University of Michigan Lean Six Sigma Black Belt 10-Day Live Certification Course Syllabus Instructor and Administrative Support Contact Information Lead Instructors: Pat Hammett, MBB, Ph.D. Phone: 734-936-1121 Luis Guzman, MBB, PhD. Nicole Friedberg, MBB Don Lynch, MBB, Ph.D. phammett@umich.edu lgguzman@umich.edu nicole.marie.tucker@gmail.com dplynch@umich.edu For Content Questions/Certification Project Support Issues from Instructors: bb-instructors@umich.edu (please use this Group Email for questions) Learning Management System (Online Course Support) Isd.engin.umich.edu/canvas For Administrative/Online Technical Support: isd-answers@umich.edu (please use this Group Email for non-course content related questions) Course Description The purpose of this course is to develop advanced continuous improvement and quality engineering analysis skills used in Lean-Six Sigma problem solving. This course includes examples drawn from office business process, healthcare, and manufacturing operations. Upon completion of the course, participants are expected to demonstrate their understanding of key course concepts through passing a Black Belt Certification Exam and successful completion of an industry project. Lean Six Sigma Black Belt 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. University of Michigan (U-M) Lean Six Sigma Black Belt Certification Requirements: Completion of all Lectures Completion of all Testing Exercises and Case Studies with cumulative score > 80% Completion of Certification Exam with Score > 80% Completion of a Certification Project (Approved by U-M Faculty) 1
Black Belt Certification Project Information See Online Learning Management System (Assignments Tab) for information on: Submitting Project Proposals (All projects proposals should be approved by U-M Faculty) Sample Projects Certification Project Report Writing Templates (Word Document Template) Teamwork Policy (Note: Our expectation is that each student will complete their own certification project report, though we will accept teams up to two upon request). Recommended Course 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; and hypothesis testing. Successful completion of an undergraduate Statistics and/or Linear Statistical Models course is recommended. The completion of a Green Belt Certification is desired, but not required (especially if a candidate has a background in the above prerequisite topics). Of note, we will cover all of the above topics in the class, but at an application/applied level. English proficiency is REQUIRED for this course. Pre-read/Supplemental Material: What is Six Sigma?, by Donald P. Lynch Statistics Refresher (See Canvas Learning Management System) Course Learning Management System (Internet Portal) All lecture notes, homework sets, solutions, and tutorials are available through the course learning management system via the internet. Course Text Book The course lecture notes have been developed from a variety of sources and created such that a textbook is NOT required. Many of the statistical tools and concepts covered are available through numerous web resources. If you prefer a reference book, several are listed below. Reference TEXTBOOKS: Doane and Seward (2007). Applied Statistics in Business & Economics, McGraw-Hill Breyfogle, F.W., Implementing Six Sigma, Wiley-Interscience Montgomery (2009). Design and Analysis of Experiments, 7 th Edition, Wiley. Montgomery (2009). Introduction to Statistical Quality Control, 6 th Edition Wiley. QUICK REFERENCE GUIDES (LOW COST OPTIONS): George, Rowlands, Price, and Maxey (2005). The Lean Six Sigma Pocket Toolbook. Useful Web Sites Statistics: www.itl.nist.gov/div898/handbook/ www.sjsu.edu/faculty/gerstman/statprimer/ (Recommended) statpages.org MINITAB Software: The assignment exercises and case studies involve the extensive use of Minitab Statistical Software for analysis. Lectures and assignments are developed for: Minitab 17 or higher (Minitab 13-16 also are fine though some menus may appear different than those shown in lecture) or equivalent software (SPSS, STAT SOFT, SAS). 2
TOPIC OUTLINE (Note: Lecture sessions covered in the testing exercises are noted in the table below. Students should complete all relevant sections prior to completing the exercise). Day Session Topic 1 1A/B Course Overview (A) and Six Sigma Overview (B) Graded Exercise (Session #) 1 2 DMAIC Problem Solving Process and DEFINE Phase 1 3 Sampling, Descriptive Statistics, and Basic Graphical Tools (Run Chart, Histogram, Box Plot) 1 4 Introduction to Minitab (Tutorial) Ex 1 (S# 1-4) 2 5 Process Maps (Review of SIPOC/Swim Lane; Current and Future State Maps) 2 6 Value Stream Mapping (VSM) Analysis (Value Stream Process Redesign, Current State VSM, Value Add Timeline, Future State VSM) 2 7 Value Stream Productivity Analysis (Takt, Nominal vs. Effective Process Time, Detractors, Operator Bar Ex 2 (S# 5-7) Charts, Capacity and Utilization) 3 8 MEASURE: Measure the Current State - Continuous Outputs (Yield, PPM Defective, Mean vs. Variation) 3 9 Measure Current State - Defect Count Data (DPMO, Rolled Yield, Tabulation, Check Sheets, and Pareto) 3 10 Minitab Tutorial Measure Phase Ex 3 (S# 8-10) Case Study 3 11 Measuring Current State Using Survey Methods 4 12 4 13 Assessing Process Stability Variable Control Charts (X-Bar/Range, I/MR) Statistical Process Control: Attribute Charts (e.g., p-chart, u-chart) 4 14 Minitab Tutorial - SPC 4 15 Process Capability Analysis (Cp and Cpk) Mean vs. Variation; Normal/Non-Normal Distributions 4 15B Sigma Level and Six Sigma (Supplemental) 4 16 Minitab Tutorial Process Capability Analysis Ex 4 (S# 12-16) 5 17 5 18 Data Collection and Qualitative Process Analysis (Data Collection, Cause and Effect, P-Diagram) Two Group Hypothesis Tests (F-tests, t-tests, 2 Proportion, ANOVA) 5 19 One-Factor ANOVA Operating Windows 5 20 Power and Sample Size Planning 5 21 Minitab Tutorial Hypothesis Testing Ex 5 (S# 17-21) 3
Day Session Topic 6 22 6 23 6 24 6 25 IMPROVE Phase - Countermeasures and Short Term Verification IMPROVE Phase Standardized Work and Load Leveling CONTROL Methods of Control, Visual Controls, and Control Plans Failure Mode and Effects Analysis (FMEA) Improving Methods of Control (Detection) 7 26 Nonparametric Hypothesis Tests 7 27 Categorical Data Analysis (Measures of Association) 7 28 Minitab Tutorial Categorical Data Analysis 7 29 Transactional Measurement Systems Analysis (MSA) (Sources of Measurement Error, Accuracy and Repeated Measurement Studies) 7 30 Gage R&R Study Testing Exercise (Session #) Ex 6 (S# 22-25) Case Study Case 1: Mandelbaum 7 31 Minitab Tutorial MSA Ex 7 (S# 26-31) 8 32 Two Variable Analysis Simple Linear Regression/Correlation 8 33 Multiple Regression/Stepwise Regression/Best Subset 8 34 Binary Logistic Regression Analysis 8 35 Minitab Tutorial Regression Analysis Ex 8 (S# 32-35) 9 36 Multi-Vari Studies 9 37 Principles of Design of Experiments (DOE) 9 38 DOE 2k Factorial 9 39 Minitab Tutorial DOE 9 40 General Linear Model (GLM) 9 41 Minitab Tutorial GLM Ex 9 (S# 36-41) 10 42 Tolerance Analysis and Adjustment 10 43 Project Identification and Selection Techniques 10 44 DMAIC Project Management 10 45 Course Summary and DMAIC Gate Review Process 10 46 Certification Exam Review Case 2: Coating Kramerica 4
The following modules are available online ONLY and consist of either supplemental topics or more comprehensive coverage of a topic discussed in the regular course. Lean-Productivity Analysis (Supplemental - Optional) Session Topic 51 Lean-Six Sigma Integration 52 Conducting a Kaizen Event 53 Productivity Analysis (Takt, Throughput, Nominal vs. Effective Time, Total Time in System) 54 Capacity and Utilization (Nominal vs. Effective) 55 Corrupting Influence of Flow Variability 56 Capacity Planning and Analysis 57 Load Leveling Analysis (Operator Bar Charts) Standard Work Analysis (Time observation, capacity 58 planning sheets, detail job instructions, Leadership Standardized Work) 59 Flow Improvements (One-Piece Flow, Little's Law, Layout) 60 Implementing Pull Systems (Kanban, FIFO, CONWIP) 61 Process Modeling and Monte Carlo Simulation Additional Topics (Supplemental - Optional) Session Topic 62 Scorecard and Desirability Index 63 Quality Function Deployment (QFD) 64 Visual Controls 65 Total Productive Maintenance (TPM) - OEE 66 Measurement Systems Analysis: Attribute Agreement Analysis 67 Introduction to Sample Size Planning (Single Statistics, Margin of Error, CV) 68 Complex Regression and Data Transforms 69 DOE Fractional Factorial Designs, 3k Factorial, 2k w/ Center Points 70 Minitab Tutorial Fractional Factorial DOE 71 Creativity Activation Techniques 72 Pugh Concept Selection Process 5
Assignments (All assignments must be submitted electronically per instructions below): Test Exercises: These exercises consist of multiple choice questions based on lecture concepts. (For the exercises, multiple lecture modules are incorporated (Lecture sessions numbers are listed on the syllabus outline). The test exercises are administered using online learning management system. They are graded automatically when you hit the submit button. Each student must complete their own exercises. o Note: You may print out a copy of the questions and work on them off-line prior to submitting your answers. If you are unsure of the intent of a question, please ask for clarification rather than assuming information not present in the question. You cannot retake a test exercise, so please make sure you have considered your answers carefully before submitting. Ex # Topics #1 DMAIC, Graphical Analysis Tools (Minitab) #2 Process Maps, Productivity Analysis #3 Measuring Current State: Yield, PPM, DPMO, and Pareto Analysis #4 Statistical Process Control and Process Capability #5 Hypothesis testing: F-test, t-test, ANOVA, 2 Proportions #6 Improve/Control Phase, FMEA #7 Categorical Analysis and Transactional MSA #8 Regression Analysis #9 Design of Experiments and General Linear Model Analysis Practice Exercise: Tolerance Analysis (See Assignments for Tolerance Analysis Practice Exercise) Case Study Assignments: These assignments are intended to reinforce key course content within an actual problem solving scenario. Participants may begin a case study after the session in which it is listed in the above topic outline. Case study reports must be emailed using a single report file (See Case Study Report Requirements and Electronic Submittal ). Acceptable file formats: (Adobe PDF or MS Word) Case # Topic Points #1 Mandelbaum Accounts Payable (or Pennypecker Vanes Mfg Case) 20 #2 Coating Kramerica (or Reliable Health Systems) 20 Case Study Assignments should be completed either individually or in teams of 2-4. For teams, please submit a single solution for all members. Additional case studies available upon request. 6
University of Michigan Lean Six Sigma Black Belt Certification Requirements Participants pursuing their University of Michigan Six Sigma Black Belt Professional Certification are required to meet the following: Complete all Black Belt course lecture modules Complete all testing exercises and case studies and obtain an overall cumulative score > 80% Obtain a score > 80% on the Black Belt Certification Exam (see About Certification Exam) Obtain approval from industry-sponsor supporting project proposal (email is fine). Note: This requirement only applies if required by your employer. Approval of Black Belt Project Proposal by U-M faculty Successful completion of Black Belt Project (See Black Belt Certification Project Selection and Report Requirements). Note: All projects are reviewed and approved by U-M faculty. Letter of support from industry-sponsor/process owner for project attesting to the impact or potential for impact of your Black Belt project (brief email is fine). ). Note: While U-M prefers a letter of support from all participants, this only applies if required by your employer. About the Black Belt Certification Exam 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. See course learning management system for exam dates and instructions to sign up for the exam. 7