Lean Six Sigma Black Belt

Learn all the key skills associated with Lean and Six Sigma as well as how to apply the solutions you generate through learning change management skills. This Lean Six Sigma Black Belt course is designed to enable you to solve problems permanently in any industry or function using a DMAIC approach. As a Black Belt, you will be able to challenge the current state in any company and provide solutions which will transform the business: customer service, staff satisfaction, costs, profit. You will master the skills needed to achieve real business change.
Course Code
Course Delivery
Course Pre-requisite(s)
5SWO
1 Day
None
Objectives
Elements
Tools / Learning Approach
  • Master the Six Sigma DMAIC methodology and the related set of analytical tools.
  •  Apply the Lean Six Sigma knowledge and skills to successfully lead project teams.
  • Implement the DMAIC methodology and tools to accomplish Black Belt level projects.
  • Utilize the principles and practices of Lean Six Sigma to better frame and solve daily problems.
  • Improve business value for the customer and provider in a concurrent and synergistic way.
  • Deliverables of a Lean Six Sigma Project
  • The Problem Solving Strategy Y = f(x)
  • Defining a Process
  • Critical to Quality Characteristics (CTQ’s)
  • Cost of Poor Quality (COPQ)
  • Basic Six Sigma Metrics - including DPU, DPMO, FTY, RTY Cycle Time; deriving these metrics
  • Building a Business Case & Project Charter
  • Developing Project Metrics
  • Financial Evaluation & Benefits Capture
  • X-Y Diagram
  • Basic Statistics
  • Descriptive Statistics
  • Normal Distributions & Normality
  • Graphical Analysis
  • Precision & Accuracy
  • Bias, Linearity & Stability
  • Gage Repeatability & Reproducibility
  • Variable & Attribute MSA
  • Capability Analysis
  • Concept of Stability
  • Attribute & Discrete Capability
  • Monitoring Techniques
  • Multi-Vari Analysis
  • Classes of Distributions
  • Understanding Inference
  • Sampling Techniques & Uses
  • Central Limit Theorem
  • General Concepts & Goals of Hypothesis Testing
  • Significance; Practical vs. Statistical
  • Risk; Alpha & Beta
  • Types of Hypothesis Test
  • 1 & 2 sample t-tests
  • 1 sample variance
  • One Way ANOVA
  • Mann-Whitney
  • Kruskal-Wallis
  • Mood’s Median
  • Friedman
  • 1 Sample Sign
  • 1 Sample Wilcoxon
  • One and Two Sample Proportion
  • Chi-Squared (Contingency Tables)
  • Correlation
  • Regression Equations
  • Residuals Analysis
  • Non- Linear Regression
  • Multiple Linear Regression
  • Confidence & Prediction Intervals
  • Residuals Analysis
  • Data Transformation, Box Cox
  • Experiment Objectives
  • Experimental Methods
  • Experiment Design Considerations
  • 2k Full Factorial Designs
  • Linear & Quadratic Mathematical Models
  • Balanced & Orthogonal Designs
  • Fit, Diagnose Model and Center Points
  • Designs
  • Confounding Effects
  • Experimental Resolution
  • Data Collection for SPC
  • I-MR Chart
  • Xbar-R Chart
  • U Chart
  • P Chart
  • NP Chart
  • Xbar-S Chart
  • CuSum Chart
  • EWMA Chart
  •  Control Methods
  •  Control Chart Anatomy
  •  Subgroups, Impact of Variation, Frequency of Sampling
  •  Center Line & Control Limit Calculations
  • Cost Benefit Analysis
  • Elements of the Response Plan
  • Hands on examples.
  • Build a project charter
  • Understand and develop the Y = f(x) equation
  • Team memebers, types, communication styles (Exercise)
  • Normal and Non-Normal Distributions
  • Practical demonstrations of process theory
  • Advanced lean, Six Sigma and TOC principles.
  • Quality function deployment (QFD) to translate customer requirements into product/service features, performance measures,or opportunities for improvement.
  • Value Vs Non Value Vs Necessary Non Value
  • Waste identification.
  • Process Mapping (Exercise).
  • The Value Stream.
  • The Current State Map.
  • Value Stream Analysis.
  • The Future state map.
  • Lean Building Blocks.
  • Workplace Organisation – 5S.
  • 5S (Exercise).
  • Visual Management.
  • Error Proofing (Poke Yoke)
  • Employee Involvement & Continuous Improvement.
  • Quality at the source.
  • Thinking Lean (Exercise).
  • Graphical Analysis
  • Precision & Accuracy
  • Bias, Linearity & Stability
  • Gage Repeatability & Reproducibility
  • Variable & Attribute MSA
  • Capability Analysis
  • Central Limit Theorem
  • General Concepts & Goals of Hypothesis Testing
  • Significance; Practical vs. Statistical
  • Risk; Alpha & Beta
  • Types of Hypothesis Test
  • 1 & 2 sample t-tests
  • 1 sample variance
  • One Way ANOVA
  • One and Two Sample Proportion
  • Chi-Squared (Contingency Tables)
  • Correlation
  • Regression Equations
  • Residuals Analysis
  • Non- Linear Regression
  • Multiple Linear Regression
  • Confidence & Prediction Intervals
  • Residuals Analysis
  • Data Transformation, Box Cox
  •  Center Line & Control Limit Calculations
  • Cost Benefit Analysis
  • Elements of the Response Plan
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