Certificación Lean Six Sigma Green Belt

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DMAIC CYCLE: 128 hours

Module 1: Overview/Define  

A. Overview of Six Sigma  
B. DMAIC Methodology Overview
C. Defining Roles and Responsibilities
D. Tipos de variaciones. Affinity Diagram
E. Voice of the customer VOC- SIPOC diagram - CTQ tree.
F. Process Map, Cause and Effect Matrix,
G. Translating Customer Needs into Specific Requirements: QFD (Quality Function Deployment), level 1,2,3
H. Pugh Concept selection matrix
I. Fundamentos for process or product innovation: systemic innovation
J. Data management (data subset, stack, unstack data)- Advanced Pareto Chart –
K. Diagrama de causa y efecto
L. Understanding Lean Manufacturing. History of Lean
M. 8 wastes of Lean
N. Value Stream Mapping Actual state
O. Data measurement plan

Module 2: Measure

A. Basic Statistics and distributions (descriptive statistics). Central tendency. Normality.
B. Skewness and Kurtosis (descriptive statistics II), Confidence Interval,
C. Measurement System Analysis: Gage Repeatability and Reproducibility. R&R supervised workshop.
D. Kappa. Kappa in class simulation.                                                                                                          
E. Histogram. Precision and Accuracy
F. Serial independence                                                        
G. Sampling techniques and sampling in class simulation. Statistical Inference.
H. Calculando el nivel sigma
I. Process Capability/Process Performance (Cp, CpK, Pp, PpK, CpM). Attribute capability
J. Lean Accounting: Box Score
K. 5S+1
L. Monitoring techniques. Data analysis plan

Module 3: Analyze

A. Rolled Throughput yield RTY
B. FMEA
C. Analysis of distribution. Distribution fitting.
D. Box and Whisker Plots. Violin plots
E. Multi-Vari Studies
F. Scatter Diagram. Scatter matrix plot.
G. Pearson and Spearman correlation
H. Homoscedasticity. Introduction to regresion
I. Introduction to Hypothesis Testing. Error types 1 o Alpha and 2 o Beta.
J. Confidence Intervals
K. Parametric Methods:. T-Test, Z-test, Chi-Square, Power and Sample size calculation.
L. Analysis of Variance (ANOVA), Equal Variance Barlett test. F-Test ANOM, Welch ANOVA, Analysis of Mean (ANOM),
M. Cramer Contingency Coefficient
N. Statistical modeling for improvement: Akaike Information Criterion,AIC. Statistical Inference.
O. Basic Introduction to non Parametric test: Mann Whitney, Kruskal Wallis, Mood Median, Sign test

Module 4: Improve

A. Weibull Reliability analysis. Kaplan Meier Survival Probability estimate
B. Failure tree analysis,FTA
C. Conceptos de DOE. DOE Full Factorial
D. Introduction to DOE
E. DOE: Statistical Principles and Methods
F. DOE Planning
G. Full Factorial
H. 2 level Factorials
I. Fractional Factorials
J. DOE Supervised Plant workshop.
K. Value Stream Mapping Future State

Module 5: Control

A. Control Charts all types. Rational Sub-grouping
B. Non Shewart Control charts: EWMA and CUSUM charts
C. Process sigma culture calculation
D. Developing a Process Control Plan

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