Programa de certificación Six sigma Green Belt

Module 1: Overview/Define

A. Overview of Six Sigma
B. DMAIC Methodology Overview
C. Defining Roles and Responsibilities. COPQ
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 and 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. Data measurement plan

Module 2: Measure

A. Process Map, Cause and Effect Matrix, FMEA  
B. Basic Statistics and distributions (descriptive statistics). Central tendency. Normality.  
C. Skewness and Kurtosis (descriptive statistics II)  
D. Histogram. Precision and Accuracy                                                        
E. Calculando el nivel sigma
F. Serial independence
G. Sampling techniques and sampling in class simulation. Statistical Inference.  
H. Measurement System Analysis: Gage Repeatability and Reproducibility. R&R supervised workshop.
I. Kappa. Kappa in class simulation.                                                                        

J. Process Capability/Process Performance (Cp, CpK, Pp, PpK, CpM)  

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 regression
G. Introduction to Hypothesis Testing. Error types 1 o Alpha and 2 o Beta.
H. Confidence Intervals
I. Parametric Methods:. Analysis of Mean (ANOM), T-Test, Z-test, Chi-Square, Power and Sample size calculation.
J. Analysis of Variance (ANOVA), Equal Variance Barlett test. F-Test ANOM, Welch ANOVA
K. Cramer Contingency Coefficient
L. Statistical modeling for improvement: Akaike Information Criterion,AIC. Statistical Inference.
M. Basic Introduction to non Parametric test: Mann Whitney, Kruskal Wallis, Mood Median, Sign test

Module 4: Improve (total 28 hours)

A. Weibull Reliability analysis. Kaplan Meier Survival Probability estimate
B. Failure tree analysis
C. Conceptos de DOE
D. Introduction to DOE
E. DOE: Statistical Principles and Methods
F. DOE Planning
G. Full Factorial
H. 2 level Factorials. Countour and Surface Plot for optimum design
I. Intro to Fractional Factorials
J. DOE Supervised Simulation workshop (8 hours)

Module 5: Control (total 12 horas)

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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