Description
IASSC Universally Accepted Lean Six Sigma Body of Knowledge for black Belts: v Outlines:1.0 Define Phase1.1 The Basics of Six Sigma1.1.1 Meanings of Six Sigma1.1.2 General History of Six Sigma & Continuous Improvement1.1.3 Deliverables of a Lean Six Sigma Project1.1.4 The Problem Solving Strategy Y = f(x)1.1.5 Voice of the Customer, Business and Employee1.1.6 Six Sigma Roles & Responsibilities1.2The Fundamentals of Six Sigma1.2.1 Defining a Process1.2.2 Critical to Quality Characteristics (CTQ's)1.2.3 Cost of Poor Quality (COPQ)1.2.4 Pareto Analysis (80:20 rule)1.2.5 Basic Six Sigma Metricsa. including DPU, DPMO, FTY, RTY Cycle Time, deriving these metrics and these metrics1.3Selecting Lean Six Sigma Projects1.3.1 Building a Business Case & Project Charter1.3.2 Developing Project Metrics1.3.3 Financial Evaluation & Benefits Capture1.4The Lean Enterprise1.4.1 Understanding Lean1.4.2 The History of Lean1.4.3 Lean & Six Sigma1.4.4 The Seven Elements of Wastea. Overproduction, Correction, Inventory, Motion, Over processing, Conveyance, Waiting.1.4.5 5Sa. Straighten, Shine, Standardize, Self-Discipline, Sort2.0 Measure Phase2.1 Process Definition2.1.1 Cause & Effect / Fishbone Diagrams2.1.2 Process Mapping, SIPOC, Value Stream Map2.1.3 X-Y Diagram2.1.4 Failure Modes & Effects Analysis (FMEA)2.2 Six Sigma Statistics2.2.1 Basic Statistics2.2.2 Descriptive Statistics2.2.3 Normal Distributions & Normality2.2.4 Graphical Analysis2.3 Measurement System Analysis2.3.1 Precision & Accuracy2.3.2 Bias, Linearity & Stability2.3.3 Gage Repeatability & Reproducibility2.3.4 Variable & Attribute MSA2.4 Process Capability2.4.1 Capability Analysis2.4.2 Concept of Stability2.4.3 Attribute & Discrete Capability2.4.4 Monitoring Techniques3.0 Analyze Phase3.1 Patterns of Variation3.1.1 Multi-Vari Analysis3.1.2 Classes of Distributions3.2 Inferential Statistics3.2.1 Understanding Inference3.2.2 Sampling Techniques & Uses3.2.3 Central Limit Theorem3.3Hypothesis Testing3.3.1 General Concepts & Goals of Hypothesis Testing3.3.2 Significance; Practical vs. Statistical3.3.3 Risk; Alpha & Beta3.3.4 Types of Hypothesis Test3.4Hypothesis Testing with Normal Data3.4.1 1 & 2 sample t-tests3.4.2 1 sample variance3.4.3 One Way ANOVAa. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.3.5Hypothesis Testing with Non-Normal Data3.5.1 Mann-Whitney3.5.2 Kruskal-Wallis3.5.3 Mood's Median3.5.4 Friedman3.5.5 1 Sample Sign3.5.6 1 Sample Wilcoxon3.5.7 One and Two Sample Proportion3.5.8 Chi-Squared (Contingency Tables)a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.4.0 Improve Phase4.1 Simple Linear Regression4.1.1 Correlation4.1.2 Regression Equations4.1.3 Residuals Analysis4.2 Multiple Regression Analysis4.2.1 Non- Linear Regression4.2.2 Multiple Linear Regression4.2.3 Confidence & Prediction Intervals4.2.4 Residuals Analysis4.2.5 Data Transformation, Box Cox5.0 Control Phase5.1 Lean Controls5.1.1 Control Methods for 5S5.1.2 Kanban5.1.1 Poka-Yoke (Mistake Proofing)Design of experiments ( DOE)
