• Six Sigma Black Belt Transactional / Health

Earn Your Black Belt Online from the University of Michigan

 

Develop advanced continuous improvement and quality engineering analysis skills used in Lean Six Sigma problem solving.


This course will provide you with the necessary skills to execute Lean Six Sigma techniques and strategies at the Black Belt level. Effective quality analysis often requires finding the right tool for the right problem, and this course examines many Lean Six Sigma analytical and problem solving techniques from descriptive statistics to advanced design of experiments.

After completing the program—including a series of case studies, a certification exam, and an improvement project at your organization—you'll earn a University of Michigan Lean Six Sigma Black Belt certification.




 
 

Transactional/Health Track



Using examples and case studies, this course focuses on applications primarily drawn from office and healthcare processes. Project results include reduced internal processing time, improved customer/patient satisfaction scores, reduced service costs, and more.

Demonstrate your ability to effectively apply Lean Six Sigma techniques to solve actual problems that affect performance in quality, lead time, and cost with a University of Michigan Lean Six Sigma Black Belt certification.

 

 

Learning Objectives

  • Understand and characterize variability through the graphical representation of data
  • Describe a process visually through process mapping techniques
  • Apply DMAIC problem solving process toward process improvement at the Black Belt skill level
  • Develop data collection plans and design experiments to test hypotheses
  • Interpret test results and draw conclusions based on data and the application of advanced statistical analysis techniques
  • Integrate statistical analysis tools, software, and problem solving methodologies
  • Develop recommendations and control plans to improve processes
  • Complete a process improvement project outside of class that demonstrates the application of the full DMAIC methodology


 

Course Topics

 
Time Commitment and Work Pace

Estimated: 120 self-paced hours

  • 90 hours (approximately) for lecture recordings and exercises
  • 20-40 hours for project work

All requirements must be completed within 365 days after your start date.

This is a self-paced online course consisting of 46 lecture modules with 10 test exercises (multiple choice tests to complete after each learning module) and 2 case study assignments. Most lecture tapes are approximately one hour in length. While the course is self-paced, we recommend completing two sessions/week.

Module Topics

The following modules are required, and you will also receive access to optional supplemental material.

  1. Course Overview (A) and Six Sigma Overview (B)
  2. DMAIC Problem Solving Process and DEFINE Phase
  3. Process Maps (Review of SIPOC/Swimlane; Current and Future State Maps)
  4. Value Stream Mapping (VSM) Analysis (Value Stream Process Redesign, Current State VSM, Value Add Timeline, Future State VSM)
  5. Value Stream Productivity Analysis (Takt, Nominal vs. Effective Process Time, Detractors, Operator Bar Charts, Capacity and Utilization)
  6. Sampling, Graphical Analysis Tools, and Descriptive Statistics (Normality, Hypothesis Tests)
  7. Introduction to Minitab (Tutorial)
  8. MEASURE: Measure the Current State - Continuous Outputs (Yield, PPM Defective, Mean vs. Variation)
  9. Measure Current State - Defect Count Data (DPMO, Rolled Yield, Tabulation, Check Sheets, and Pareto)
  10. Minitab Tutorial – Measure Phase
  11. Measuring Current State Using Survey Methods
  12. Assessing Process Stability – Variable Control Charts (X-Bar/Range, I/MR)
  13. Statistical Process Control: Attribute Charts (e.g., p-chart, u-chart)
  14. Minitab Tutorial - SPC
  15. Process Capability Analysis (Cp and Cpk) – Mean vs. Variation; Normal/Non-Normal Distributions
  16. Sigma Level and Six Sigma (Supplemental)
  17. Minitab Tutorial – Process Capability Analysis
  18. Data Collection and Qualitative Process Analysis (Data Collection, Cause and Effect, P-Diagram)
  19. Two Group Hypothesis Tests (F-tests, t-tests, 2 Proportion, ANOVA)
  20. One-Factor ANOVA – Operating Windows
  21. Power and Sample Size Planning (Optional)
  22. Minitab Tutorial – Hypothesis Testing
  23. IMPROVE Phase - Countermeasures and Short Term Verification
  24. IMPROVE Phase – Standardized Work and Load Leveling
  25. CONTROL – Methods of Control, Visual Controls, and Control Plans
  26. Failure Mode and Effects Analysis (FMEA) – Improving Methods of Control (Detection)
  27. Nonparametric Hypothesis Tests
  28. Categorical Data Analysis (Measures of Association)
  29. Minitab Tutorial – Categorical Data Analysis
  30. Transactional Measurement Systems Analysis (MSA) (Sources of Measurement Error, Accuracy and Repeated Measurement Studies)
  31. Attribute Agreement Analysis
  32. Minitab Tutorial – Transactional MSA
  33. Two Variable Analysis – Simple Linear Regression/Correlation
  34. Multiple Regression/Stepwise Regression/Best Subset
  35. Binary Logistic Regression Analysis
  36. Minitab Tutorial – Regression Analysis
  37. Multi-Vari Studies
  38. Principles of Design of Experiments (DOE)
  39. DOE – 2k Factorial
  40. Minitab Tutorial – DOE
  41. General Linear Model (GLM)
  42. Minitab Tutorial – GLM
  43. Tolerance Analysis and Adjustment
  44. Project Identification and Selection Techniques
  45. DMAIC Project Management
  46. Course Summary and DMAIC Gate Review Process
  47. Certification Exam Review
Certification Requirements

Participants pursuing their University of Michigan Lean Six Sigma Green Belt Certification are required to:

  • Complete all required online lecture modules
  • Complete all testing exercises and case studies with an overall cumulative score > 80%
  • Obtain an 80% or above on Black Belt Certification Exam
  • Obtain approval of Black Belt Project Proposal by U-M faculty
  • Successfully complete Black Belt Project (reviewed by U-M faculty)

Upon successful completion, you will be mailed your University of Michigan Lean Six Sigma Black Belt Certification.

Prerequisites

Participants are expected to have knowledge in statistical concepts and linear statistical models along with their application to data analysis. Recommended prerequisite topics include:

  • Descriptive statistics
  • Sampling and distributions (e.g., Normal)
  • Simple linear regression and correlation
  • Hypothesis testing

Successful completion of an undergraduate Statistics and/or Linear Statistical Models course is desired. Completion of Green Belt certification is desired but not required, especially if candidates have background in the above prerequisite topics.

Exam Format

The Final Black Belt Certification Exam is a comprehensive online exam consisting of 50 multiple choice questions and must be completed within a 4-hour time period. The exam format is open book/open note/open software. For some questions, students are given data and expected to use Minitab or other similar software to complete analyses and interpret results to answer questions.

Project Information

Lean Six Sigma DMAIC analysis may be applied to a vast array of process improvement opportunities. Participants are expected to complete a project to practice and apply course concepts.

Learn More

CEUs and Academic Credit

Upon successful completion of this 120-hour program, participants can earn 12 Continuing Education Units. CEU credits may not be applied toward a degree. The University of Michigan will provide necessary documentation upon request.

Students who are enrolled in MFG 461 will receive 3 academic credits from the University of Michigan and their Black Belt Certification upon successful completion of the course and Black Belt requirements.

Course Access & Technical Requirements

All lecture notes, homework sets, solutions, and tutorials are available through the course’s online learning management system.

Technical Requirements

Support

Administrative/Online Technical Support

Support staff are available via phone and email to help with administrative and technical issues during our normal business hours (Monday through Friday 8:00 a.m. to 5:00 p.m. Eastern Time). 

Content Questions/Certification Project Support

Candidates are welcome to contact the course instructors for content questions and project support. The instructors will provide support via e-mail, phone consultation, and/or online videoconferencing.

Program Faculty

 
 
Patrick Hammett
Patrick Hammett
Director of Academic Programs and Learning Systems, Integrative Systems + Design
Lead Faculty, Six Sigma Programs
Lecturer, Integrative Systems + Design
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Don Lynch
Don Lynch
Instructor, Integrative Systems + Design
VP of Operations, Battery Solutions
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Luis Guzman
Luis Guzman
Lecturer, Industrial & Operations Engineering
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