, improvement potential estimates and basics of data analysis (data types, location, variation, distribution). Fundamentals of Value Stream and using it for project pipeline development.
• Measure Phase – Data collection strategies, CLT application, MSA, capability analysis, identification product /process variables using multiple methods, Using Waste Analysis for immediate improvements, high & level prioritization (Cause & Effect Matrix) of impacting variables
• Analyze Phase – Detailed variable analysis using FMEA, Action planning for immediate gains, Data interpretation using various graphical analysis, correlation / regression, Hypothesis testing including Central Limit Theorem.
• Improve Phase – Validating highest impacting variables, Design of Experiments (2k, Full Factorial), Optimal Solution Identification. SMED techniques for cycle time reduction.
• Control Phase – Various Strategies of process control, Control Plan design, Training teams for new control plans, SPC, error proofing etc. Introducing Kanban. Project to Process Transition.

Who Should Attend”

• Must Certification for all aspiring career in Six Sigma (Green Belt / Black Belt / Master Black Belt)
• Junior and Middle Management Team
• Must for those members in the functions of technology, research and engineering responsible for setting specification limits and design of new product / processes as basic requirement.
• Quality Team, Management Representative and key people involved in improvement
• For those who want to learn & use tools and certification is just a bi-product.

Day 1

DATA ANALYSIS FUNDAMENTALS

• Basic Statistics – 5 steps with the concept and application
• Types of Data – Discrete (Nominal, Ordinal) and Continuous (Interval & Ratio)
• Location / Central tendency of Data (Mean, Median, Mode)*
• Spread of Data – Range, Variance, Standard Deviation & COV*
• Shape of Data and Predictions – Histogram, Distributions, Normal Distribution, probability Calculations*
• Introduction to Minitab* – a statistical software.

Day 2

IDENTIFY PHASE (Project Pipeline)

• Basics of Value and its Definition, its various dimensions and linkage to VA/NVA and MUDA.
• Value Stream Mapping, its analysis and understanding overall perspective for project pipeline.

Day 3

DEFINE PHASE

• Lean Six Sigma Road Map and purpose / key requirements of Define Phase.
• Six Sigma Metrics (Business, Primary, Negative consequence, Financial)
• Scoping Down Tools (Macro Map, VSM, Tree Diagram, Pareto Analysis*)
• Base lining the performance, Time series analysis* and target setting, Improvement potential estimates
• Problem definition, objective statements, metric tracking
• Team Constitution and Finalizing Team Charter with team

MEASURE PHASE – Part 1

• Measure Phase Road Map, Purpose and requirements
• Accuracy and Precision – definition and types
• Measurement System Analysis (MSA) for variable data* –terms, definitions and existing data based exercise
• Measurement System Analysis (MSA) for variable data* – Live Exercise with data collection, calculation and improvement plans

Day 4

MEASURE PHASE – Part 2

• Measurement System Analysis (MSA) for attribute data* –terms, definitions and class room exercise
• Measurement System Analysis (MSA) for attribute data* – Live Exercise with data collection, calculation and improvement plans
• Process Specification and Control Limits
• Definition of Process Capability (Cp, Zst, Cpk and Pp, Zlt, Ppk)*
• Capability analysis and interpretation for target setting and improvement*
• Analyze Phase Road Map, Purpose and requirements
• Identification product /process variables using Ishikawa Diagram, PFD diagnosis technique, KPIV / KPOV Matrix
• Initial Improvement Actions, Hidden Factories, VA/NVA, MUDA and other two Ms.
• High & level prioritization (Cause & Effect Matrix) of impacting variables

Day 5

ANALYZE PHASE – PART 1

• Detailed variable analysis using FMEA, Design of severity, occurrence and detection scales,
  FMEA – Action planning for immediate gains Creative Thinking Techniques
• Data interpretation using various graphical analysis*
• Sampling Methods

Day 6

ANALYZE PHASE – PART 2

• Central Limit Theorem (CLT) along with its 3 applications*
• Confidence Intervals* – basics, calculations and its significance with respect to sample size.
• Introduction to Hypothesis testing along with risks (alpha and beta)*
• Test of Means (1 sample Z, 1 sample t, 2 sample t, Paired t & ANOVA)*

Day 7

ANALYZE PHASE – PART 2…..continues

• Test of Variations (1 Variance, 2 variance)*
• Test of Proportions (1 Proportion, 2 Proportion and ANOM)*
• Correlation and Regression*
• Concept of Quick Change over (SMED) – Shingo Principles, Mapping of Cycles, In/Out and ESCAPE methodology.
• Work Balancing and Reliability Improvement Programs

Day 8

IMPROVE PHASE – PART 1

• Improve Phase Road Map, Purpose and requirements
• Kanban / Supermarket System – Types of Kanban & their applicability, Pace-maker and choice of Kanban and FIFO, Kanban Strategies
• Load Leveling (Mix, Volume &Heijunka)
• DOE – basic definitions, response, factors, levels, main effect, interaction etc.
• DOE – decision on levels, replicates and repeats based on understanding of hypothesis tests.

Day 9

IMPROVE PHASE – Part 2

• ANOVA and understanding its table as DOE basics*
• Understanding General Liner Model and Reducing Model*
• Setting Target (Mean or Variation?)
• 2k Factorial – Design, Analysis, writing equation, Optimization*
• Statapult Exercise*

Day 10

CONTROL PHASE

• Various Strategies of process control
• Control Plan design
• SPC* – Introduction, Interpretation for process control
• Mistake Proofing
• Project to Process Transition& Closure

* Indicates statistical software, Minitab is needed during training.

Prior Knowledge Requirement

• Prior exposure to improvement projects of any kind is useful.
• Lean Six Sigma Yellow Belt Certification or passing exam with minimum of 70% marks.