SEF-BUS7435 - Lean Six Sigma Black Belt Certification

Course Description

Prepare to provide an organization with the expertise of a certified Lean Six Sigma Black Belt. Course content is built on the American Society for Quality’s Body of Knowledge and can assist students in preparing for ASQ certification exam.  Black belts lead cross-functional teams to carry out improvement projects, implement tools of Six Sigma and provide statistical expertise for project teams. 
 

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

• The participant will understand and define the quality philosophy of Six Sigma and DMAIC-L
• The participant will identify benefits and objectives of Six Sigma
• The participant will be able to outline the Six Sigma implementation process
• The participant will identify and implement the DMAIC-L process including objectives and tools
• The participant will understand the organizational value of six sigma, its philosophy, goals, and definition.
• The participant will understand key drivers for business; understand key metrics/scorecards
• The participant will use the correct formula to calculate ROI
• The participant will use graphical, statistical, and qualitative tools to understand customer feedback. 
• The participant will calculate DPU, RTY, and DPMO sigma levels; understand 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. 
• The participant will understand and present financial measures and other benefits (soft and hard) of a project; understand and 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)  
• The participant will 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. 
• The participant will define the central limit theorem and understand its significance in the application of inferential statistics for confidence intervals, control charts, etc.
• The participant will describe and apply concepts such as independence, mutually exclusive, multiplication rules, complementary probability, joint occurrence of events, etc. 
• The participant will Identify, define, classify and compare continuous (variables) and discrete (attributes) data, and recognize opportunities to convert attributes data to variables measures.
• The participant will define, compute, and interpret measures of dispersion and central tendency, and construct and interpret frequency distributions and cumulative frequency distributions.
• The participant will 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.
• The participant will describe and apply binomial, Poisson, normal, chi-square, Student's t, and F distributions. 
•  The participant will recognize when to use hyper-geometric, bivariate, exponential, log-normal, and Weibull distributions. 
•  The participant will 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. 
• The participant will 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.
• The participant will define, select, and calculate Pp, Ppk, Cpm, and assess process performance 
• The participant will define, select, and calculate Cp, Cpk, and assess process capability 
• The participant will understand the cause of non-normal data and determine when it is appropriate to transform.
• The participant will perform exploratory data analysis by using multi-var studies to analyze variation, develop simple and multiple regression models, and calculate the correlation coefficient.
• The participant will use Design of Experiments to design, conduct and analyze experimental data.
• The participant will perform hypothesis testing and develop confidence intervals.
• The participant will understand appropriate uses of short-run SPC, EWMA, CuSum, and moving average
•  The participant will 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
•  The participant will define, select, and apply tools such as visual factory, kanban, poka-yoke, standard work, SMED, etc., in areas outside of DMAIC-Control.
• The participant will understand the terminology, purpose, and use of scale criteria (RPN) and be able to apply it to a process, product or service; understand the distinction between and interpret data associated with DFMEA and PFMEA
• The participant will use Mini-tab to perform required statistical analysis.  Mini-tab will be provided in the CPCC lab but students will have to purchase their own copy if they want to work outside of class using Mini-tab.

Notes

Instructional methods for this course are online self study, Class Lecture, Q&A, Computer lab exercises using Mini-tab

 

EVALUATION
1.    Certification Exam and demonstration of data analysis skills using Mini-tab
2.    Demonstration of Skills: online assessment and testing
3.    Class Participation: Group discussions and implementation planning
4.    Computer lab: Exercises and reports
Students must successfully complete all online modules, pass an in-class  certification exam, demonstrate proficiency of data analysis using  Mini-tab, and demonstrate proficiency in applying the skills in a  completed Six Sigma project.