Six Sigma Black Belt
A course designed beyond certification with unlimited support with one vision to help someone with a desire to become a successful Six Sigma professional/consultant to achieve their dream. Six Sigma Black Belt provides you with in-depth knowledge of Six Sigma along with the skills required to drive & mentor result oriented Six Sigma projects. Industry specific case studies and comprehensive training on statistical software (Minitab or R) with real-time data take the participant closer to the challenges they encounter tomorrow as Black Belt. Eight days of intense Six Sigma training spread across four weekends will help you go back to the workplace and practice the learnings and come back with hands-on experience & endless stories to share. With unmatched support in helping you drive a real-time project will make you a confident Black Belt ready to travel across the globe and drive high impacting projects.
Duration
08 Days – 80 Hours + 40 Hours of Project Guidance
Certification By
TÜV SÜD (An internationally recognised certification)
Objective
To enable participants with the necessary knowledge, methodologies & skills required to drive & mentor DMAIC Lean Six Sigma Black Belt projects in their respective industry.
Who Should Attend?
- Professionals with 4+ years of experience
- Any Professionals thoughtful to accelerate their corporate career
- Anyone who wants to consider Lean Six Sigma their career
- Certified Black Belts looking to equip themselves to be able to drive projects
Project Assistance
Free Assistance from an expert from your respective discipline
Essentials
Certified Green Belts with minimum of 1 year as Green Belts or Professionals with 4+ years of Industry experience
Course Program
- 1.0 Introduction to Quality
- 2.0 Quality Leaders (Juran, Deming, Shewhart, Ishikawa) (Videos to Understand)
- 3.0 Cost of Quality (COQ)
- 4.0 Cost of Poor Quality (COPQ)(Videos to Understand)
- 5.0 Optimum Quality Levels
- 6.0 Failure Mode & Effect Analysis (FMEA)
- 6.1 Create Process FMEA (Simulation to Understand)
- 6.2 Create Design FMEA
- 7.0 Key Performance Measures
- 7.1 Key Performance Indictors
- 7.2 Customer Satisfaction
- 7.3 Product Differentiation
- 7.4 Customer Loyalty Metrics
- 7.5 Leading & Lagging Indicators
- 7.6 Create Line of Sight
- 8.0 Key Business Drivers & their Impact
- 8.1 Profit/Margin (Practice to Understand)
- 8.2 Market Share
- 8.3 Net Present Value (NPV)
- 8.4 Cost Benefit Analysis (CBA)
- 8.5 Hard & Soft Benefits (Practice to Understand)
- 8.6 Cost avoidance & Cost reduction (Practice to Understand)
- 9.0 Organisation Goals & Six Sigma
- 10.0 Balanced Score Card& Six Sigma
- 11.0 History & Evolution of Six Sigma
- 12.0 Continuous Improvement
- 13.0 Basics of Six Sigma(Simulation to Understand)
- 14.0 Six SigmaApplications
- 15.0 Types of Six Sigma Projects
- 15.1 DMAIC
- 15.2 DFSS (DMADV/IDOV)
- 16.0 Organization Road Blocks
- 16.1 Organisation Structure & Culture
- 16.2 Common Causes of Six Sigma Failures
- 16.3 Stakeholder Analysis (Six Sigma Impact)
- 17.0 Change Management (Simulation& Videos to Understand)
- 17.1 Basics of Change Management
- 17.2 Readiness Assessment
- 17.3 Communication Plans to Overcome Barriers
- 18.0 Strategic Planning & Deployment
- 18.1 Importance of Lean Six Sigma
- 18.2 Hoshin Kanri (Policy Deployment) (Practice to Understand)
- 18.3 SWOT Analysis(Practice to Understand)
- 18.4 PEST
- 18.5 Business Contingency Planning
- 19.0 Team Management (Simulation & Videos to Understand)
- 19.1 Team Types & Constraints
- 19.2 Team Roles &Responsibilities
- 19.3 Team Member Selection Criteria
- 19.4 Team Success Factors
- 20.0 ProjectTeam Dynamics (Simulation to Understand)
- 20.1 Forming
- 20.2 Storming
- 20.3 Norming
- 20.4 Performing
- 20.5 Team Communication
- 21.0 Team Facilitation
- 21 Motivational Technique
- 22 Team Stages & Development
- 23 Team Communication
- 24 Team Leadership & Models
- 22.0 Team Dynamics (Simulation & Videos to Understand)
- 22.1 Group Behaviour
- 22.2 Meeting Management
- 22.3 Team Decision Making Methods
- 23.0 Team Training (Simulation to Understand)
- 23.1 Need Assessment
- 23.2 Delivery
- 23.3 Evaluation
- 1.0 Voice of Customer & Business(Simulation to Understand)
- 1.1 Collect Customer & Business Voices
- 1.2 Eliminate Vagueness & Ambiguity
- 1.3 VOC Clarity Table
- 2.0 Kano Model (Practice to Understand)
- 3.0 Benchmarking
- 3.1 Competitive
- 3.2 Collaborative
- 3.3 Best Practices
- 4.0 Customer Requirements to Process Requirements
- 4.1 Critical to X (X-Quality, Cost, Safety or any other )
- 4.2 CTQ Drill Down
- 4.3 Quality Function Deployment (Practice to Understand)
- 5.0 Project Section & Prioritisation (Practice to Understand)
- 6.0 Process Owners & Stakeholder Analysis
- 7.0 Project Charter (Practice to Understand)
- 7.1 Business Case
- 7.2 Problem Statement
- 7.3 Project Goal Statement
- 7.4 Project Team
- 7.5 Project Timeline
- 7.6 Project Scope
- 7.7 Expected Benefits
- 8.0 Financial Evaluation & Business Case
- 9.0 Develop Project Metrics
- 10.0 Project Short &Long Terms Gain (Practice to Understand)
- 11.0 Project Risk Analysis
- 12.0 Six Sigma Project Types
- 13.0 ProjectRoles & Responsibilities
- 13.1 Roles of Executive Leadership
- 13.2 Roles of Champion
- 13.3 Roles of Sponsor
- 13.4 Roles of Master Black Belt
- 13.5 Roles of Black Belt
- 13.6 Roles of Green Belt & Team
- 14.0 Project Management& Analytical tools
- 14.1 Gantt charts
- 14.2 Work Breakdown Structure
- 14.3 Critical Path Method (CPM)(Simulation to Understand)
- 14.4 Project Evaluation & Review Technique
- 14.5 RACI model
- 14.6 Activity Network Diagram
- 14.7 Tree Diagram
- 14.8 Matrix Diagram
- 15.0 Project Scope
- 16.0 SIPOC & Process Mapping (Simulation to Understand)
- 17.0 Project Performance Measurement
- 17.1 Define Performance Measurement
- 17.2 Process Critical Elements
- 17.3 Key Outputs
- 18.0 Project Tool Gate Review
- 1.0 Process Analysis & Documentation
- 1 Process Flow Charts
- 2 Work Instructions &Gap Analysis
- 2.0 Types of Data & Measurement Scale (Practice to Understand)
- 2.1 Continuous (Variable) Data
- 2.2 Discrete (Attribute) Data
- 2.3 Nominal Data
- 2.4 Ordinal Data
- 2.5 Interval Measurement
- 2.6 Ratio Measurement
- 3.0 Population & Sampling
- 3.1 Basics of Sampling
- 3.2 Calculate Sample size(Practice to Understand)
- 4.0 Type of Samples(Simulation to Understand)
- 4.1 Random Sample
- 4.2 Systematic Sample
- 4.3 Stratified Sample
- 4.4 Sequential
- 5.0 Basics of Statistics (Simulation to Understand)
- 5.1 Central Tendency
- 5.2 Dispersion
- 5.3 Proportion
- 6.0 Introduction to Statistical Software (Minitab)
- 6.1 Minitab Practice
- 6.2 Descriptive Statistics
- 6.3 Inferential Statistics
- 7.0 Probability
- 7.1 Basic Concepts
- 7.2 Independence Events
- 7.3 Mutually Exclusive Events
- 7.4 Addition & Multiplication Rules
- 7.5 Complimentary Probability
- 7.6 Occurrence of events
- 8.0 Statistical Distributions (Practice to Understand)
- 8.1 Normal
- 8.2 Binominal
- 8.3 Poisson
- 8.4 Chi-Square
- 8.5 Student’s T
- 8.6 F distribution
- 8.7 Hypergeometric
- 8.8 Bivariate
- 8.9 Exponential
- 8.10 Lognormal
- 8.11 Weibull
- 9.0 Probability of Distributions (Practice to Understand)
- 9.1 Frequency Distribution
- 9.2 Cumulative Frequency Distribution
- 9.3 Inverse Cumulative Frequency Distribution
- 10.0 Central Limit Theorem (Simulation to Understand)
- 11.0 Measurement & Data Collection
- 11 What is Measurement
- 12 Operation Definition
- 12.0 Data Collection Plan (Simulation to Understand)
- 12.1 Check Sheets
- 12.2 Data Coding
- 12.3 Data Cleaning
- 12.4 Data Collection Pitfalls
- 12.5 Avoid Data Collection Pitfalls
- 12.6 Seasonality Effect on Data
- 12.7 Data Collectors Training
- 13.0 Graphical Analysis (Practice to Understand)
- 11 Pareto
- 12 Scatter Plot
- 13 Box Plot
- 14 Histogram
- 15 Stem &Leaf Plots
- 16 Time Series Plot
- 17 Run Chart
- 18 Normality (using Minitab)
- 19 Graphical Summary
- 14.0 Metrology
- 14.1 Elements of Metrology
- 14.2 Calibration System
- 14.3 Traceability &Reference Standards
- 14.4 Control & Integrity of Standards
- 15.0 Variations& Measurement System Analysis
- 15.1 Understanding Variations (Simulation to Understand)
- 15.2 Measurement System Analysis (MSA)
- 15.2.1 Discrimination
- 15.2.2 Accuracy
- 15.2.3 Precision
- 15.2.4 Stability
- 15.3 GRR for Continuous data (Simulation to Understand)
- 15.4 GRR for Discrete Data (Simulation to Understand)
- 15.5 Control Charts & Stability (Simulation to Understand)
- 16.0 Measurement Systems to
- 16.1 Sales & Marketing
- 16.2 Engineering
- 16.3 Supply chain & Management
- 16.4 Research & Development
- 16.5 Customer Satisfaction
- 17.0 Baseline Process Performance (Practice to Understand)
- 17.1 Baseline Discrete Data (DPU, DPO,DPMO)
- 17.2 Baseline Continuous Data (Cp, Cpk, Pp, Ppk, Cpm)
- 17.3 Sigma Value (Short term & Long term)
- 17.4 Sigma Shift
- 18.0 Process Capability in Detail (Practice to Understand)
- 18.1 Natural Process Limits & Specification Limits
- 18.2 Design & Conducting Process Capability Studies
- 18.3 Specifications, Sampling Plan, Stability & Normality
- 18.4 Capability for Normal & Non-Normal Data
- 18.5 Process Performance (PPM, DPU, DPMO)
- 18.6 Transformations (Box-Cox & Johnson transformation)
- 18.7 Capability for Discreet Data
- 1.0 Identify Potential Causes (Practice to Understand)
- 1 Brain Storming
- 2 Affinity Diagram
- 3 Cause & Effect Diagram
- 4 Five Whys?
- 2.0 Process Analysis
- 2.1 Value Stream Mapping (Recap from Lean)
- 3.0 Data Analysis
- 4.0 NormalCurve & Normality Test(Practice to Understand)
- 5.0 Confidence Interval, Risk & P value
- 6.0 Hypothesis Testing -Null & Alternate
- 6.1 Significance of Confidence Level
- 6.2 Significance of Power
- 6.3 Statistical &Practical Significance
- 6.4 Sample Size for Hypothesis Tests
- 6.5 Point & Interval Estimates
- 6.6 Contingency Tables
- 7.0 Alpha & Beta Risks (Practice to Understand)
- 8.0 Hypothesis with Normal Data(Practice to Understand)
- 8.1 1 Sample T
- 8.2 2-Sample T
- 8.3 Paired T
- 8.4 One-Way Anova
- 8.5 Test of Variance
- 9.0 Hypothesis with Non- Normal Data(Practice to Understand)
- 9.1 1 Sample Sign
- .9.2 1 Sample Wilcoxon
- 9.3 Mann – Whitney
- 9.4 Kruskal- Wallis
- 9.5 Mood’s Median
- 9.6 Friedman
- 10.0 Hypothesis with Discrete Data (Practice to Understand)
- 10.1 1 Proportion
- 10.2 2 Proportions
- 10.3 Chi-Square
- 11.0 Multi Vari Chart (Practice to Understand)
- 12.0 Correlation & its Terminologies (Practice to Understand)
- 13.0 Correlation &Causation (Practice to Understand)
- 14.0 Regression Analysis (Practice to Understand)
- 15.0 Linear & Non-Linear Regression (Practice to Understand)
- 16.0 Simple & Multi-Linear Regression (Practice to Understand)
- 17.0 Residual Analysis (Practice to Understand)
- 18.0 Multivariate Tools (Practice to Understand)
- 18.1 Factor Analysis
- 18.2 Item Analysis
- 18.3 Discriminant Analysis
- 18.4 Simple & Multiple Correspondence Analysis
- 19.0 Design of Experiments (Practice to Understand)
- 19.1 Need for DOE
- 20.0 Terminologies
- 20.1 Factors, Levels, Response, Treatment
- 20.2 Blocks, Randomisation, Effects & Replication
- 20.3 DOE Plots: Main Effect & Interaction Plots
- 20.4 Confounding
- 21.0 DOE Designs
- 21.1 Full Factorial Experiments (Practice to Understand)
- 22.0 Fractional Factorial (Practice to Understand)
- 23.0 Latin Square Designs (Practice to Understand)
- 24.0 Balanced & Orthogonal Arrays (Practice to Understand)
- 25.0 Taguchi’s Design (Practice to Understand)
- 26.0 Experimental Resolutions
- 27.0 Confounding Effect
- 1.0 Generate & Evaluate Ideas (Simulations to Understand)
- 1 Brain Storming
- 2 SCAMPER
- 3 Six Thinking Hats
- 4 Benchmarking
- 5 doHow
- 6 Lean Solutions
- 7 TRIZ (Introduction)
- 2.0 Selecting Best Solution(Practice to Understand)
- 2.1 Multi-Voting
- 2.2 Pay-off Matrix
- 2.3 Criteria Matrix
- 3.0 Error Proofing
- 3.1 Prevention & Detection
- 3.2 Mistake Proofing &Examples
- 4.0 Assess Risk FMEA (Recap)
- 5.0 Piloting & Implementation
- 5.1 Pilot Solutions
- 5.2 Pilot Location
- 5.3 Pilot Success Criteria
- 6.0 Implementation
- 6.1 Plan for implementation
- 6.2 Stakeholder Analysis
- 6.3 Communication Plan
- 6.4 Implementation
- 1.0 What is Process Control?
- 2.0 Different Types of Process controls
- 3.0 Response Plan & Reaction Plan
- 4.0 Statistical Process Control (Practice to Understand)
- 4.1 Monitoring, Controlling of Process Performance
- 4.2 Identify & Select Critical Process Parameters
- 4.3 Subgrouping & Rational Subgrouping
- 4.4 SPC- Continuous Data (I-MR, Xbar R, X bar S)
- 4.5 SPC – Discrete Data (C,U,P,NP charts)
- 4.6 SPC - Time Weighted (CUSUM, EWMA,
- 5.0 Analyse Control Charts
- 6.0 Control Plan
- 7.0 Visual Control
- 8.0 Sustain Improvements
- 8.1 Lesson Learnt
- 8.2 Documentation
- 8.3 Trainings
- 8.4 Ongoing Evaluation
- 9.0 Benefit Computation
- 10.0 Project Closure
- 11.0 Celebration
- 1.0 Common DFSS/ DMADV Methodologies
- 1 Define
- 2 Measure
- 3 Analyze
- 4 Design
- 5 Validate
- 2.0 Design for X (DFX)
- 2.1 Design Constraints
- 2.2 Design Cost
- 2.3 Design for Manufacturability
- 2.4 Design for Test
- 2.5 Design for Maintainability
- 3.0 Robust Design
- 3.1 Robust Product Design
- 3.2 Tolerance for Design
- 3.3 Statistical Tolerancing
- 3.4 Robust Process Design
Trainers Profile
Certified Black Belt/Master Black Belt, with 100+ projects across Industries
Course Fee Includes
- Eight Days of Simulation Enabled training
- Minitab Training
- One Lean Six Sigma Green Belt Knowledge Book
- Five case studies
- Templates & real-life data sheets for practice
- doHow gamification
- Five sample question papers with answers
- Examination & certification cost(for TÜV & SÜD)
- Support in executing project for a period of 24 months
- Project evaluation by experts from your respective domain
- Exclusive invite to attend XergY’s students’GB & BB project presentations
- Refresher training at no charges
- Mentorship & assistance to accelerate your corporate career
- 100% Placement assistance
- Refreshment at the training venue
Certification Procedure (TÜV & SÜD only)
- Attend eight days training
- Successful completion of Black Belt certification exam conducted by TUV with 60% marks (at the end of the 8th day)
- Submission of the project (within eight months from the date of completion of the course)
Please contact us via below from for more info
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Our Courses
- 7 Quality Control
- Failure Mode & Effect Analysis
- Lean Management
- Lean Six Sigma Yellow Belt
- Lean Six Sigma Green Belt
- Lean Six Sigma Black Belt
- Six Sigma Yellow Belt
- Six Sigma Green Belt
- Six Sigma Black Belt
- Integrated Lean Six Sigma Green Belt + Black Belt
- Integrated Six Sigma Green Belt + Black Belt
- Lean Six Sigma Consultant Program
XergY: Six Sigma Black Belt
A course designed beyond certification with unlimited support with one vision to help someone with a desire to become a successful Six Sigma professional/consultant to achieve their dream.