Curriculum
- 7 Sections
- 129 Lessons
- 5 Days
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- INTRODUCTION5
- DEFINE23
- 2.11.1 The Basics of Six Sigma
- 2.21.1.1 Meanings of Six Sigma
- 2.31.1.2 General History of Six Sigma & Continuous Improvement
- 2.41.1.3 Deliverables of a Lean Six Sigma Project
- 2.51.1.4 The Problem Solving Strategy Y = f(x)
- 2.61.1.5 Voice of the Customer, Business and Employee
- 2.71.1.6 Six Sigma Roles & Responsibilities
- 2.81.2 The Fundamentals of Six Sigma
- 2.91.2.1 Defining a Process
- 2.101.2.2 Critical to Quality Characteristics (CTQ’s)
- 2.111.2.3 Cost of Poor Quality (COPQ)
- 2.121.2.4 Pareto Analysis (80:20 rule)
- 2.131.2.5 Basic Six Sigma Metrics
- 2.141.3 Selecting Lean Six Sigma Projects
- 2.151.3.1 Building a Business Case & Project Charter
- 2.161.3.2 Developing Project Metrics
- 2.171.4 The Lean Enterprise
- 2.181.3.3 Financial Evaluation & Benefits Capture
- 2.191.4.5 5S – Straighten, Shine, Standardize, Self-Discipline, Sort
- 2.201.4.2 History of Lean
- 2.211.4.1 Basics of Lean
- 2.221.4.3 Lean & Six Sigma Integration
- 2.231.4.4 The Seven Elements of Waste
- MEASURE15
- 3.1Process Mapping (As-Is Process)
- 3.2Data Attributes (Continuous Versus Discrete)
- 3.3Defining Metrics
- 3.4Measurement System Analysis
- 3.5Gage Repeatability And Reproducibility
- 3.6Data Collection Techniques
- 3.7Calculating Sample Size
- 3.8Data Collection Plan
- 3.9Understanding Variation
- 3.10Measuring Process Capability
- 3.11Calculating Process Sigma Level
- 3.12Rolled Throughput Yield
- 3.13Visually Displaying Baseline Performance
- 3.14Statistical Software Training
- 3.15Measurement Phase Review
- ANALYZE20
- 4.12.1 Process Definition
- 4.22.1.1 Cause & Effect / Fishbone Diagrams
- 4.32.1.2 Process Mapping, SIPOC, Value Stream Map
- 4.42.1.3 X-Y Diagram
- 4.52.1.4 Failure Modes & Effects Analysis (FMEA)
- 4.62.2 Lean Six Sigma Statistics
- 4.72.2.1 Basic Applied Statistics
- 4.82.2.4 Graphical Analysis
- 4.92.2.2 Descriptive Statistics
- 4.102.4.4 Monitoring Techniques
- 4.112.3.3 Gage Repeatability & Reproducibility
- 4.122.3 Measurement System Analysis
- 4.132.4.1 Capability Analysis
- 4.142.4 Process Capability
- 4.152.4.2 Concept of Stability
- 4.162.4.3 Attribute & Discrete Capability
- 4.172.2.3 Distributions
- 4.182.3.2 Bias, Linearity & Stability
- 4.192.3.4 Variable & Attribute MSA
- 4.202.3.1 Precision & Accuracy
- IMPROVE21
- 5.13.1 Patterns of Variation
- 5.23.1.1 Multi-Vari Analysis
- 5.33.1.2 Classes of Distributions
- 5.43.2 Inferential Statistics
- 5.53.2.1 Understanding Inference
- 5.63.2.2 Sampling Techniques & Uses
- 5.73.2.3 Central Limit Theorem
- 5.83.3 Hypothesis Testing
- 5.93.3.1 General Concepts & Goals of Hypothesis Testing
- 5.103.3.2 Significance; Practical vs. Statistical
- 5.113.3.3 Risk; Alpha & Beta
- 5.123.4 Hypothesis Testing with Normal Data
- 5.133.4.1 1-sample & 2 sample t-tests
- 5.143.4.2 One-Way ANOVA
- 5.153.4.3 Two-Way ANOVA
- 5.163.5 Hypothesis Testing with Non-Normal Data
- 5.173.5.1 Mann-Whitney
- 5.183.5.2 Kruskal-Wallis
- 5.193.5.3 Mood’s Median
- 5.203.5.4 Friedman
- 5.213.5.5 1 Sample Sign
- IMPROVE25
- 6.14.1 Simple Linear Regression
- 6.24.1.1 Correlation
- 6.34.1.2 Regression Equations
- 6.44.1.3 Residuals Diagnostics Analysis
- 6.54.2 Multiple Regression Analysis
- 6.64.2.1 Non-Linear Regression
- 6.74.2.2 Multiple Linear Regression
- 6.84.2.3 Confidence & Prediction Intervals
- 6.94.2.4 Residuals Diagnostics Analysis
- 6.104.2.5 Data Transformation, Box Cox Technique
- 6.114.3 Designed Experiments
- 6.124.3.1 Experimental Objectives
- 6.134.3.2 Experimental Methods
- 6.144.3.3 Experiment Design Considerations
- 6.154.4 Full Factorial Experiments
- 6.164.4.1 2k Full Factorial Designs
- 6.174.4.2 Linear & Quadratic Mathematical Models
- 6.184.4.3 Balanced & Orthogonal Designs
- 6.194.4.4 Fit, Diagnose Model and Center Points
- 6.204.5.2 Confounding Effects
- 6.214.5.3 Experimental Resolution
- 6.224.6 Advanced Experiments
- 6.234.5 Fractional Factorial Experiments
- 6.244.6.1 Steepest Ascent Analysis
- 6.254.5.1 Designs
- CONTROL20
- 7.15.1 Lean Controls
- 7.25.3.1 Control Methods for 5Sy
- 7.35.3.2 Kanban (Pull Systems)
- 7.45.3.3 Poka-Yoke (Mistake Proofing)
- 7.55.2 Statistical Process Control (SPC)
- 7.65.4.1 Data Collection for SPC
- 7.75.4.2 I-MR Chart
- 7.85.4.3 Xbar-R Chart
- 7.95.4.4 U Chart
- 7.105.4.5 P Chart
- 7.115.4.6 NP Chart
- 7.125.4.7 Xbar-S Chart
- 7.135.4.8 CumSum Chart
- 7.145.4.9 EWMA Chart
- 7.155.4.10 Control Methods
- 7.165.3 Six Sigma Control Plans
- 7.175.6.1 Cost Benefit Analysis
- 7.185.6.2 Elements of the Control Plan
- 7.195.6.3 Elements of the Response Plan
- 7.20EXAM DAY ON THE LAST DAY.