Brief Introduction
Sure Shot Way to Become a Master of Six SigmaDescription
As per Indeed, a job site's survey, Certified black belt salaries range between $100,000 - $200,000. Lean Six Sigma Black Belts command a premium in Job market. Black Belts deliver business results, so there are 75% more likely to be promoted that one without, but with similar domain experience.
The BoK is based on IASSC and ASQ curriculums.
Instructor is an Accredited Training Associate.
Every topic is application based. It starts with a business scenario and Six Sigma concepts are introduced subsequently. Data Files, Practices Files, Templates and Minitab Instructions are included for all the topics.
CBMG LEAN SIX SIGMA BLACK BELT BoK
Black Belt leadership
Expectations from a Black Belt role in market
Leadership Qualities
Organizational Roadblocks & Change Management Techniques
Mentoring Skills
Basic Six Sigma Metrics
CTQ Tree, Big Y , CTX
Including DPU, DPMO, FTY, RTY, Cycle Time, Takt time
Sigma scores with XL, Z tables, Minitab
Target setting techniques
Role of Benchmarking
Business Process Management System
BPMS and its elements
Benefits of practicing BPMS (Process centricity and silos)
BPMS Application scenarios
BSC Vs Six Sigma
MSA
Performing Variable GRR using ANOVA/X-bar R method
Precision, P/T , P/TV, Cont %, No. of Distinct Categories
Crossed & Nested Designs
Procedure to conduct Continuous MSA
Performing Discrete GRR using agreement methods for binary and ordinal data
Agreement & Disagreement Scores for part, operator, standard
Kappa Scores Computation for ordinal data and criteria for acceptance of gage
Statistical Techniques
Probability Curve, Cumulative Probability, Inverse Cumulative Probability (Example and procedure), Shape, Scale and Location parameters
Types of Distributions ( Normal, Weibull, Exponential, Binomial, Poission) & their interpretation and application
Identifying distributions from data
Central Limit Theorem - Origin, Standard Error, Relevance to Sampling
Example & Application of Central Limit Theorm
Sampling Distributions
Degrees of Freedom
t-distribution - Origin, relevance, pre-requisites, t-statistic computation
Chi-square distribution - Origin, relevance, pre-requisites, Chi-square statistic computation, Appoximation to discrete data
F-distribution - Origin, relevance, pre-requisites, F-Statistic and areas of applications
Point & Interval estimates - Confidence and Predictive estimates for Sampling distributions
Application of Confidence Estimates in decision making
Sampling of Estimates
Continuous and Discrete Sample Size Computation for sampling of estimates
Impact of Marigin of Error, standard deviation, confidence levels, proportion defective and population on sample size
Sample Size correction for finite population
Scenarios to optimize Sample Size such as destructive tests, time constraints
Advanced Graphical Methods
Depicting 1 or 2 variables (with example and procedure)
Dot Plot
Box Plot
Interval Plot
Stem-and-Leaf Plot
Time Series & Run Chart
Scatter Plot
Marginal Plot
Line Plots
Depicting 3 variables (with example and procedure)
Contour Plot
3D scatter Plot
3D Surface Plot
Depicting > 3 Variables (with example and procedure)
Matrix Plot
Multi Vary Chart
Inferential Statistics
Advanced Introduction to Hypothesis Tests
Significance and implications of 1 tail and 2 tail
Types of Risks - Alpha and Beta Risks
Significance & computation of test statistic, critical statistic, p-value
Sample Size for Hypothesis Tests
Sample Size computation for hypothesis tests
Power Curve
Scenarios to optimize Sample Size, Alpha, Beta, Delta such as destructive tests
Hypothesis Tests
1Z, 1t, 2t, Paried t Test - Pre-requisites, Components & interpretations
One and Two Sample Proportion
Chi-square Distribution
Ch-square Test for Significance & Good of Fit - Components & interpretations
ANOVA & GLM
ANOVA - Pre-requisites, Components & interpretations
Between and Within Variation, SS, MS, F statistic
2-way ANOVA - Pre-requisites, Interpretation of results
Balanced, unbalanced and Mixed factors models
GLM - Introduction, Pre-requisites, Components & Interpretations
Correlation & Regression
Linear Corrrelation - Theory and computation of r value
Non-linear Correlation - Spearson's Rho application and relevance
Partial Correlation - Computing the impact of two independent variables
Regression - Multi-linear Components & interpretations
Confidence and Prediction Bands, Residual Analysis, Building Prediction Models
Regression – Logistic(Logit) & Prediction - Components & interpretations with example
Dealing with Non-normal data
Identifying Non-normal data
Box Cox & Johnson Transformation
Process Capability
Process Capability for Normal data
Within Process Capability, Sub-grouping of data
Decision Tree for Type of Process Capability Study
Process Capability of Non-normal data - Weibull, Binomial, Poisson Process Capability and interpretation of results
Non Parametric Tests
Mann-Whitney
Kruskal-Wallis
Mood’s Median
Sample Sign
Sample Wilcoxon
Experimental Design
DOE terms, (independent and dependent variables, factors, and levels, response, treatment, error, etc.)
Design principles (power and sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, resolution, etc.)
Planning Experiments (Plan, organize and evaluate experiments by determining the objective, selecting factors, responses and measurement methods, choosing the appropriate design,
One-factor experiments (Design and conduct completely randomized, randomized block and Latin square designs and evaluate their results)
Two-level fractional factorial experiments (Design, analyze and interpret these types of experiments and describe how confounding affects their use)
Full factorial experiments (Design, conduct and analyze full factorial experiments)
Advanced Control Charts
X-S chart
CumSum Chart
EWMA Chart
Requirements
- Requirements
- Green Belt Certification & Green Belt Level working knowledge
- The participant should have sufficient exposure to his/her domain or industry, It is advisable to have a minimum of 5-8 years of industry work experience
Nilakantasrinivasan Janakiraman
4.5 Raiting
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