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Lean Six Sigma Black Belt Certification Program: In-House Training

Lean Six Sigma Black Belt Certification Program: In-House Training

  • 30 Day Money Back Guarantee
  • Completion Certificate
  • 24/7 Technical Support

Highlights

  • Delivered Online or In-Person

  • Delivered at your location

  • UK Wide

  • 3 days

  • All levels

Description

Lean Six Sigma Black Belt Certification Program: In-House Training

This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners.

If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others.

Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course.

What you Will Learn

At the end of this program, you will be able to:

  • Use Minitab for advanced data analysis

  • Develop appropriate sampling strategies

  • Analyze differences between samples using Hypothesis Tests

  • Apply Statistical Process Control to differentiate common cause and special cause variation

  • Explain and apply various process capability metrics

  • Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data

  • Conduct and analyze simple and multiple regression analysis

  • Plan, execute, and analyze designed experiments

  • Drive sustainable change efforts through leadership, change management, and stakeholder management

  • Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps

  • Explain the main concepts of Design for Six Sigma including QFD

Introduction: DMAIC Review
  • IIL Black Belt Certification Requirements

  • Review Project Selection

  • Review Define

  • Review Measure

  • Review Analyze

  • Review Improve

  • Review Control

Introduction: Minitab Tool
  • Introduction to Minitab

  • Minitab basic statistics and graphs

  • Special features

  • Overview of Minitab menus

Introduction: Sampling
  • The Central Limit Theorem

  • Confidence Interval of the mean

  • Sample size for continuous data (mean)

  • Confidence Interval for proportions

  • Sample size for discrete data (proportions)

  • Sampling strategies (review)

  • Appendix: CI and sample size for confidence levels other than 95%

Hypothesis Testing: Introduction
  • Why use advanced stat tools?

  • What are hypothesis tests?

  • The seven steps of hypothesis tests

  • P value errors and hypothesis tests

Hypothesis Testing: Tests for Averages
  • 1 factor ANOVA and ANOM

  • Main Effect Plots, Interaction Plots, and Multi-Vari Charts

  • 2 factor ANOVA and ANOM

Hypothesis Testing: Tests for Standard Deviations
  • Testing for equal variance

  • Testing for normality

  • Choosing the right hypothesis test

Hypothesis Testing: Chi Square and Other Hypothesis Test
  • Chi-square test for 1 factor

  • ANOM test for 1 factor

  • Chi-square test for 2 factors

  • Exercise hypothesis tests - shipping

  • Non-parametric tests

Analysis: Advanced Control Charts
  • Review of Common Cause and Special Cause Variation

  • Review of the Individuals Control Charts

  • How to calculate Control Limits

  • Four additional tests for Special Causes

  • Control Limits after Process Change

  • Discrete Data Control Charts

  • Control Charts for Discrete Proportion Data

  • Control Charts for Discrete Count Data

  • Control Charts for High Volume Processes with Continuous Data

Analysis: Non-Normal Data
  • Test for normal distribution

  • Box-Cox Transformation

  • Box-Cox Transformation for Individuals Control Charts

Analysis: Time Series Analysis
  • Introduction to Time Series Analysis

  • Decomposition

  • Smoothing: Moving Average

  • Smoothing: EWMA

Analysis: Process Capability
  • Process capability

  • Discrete Data: Defect metrics

  • Discrete Data: Yield metrics

  • Process Capability for Continuous Data: Sigma Value

  • Short- and long-term capabilities

  • Cp, Cpk, Pp, Ppk capability indices

Analysis: Measurement System Analysis
  • What is Measurement System Analysis?

  • What defines a good measurement system?

  • Gage R&R Studies

  • Attribute / Discrete Gage R&R

  • Continuous Gage R&R

Regression Analysis: Simple Correlation
  • Correlation Coefficient

  • Simple linear regression

  • Checking the fit of the Regression Model

  • Leverage and influence analysis

  • Correlation and regression pitfalls

Regression Analysis: Multiple Regression Analysis
  • Introduction to Multiple Regression

  • Multicollinearity

  • Multiple Regression vs. Simple Linear Regression

Regression Analysis: Multiple Regression Analysis with Discrete Xs
  • Introduction

  • Creating indicator variables

  • Method 1: Going straight to the intercepts

  • Method 2: Testing for differences in intercepts

Logistic Regression: Logistic Regression
  • Introduction to Logistic Regression

  • Logistic Regression - Adding a Discrete X

Design of Experiments: Introduction
  • Design of Experiment

  • OFAT experimentation

  • Full factorial design

  • Fractional factorial design

  • DOE road map, hints, and suggestions

Design of Experiments: Full Factorial Designs
  • Creating 2k Full Factorial designs in Minitab

  • Randomization

  • Replicates and repetitions

  • Analysis of results: Factorial plots

  • Analysis of results: Factorial design

  • Analysis of results: Fits and Residuals

  • Analysis of results: Response Optimizer

  • Analysis of results: Review

Design of Experiments: Pragmatic Approaches
  • Designs with no replication

  • Fractional factorial designs

  • Screening Design of Experiment Case Study Repair Time

  • Blocking

Closing: Organizational Change Management
  • Organizational change management

  • Assuring project sponsorship

  • Emphasizing shared need for change

  • Mobilizing stakeholder commitment

Closing: Project Management for Lean Six Sigma
  • Introduction to project management

  • Project management for Lean Six Sigma

  • The project baseline plan

  • Work Breakdown Structure (WBS)

  • Resource planning

  • Project budget

  • Project risk

  • Project schedule

  • Project executing

  • Project monitoring and controlling and Closing

Closing: Design for Lean Six Sigma
  • Introduction to Design for Lean Six Sigma (DMADV)

  • Introduction to Quality Function Deployment (QFD)

Summary and Next Steps
  • IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

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