Our world-class **Six Sigma Black Belt** online course is based on best in class **Universal Body of Knowledge**. Backed by experts in Lean Six Sigma, we bring the content of impeccable quality at your doorsteps.

We are *Accredited Training Organization*** of International Association for Six Sigma Certification (IASSC) **&** The Six Sigma Council**.

**Six Sigma Black Belt Course Details :**

- 18 chapters of IASSC & ASQ Lean Six Sigma Black Belt body of knowledge
**Total learning time of 150 hours**– an equivalent of 19 days of classroom training- Interactive audio-visual medium of virtual delivery
- Access anywhere and anytime – No travel required!
- Ample hands-on activities based on live case study with solution keys
- Exclusively designed for IT, ITES, manufacturing/process industry & services professionals
- Loaded with industry examples
- Interactive self-assessment quiz for every chapter
- Crisp downloadable takeaways for each chapter
- Elaborate Minitab/software procedure included.
- Excel templates for all important lean six sigma tools with step-by-step procedure

### **Course Features :**

- CBMG online training courses are developed based on the micro-learning concept. The duration of lecture videos is around 5 ~ 10 minutes/each.
- Lectures are usually in asynchronous video format and securely hosted in our LMS.
- All online courses are designed to take into consideration the learning experience and the knowledge acquisition of the participant in remote mode. Hence lectures have been segmented and grouped appropriately. For every video lecture, necessary tools, templates, case files, solution keys have been uploaded. Participants can download them on their local drive and practice.
- After every lesson/chapter, a self-assessment quiz is included for the participant to validate his/her knowledge.
- The delivery of the training content is by experienced IASSC Accredited Training Associate Instructors.

### Black Belt Certification – Way Forward

After taking our course, if you fulfill our Certification criteria below, you will receive **Canopus Lean Six Sigma Black Belt Certification** that is widely accepted in Industry and we are an **Accredited Training Organization of IASSC.**

At any time in future, you can additionally enhance your credibility as a **Certified Lean Six Sigma Professional **by appearing for certification evaluations of IASSC (www.issc.org) or ASQ (www.asq.org).

IASSC™ Accreditation does not constitute its’ approval or recognition of our own lean six sigma certification program. The only method to earn an IASSC certification is to successfully sit for and pass an official IASSC certification™ exam. We do upon request administer or provide access to IASSC Certification exams for an additional cost of $395 towards exam fees payable to IASSC.

**Pre-requisites **

- Green Belt Certification
**Industry or Domain exposure:**The participant should have sufficient exposure to his/her domain or industry, It is advisable to have a minimum of 8 years of industry work experience**Pass Pre-Test**for admission to Black Belt Course. As Black Belt is an advanced program, without active and hands-on Green Belt BoK, it would be highly difficult to cope with Black Belt BoK

### Canopus Black Belt Certification Criteria

- Completion of BB courseware
- Advanced Six Sigma online assessment\Complete 1 BB Project and get sign-off from the internal sponsor (Or) Submit Artefacts as a justification and defense of application knowledge. (Artefacts refers to application of any 1 or 2 BB BoK Tools to real life or 1 simulated scenario such as situation based cases provided by CBMG.)

### Validity

- The default access duration to the course for the participant will be specified at the time of registration is 120 days.
- However, course validity is for 1 year from date of registration. Hence if required, candidates can request to extend the access during the 1 year period from the date of registration.

### Price

120 days access with 1-year validity to Online Six Sigma Black Belt course + Canopus Certification is Rs.24,999 + 18% GST

### Contact Us Buy Online

### Six Sigma Black Belt Course Content

For the convenience of the student, 18 chapters covering the universal body of knowledge have been logically organized in Lean Six Sigma DMAIC structure as follows:

**CBMG LEAN SIX SIGMA BLACK BELT BoK (List below excludes GB BoK which is mandatory for BB)**

**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
- DPU, DPMO, FTY, RTY, Cycle Time, Takt time
- Sigma scores computation using different tools
- 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, Poisson) & their interpretation and application
- Identifying distributions from data
- Central Limit Theorem – Origin, Standard Error, Relevance to Sampling
- Example & Application of Central Limit Theorem

**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, Approximation 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 Margin 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**- Dot Plot
- Box Plot
- Interval Plot
- Stem-and-Leaf Plot
- Time Series & Run Chart
- Scatter Plot
- Marginal Plot
- Line Plots
- Contour Plot
- 3D scatter Plot
- 3D Surface Plot
- 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, Paired 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 Correlation – Theory and computation of r value
- Nonlinear 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, Subgrouping 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