Lean Six Sigma Black Belt

As of now the concept of “Customer is King” is held in high esteem by all organisations. To please the customer, the focus is on reducing delivery time. As they say “Time Saved is Money Saved”. Lean Six Sigma is an approach that removes any extra unwanted processes, saves resources and time and makes the entire process streamlined. Lean Six Sigma optimizes organisational processes to increase productivity.

At MSP Training, we ensure the delegates get trained in the concepts of Lean Six Sigma and they are able to cope up with the problems they face in real-time situations at their organisation. The Lean Six Sigma Black Belt training helps the delegates to learn Lean concepts so that they are able to lead a team of professionals during project execution.

The concept of Lean aims at removing the waste processes due to which the project tends to divert away from its scope. Six Sigma, on the other hand, reduces processes variations and couples the processes together more tightly.

In the line of Lean Six Sigma, Lean Six Sigma Black Belt is the one that excels among all. Anybody interested in going through this course must be familiar with the concepts of Lean Six Sigma Green Belt. A Lean Six Sigma Black Belt certified professional leads a team of professionals who are already certified as Green Belt professionals.

IASSC (International Association for Six Sigma Certification™), the only third-party certification authority for Lean Six Sigma, certifies the delegates after passing an examination.

Exam

Exam Type: Closed Book Proctored Exam

Duration: 240 minutes

Questions: 150 Multiple Choice Questions

• • Define Phase
    • The Basics of Six Sigma
      • Meanings of Six Sigma
      • General History of Six Sigma & Continuous Improvement
      • What Does A Lean Six Sigma Project Deliver
      • The Problem Solving Strategy Y = f(x)
      • Voice of the Customer, Business and Employee
      • Six Sigma Roles & Responsibilities
    • The Fundamentals of Six Sigma
      • Defining a Process
      • Serious Quality Characteristics (CTQ’s)
      • Poor Quality Cost
      • The Pareto Analysis (80:20 rule)
      • Six Sigma - Measurement Standards
    • Selecting Lean Six Sigma Projects
      • Building a Business Case & Project Charter
      • Developing Project Metrics
      • Financial Evaluation & Benefits Capture
    • Undestanding The Lean Enterprise
      • Lean – An Understanding and its History
      • The Combination of Lean & Six Sigma
      • The Seven Waste Elements
      • 5S
        • Define Straighten, Shine, Standardize, Self-Discipline, Sort

   

  • Measure Phase
    • Process Definition
      • Cause & Effect / Fishbone Diagrams
      • Process Mapping, SIPOC, Value Stream Map
      • X-Y Diagram
      • Failure Modes & Effects Analysis (FMEA)
    • Six Sigma Statistics
      • Basic Statistics
      • Descriptive Statistics
      • Normal Distributions & Normality
      • Graphical Analysis
    • Measurement System Analysis
      • Precision & Accuracy
      • Bias, Linearity & Stability
      • Gage Repeatability & Reproducibility
      • Variable & Attribute MSA
    • Process Capability
      • Capability Analysis
      • Concept of Stability
      • Attribute & Discrete Capability
      • Monitoring Techniques
    • Analyze Phase
      • Patterns of Variation
        • Multi-Vari Analysis
        • Classes of Distributions
      • Inferential Statistics
        • Understanding Inference
        • Sampling Techniques & Uses
        • Central Limit Theorem
      • Hypothesis Testing
        • General Concepts & Goals of Hypothesis Testing
        • Significance; Practical vs. Statistical
        • Risk; Alpha & Beta
        • Types of Hypothesis Test
      • Hypothesis Testing with Normal Data
        • 1 & 2 sample t-tests
        • 1 sample variance
        • One Way ANOVA
      • Hypothesis Testing with Non-Normal Data
        • Mann-Whitney
        • Kruskal-Wallis
        • Mood’s Median
        • Friedman
        • 1 Sample Sign
        • 1 Sample Wilcoxon
        • One and Two Sample Proportion
        • Chi-Squared (Contingency Tables)
      • Improve Phase
        • Simple Linear Regression
          • Correlation
          • Regression Equations
          • Residuals Analysis
        • Multiple Regression Analysis
          • Non- Linear Regression
          • Multiple Linear Regression
          • Confidence & Prediction Intervals
          • Residuals Analysis
          • Data Transformation, Box Cox
        • Designed Experiments
          • Experiment Objectives
          • Experimental Methods
          • Experiment Design Considerations
        • Full Factorial Experiments
          • 2k Full Factorial Designs
          • Linear & Quadratic Mathematical Models
          • Balanced & Orthogonal Designs
          • Fit, Diagnose Model and Center Points
        • Fractional Factorial Experiments
          • Designs
          • Confounding Effects
          • Experimental Resolution
        • Control Phase
          • Lean Controls
            • Control Methods for 5S
            • Kanban
            • Poka-Yoke (Mistake Proofing)
          • Statistical Process Control (SPC)
            • Data Collection for SPC
            • I-MR Chart
            • Xbar-R Chart
            • U Chart
            • P Chart
            • NP Chart
            • Xbar-S Chart
            • CumSum Chart
            • EWMA Chart
            • Control Methods
            • Control Chart Anatomy
            • Subgroups, Impact of Variation, Frequency of Sampling
            • Center Line & Control Limit Calculations
          • Six Sigma Control Plans
            • Cost Benefit Analysis
            • Elements of the Control Plan
  Elements of the Response Plan