Six Sigma Black Belt

Six Sigma Black Belt Course Overview

Six Sigma Lean Black Belts are skilled experts in the quality improvement approach who can apply Six Sigma concepts to business operations and take the reins of a quality improvement project. They are knowledgeable in the Six Sigma Methodology and are capable of taking charge of and effectively leading significant quality improvement initiatives. They are skilled in the application of six Sigma tools, processes, and fundamental principles.

Microsoft Azure course Curriculum

Define Phase: The Basics of Six Sigma

  • Meaning of Six Sigma
  • General History of Six Sigma & Continuous Improvement
  • Deliverables of a Lean Six Sigma Project
  • The Problem Solving Strategy Y=F(x)
  • Voice of the Customer, Business and Employee
  • Six Sigma Roles & Responsibilities

Define Phase: The Fundamentals of Six sigma

  • Defining a Process
  • Critical to Quality Characteristics (CTQ’s)
  • Cost of Poor Quality (COPQ)
  • Pareto Analysis (80:20 rule)
  • Basic Six Sigma Metrics: including DPU, DPMO, FTY, RTY Cycle Time, deriving these metrics

Define Phase: Selecting Lean Six Sigma Projects

  • Building a Business Case & Project Charter
  • Developing Project Metrics
  • Financial Evaluation & Benefits Capture

Define Phase: The Lean Enterprise

  • Understanding Lean
  • The History of Lean
  • Lean & Six Sigma
  • The Seven Elements of Waste: a. Overproduction, Correction, Inventory, Motion, Over processing, Conveyance, Waiting
  • 5S: 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

Measure Phase: Six Sigma Statistic

  • Basic Statistics
  • Descriptive Statistics
  • Normal Distributions & Normality
  • Graphical Analysis

Measure Phase: Measurement System Analysis

  • Precision & Accuracy
  • Bias, Linearity & Stability
  • Gage Repeatability & Reproducibility
  • Variable & Attribute MSA

Measure Phase: Process Capability

  • Capability Analysis
  • Concept of Stability
  • Attribute & Discrete Capability
  • Monitoring Techniques

Analyze Phase: Patterns of Variation

  • Multi-Vari Analysis
  • Classes of Distributions

Analyze Phase: Inferential Statistics

  • Understanding Inference
  • Sampling Techniques & Uses
  • Central Limit Theorem

Analyze Phase: Hypothesis Testing with Normal Data

  • 1 & 2 sample t-tests
  • 1 sample variance
  • One Way ANOVA: a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.

Analyze Phase: Hypothesis Testing

  • General Concepts & Goals of Hypothesis Testing
  • Significance; Practical vs. Statistical
  • Risk; Alpha & Beta
  • Types of Hypothesis Test

Analyze Phase: 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): a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.

Improve Phase: Simple Linear Regression

  • Correlation
  • Regression Equations
  • Residuals Analysis

Improve Phase: Multiple Regression Analysis

  • Non- Linear Regression
  • Multiple Linear Regression
  • Confidence & Prediction Intervals
  • Residuals Analysis
  • Data Transformation, Box Cox

Improve Phase: Designed Experiments

  • Mann-Whitney
  • Kruskal-Wallis
  • Mood’s Median
  • Friedman
  • 1 Sample Sign
  • 1 Sample Wilcoxon
  • One and Two Sample Proportion
  • Chi-Squared (Contingency Tables): a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.

Improve Phase: Full Factorial Experiments

  • 2k Full Factorial Designs
  • Linear & Quadratic Mathematical Models
  • Balanced & Orthogonal Designs
  • Fit, Diagnose Model and Center Points

Improve Phase: Fractional Factorial Experiments

  • Designs
  • Confounding Effects
  • Experimental Resolution

Control Phase: Lean Controls

  • Control Methods for 5S
  • Kanban
  • Poka-Yoke (Mistake Proofing)

Control Phase: Statistical Process Control(SPC)

  • Data Collection for SPC
  • I-MR Chart
  • Xbar-R Chart
  • U Chart
  • P Chart
  • NP Chart
  • X-S chart
  • X-S chart
  • CumSum Chart
  • EWMA Chart
  • Control Chart Anatomy
  • Subgroups, Impact of Variation, Frequency of Sampling
  • Center Line & Control Limit Calculations

Control Phase: Six Sigma Control Plans

  • Cost Benefit Analysis
  • Elements of the Control Plan
  • Elements of the Response Plan
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