SEF-BUS7435 - Lean Six Sigma Black Belt Certification

Course Description

Course Outline

Note:  This is a partial list of tools.
1.    Program Orientation and Introduction
2.    Enterprise-Wide Deployment
3.    History of organizational improvement/foundations of Six Sigma
4.    Financial benefits of Six Sigma
5.    Management and Planning Tools
6.    Financial benefits
7.    Six Sigma Improvement Methodology and Tools - Define; Tools:  Project Documentation, Project Management, VOC, ROI, COPQ analysis
8.    Six Sigma Improvement Methodology and Tools – Measure; Tools:  Descriptive Statistics, Measurement System Analysis, Capability Analysis, Basic Probability,  Sampling Techniques, Distribution Analysis
9.    Six Sigma Improvement Methodology and Tools – Analyze; Tools:  Simple and Multiple Regression Analysis, Hypothesis Testing, Parameter Estimation 
10.  Six Sigma Improvement Methodology and Tools – Improve; Tools:  Design of Experiments, Response Surface Methodology, EVOP     
11.  Six Sigma Improvement Methodology and Tools – Control; Tools:   Statistical Process Control and Advanced SPC
12.  Lean concepts; Tools:  Cycle Time Analysis, Process Modeling, Lean Implementation Road map
13.  Lean tools; Tools:  5S, Value Stream Mapping, Pull vs Push, Benchmarking
14.  Design for Six Sigma (DFSS)
15.  Terms and Glossary

Learner Outcomes

Upon successful completion, participants will be able to:

• Define the quality philosophy of Six Sigma and DMAIC-L
• Identify benefits and objectives of Six Sigma
• Outline the Six Sigma implementation process
• Identify and implement the DMAIC-L process including objectives and tools
• Describe the organizational value of six sigma, its philosophy, goals, and definition
• Identify key drivers for business; describe key metrics/scorecards
• Use the correct formula to calculate ROI
• Use graphical, statistical, and qualitative tools to understand customer feedback
• Calculate DPU, RTY, and DPMO sigma levels; describe how metrics propagate upward and allocate downward; compare and contrast capability, complexity, and control; manage the use of sigma performance measures (e.g., PPM, DPMO, DPU, RTY, COPQ) to drive enterprise decisions
• Present financial measures and other benefits (soft and hard) of a project; use basic financial models (e.g., NPV, ROI); describe, apply, evaluate, and interpret cost of quality concepts, including quality cost categories, data collection, reporting, etc. (application)  
• Define, select, and use 1) affinity diagrams, 2) interrelationship digraphs, 3) tree diagrams, 4) prioritization matrices, 5) matrix diagrams, 6) process decision program charts (PDPC), and 7) activity network diagrams
• Define the central limit theorem and understand its significance in the application of inferential statistics for confidence intervals, control charts, etc.
• Describe and apply concepts such as independence, mutually exclusive, multiplication rules, complementary probability, joint occurrence of events, etc. 
• Identify, define, classify and compare continuous (variables) and discrete (attributes) data, and recognize opportunities to convert attributes data to variables measures
• Define, compute, and interpret measures of dispersion and central tendency, and construct and interpret frequency distributions and cumulative frequency distributions
• Depict relationships by constructing, applying and interpreting diagrams and charts such as stem-and-leaf plots, box-and-whisker plots, run charts, scatter diagrams, etc., and depict distributions by constructing, applying and interpreting diagrams such as histograms, normal probability plots, Weibull plots, etc.
• Describe and apply binomial, Poisson, normal, chi-square, Student's t, and F distributions
• Recognize when to use hyper-geometric, bivariate, exponential, log-normal, and Weibull distributions
• Calculate, analyze, and interpret measurement system capability using repeatability and reproducibility, measurement correlation, bias, linearity, percent agreement, precision/tolerance (P/T), precision/total variation (P/TV), and use both ANOVA and control chart methods for non-destructive, destructive, and attribute systems
• Identify, describe, and apply the elements of designing and conducting process capability studies, including identifying characteristics, identifying specifications/tolerances, developing sampling plans, and verifying stability and normality
• Define, select, and calculate Pp, Ppk, Cpm, and assess process performance 
• Define, select, and calculate Cp, Cpk, and assess process capability 
• Describe the cause of non-normal data and determine when it is appropriate to transform
• Perform exploratory data analysis by using multi-var studies to analyze variation, develop simple and multiple regression models, and calculate the correlation coefficient
• Use Design of Experiments to design, conduct and analyze experimental data
• Perform hypothesis testing and develop confidence intervals
• Describe appropriate uses of short-run SPC, EWMA, CuSum, and moving average
• Apply appropriate lean tools (e.g., 5S, visual factory, kaizen, kanban, poka-yoke, total productive maintenance, standard work) as they relate to the control phase of DMAIC
• Define, select, and apply tools such as visual factory, kanban, poka-yoke, standard work, SMED, etc., in areas outside of DMAIC-Control.
• Describe the terminology, purpose, and use of scale criteria (RPN) and be able to apply it to a process, product or service; describe the distinction between and interpret data associated with DFMEA and PFMEA
• Use Minitab to perform required statistical analysis.  Minitab will be provided in the computer classroom but students will have to purchase their own copy if they want to work outside of class using Minitab

Notes

To Successfully complete Green Belt Certification, the course requirements are as follows:

• Active attendance and participation in classroom instructions
• Complete all online modules with post-test scores of > 80%
• In class project using Lean Six Sigma methodology
• Passing grade of > 80% on the final exam