Lean Six Sigma Green Belt: Leading DMAIC Projects

What's inside

1. Level 1: What Lean and Six Sigma Are and Where They Came FromFree
   Learn where Lean (the Toyota Production System) and Six Sigma (Motorola) came from, and the problem each one solves: Lean removes waste and delay, Six Sigma reduces variation and defects.
2. Level 2: How Lean and Six Sigma Combine: Y = f(X)Free
   Learn how Lean Six Sigma brings flow and waste removal together with variation reduction, using the Y = f(X) idea to link a process output to the inputs that drive it.
3. Level 3: Roles and Belts in an Improvement Programme
   Learn what the Champion or Sponsor, Process Owner, Master Black Belt, Black Belt, Green Belt, Yellow Belt and team members each do, and where a Green Belt fits.
4. Level 4: The DMAIC Method and Its Tollgates
   Learn the five DMAIC phases, the question each phase answers, its main deliverables, and how a tollgate review decides whether a project moves on to the next phase.
5. Level 5: Green Belt Certification Bodies and This Course
   Learn that several bodies, including ASQ, IASSC and CSSC, certify Green Belts with different syllabi, exam formats and project requirements, and that this course teaches you to apply the method rather than to pass any one exam.
6. Level 6: The Running Example Project and the Excel Workbook
   Meet the running example used in every lesson, late and incorrect order dispatch at a spare-parts distribution centre, and set up the Excel project workbook with the Analysis ToolPak, with Minitab named as an alternative.
7. Level 7: Selecting and Scoping a Project Worth Doing
   Learn how to judge candidate improvement projects on customer impact, business value, feasibility and data availability, and how to scope the chosen one so a Green Belt can deliver it in a few months.
8. Level 8: Writing Problem and Goal Statements
   Learn to write a factual problem statement (what, where, when, how big, measured impact) with no blame or assumed cause, and a SMART goal statement linked to it.
9. Level 9: Building the Project Charter
   Learn to put together a full project charter covering the business case, problem and goal, scope, team and roles, milestones by DMAIC phase, and estimated financial benefit, ready for Sponsor sign-off.
10. Level 10: Voice of the Customer and CTQ Trees
    Learn to collect voice-of-the-customer data from complaints, surveys, interviews and service records, and turn vague needs into measurable Critical-to-Quality requirements with specification limits.
11. Level 11: Mapping the Process at High Level with SIPOC
    Learn to build a SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagram that sets the process start and end points and links them to the CTQs.
12. Level 12: Stakeholder Analysis and Communication Planning
    Learn to identify project stakeholders, rate their influence and support, and plan how to engage them and communicate with them so the project keeps backing through every phase.
13. Level 13: Detailed Process Maps and Swimlane Diagrams
    Learn to walk the real process (gemba) and draw a detailed swimlane map that shows steps, decisions, handoffs, rework loops and wait points, and marks each step as value-adding, business-necessary or non-value-adding.
14. Level 14: Value-Stream Mapping and Lead-Time Measures
    Learn to draw a current-state value-stream map with material and information flow, inventory or queues, and a timeline, and to calculate cycle time, lead time and process cycle efficiency.
15. Level 15: Data Types and Choosing the Right Measures
    Learn to tell continuous data from discrete (attribute) data, sort discrete data into counts, proportions and categories, and see how the data type controls which tools and sample sizes you can use later.
16. Level 16: Operational Definitions
    Learn to write operational definitions precise enough that different people measure the same thing the same way, covering what is measured, how, with what, by whom, and what counts as a defect.
17. Level 17: Data Collection Plans and Sampling
    Learn to build a data collection plan and choose a sampling approach (random, stratified, systematic, or rational subgrouping), with a basic idea of how sample size relates to precision.
18. Level 18: Measurement System Analysis Concepts
    Learn why the measurement system must be checked before baseline data is trusted, and what accuracy, bias, linearity, stability, resolution, repeatability and reproducibility each mean.
19. Level 19: Variable Gauge R&R in Excel
    Learn to plan and analyse a crossed gauge R&R study (parts × operators × repeat trials) for a continuous measure, and read %Study Variation and the number of distinct categories against common acceptance guidelines.
20. Level 20: Attribute Agreement Analysis
    Learn to check a pass/fail or category measurement system by testing agreement within each appraiser, between appraisers, and with a known standard, including the kappa statistic.
21. Level 21: Process Capability: Cp and Cpk in Excel
    Learn how Cp and Cpk compare the spread and centring of the example project's baseline data with the customer specification limits, and how to calculate both in Excel.
22. Level 22: Sigma Level, DPMO and the Measure Tollgate
    Convert defect counts into DPMO and a sigma level, record the example project's baseline, and confirm the Measure phase is finished at the tollgate review.
23. Level 23: The Seven Wastes in the Example Process
    Find and sort non-value-adding activity in the example process using the seven wastes (TIMWOOD), with unused skills often added as an eighth.
24. Level 24: Cause-and-Effect (Fishbone) Diagrams
    Run a structured brainstorm that lists the possible causes of the example project's problem on an Ishikawa diagram, grouped into standard categories.
25. Level 25: 5 Whys: Drilling to Root Cause
    Use the 5 Whys technique to trace the causes picked in the previous level down to root causes that can be acted on and checked with data.
26. Level 26: Pareto Analysis
    Rank defect categories or causes by frequency or cost with a Pareto chart, so the project focuses on the vital few.
27. Level 27: Scatter Plots and Correlation
    Check for relationships between a suspected input (X) and the output (Y) using scatter plots and the correlation coefficient.
28. Level 28: Hypothesis Testing in Plain Terms
    Learn the logic of hypothesis tests (null and alternative hypotheses, p-values, significance and errors) and how to choose the right test for the data type.
29. Level 29: Running Hypothesis Tests in Excel
    Test the example project's root-cause hypotheses in Excel, comparing means, variances and proportions, with Minitab named as an alternative.
30. Level 30: Regression in Outline and the Analyze Tollgate
    Fit a simple linear regression model of a validated input against the output, then bring all the evidence together to close the Analyze phase.
31. Level 31: Generating and Selecting Solutions
    Generate improvement ideas aimed at each verified root cause and choose the best ones in a structured, objective way.
32. Level 32: 5S and Standard Work
    Use 5S to organise the workplace and standard work to fix the best-known method for the improved example process.
33. Level 33: Mistake-Proofing (Poka-Yoke)
    Design mistake-proofing devices and checks that prevent or detect the errors behind the example project's defects.
34. Level 34: Flow and Pull
    Reduce lead time and work-in-process by improving flow and replacing push scheduling with pull, using takt time and Little's Law.
35. Level 35: FMEA: Assessing Solution Risk
    Run a process failure mode and effects analysis (FMEA) on the improved process to find and reduce risks before the pilot.
36. Level 36: Piloting and Proving the Improvement
    Plan and run a controlled pilot of the solutions, then prove the improvement statistically against the Measure-phase baseline.
37. Level 37: Building the Control Plan
    Write a control plan that sets out what will be monitored, how, by whom, and what to do when the process goes out of control.
38. Level 38: SPC: Individuals and X-bar Charts in Excel
    Set up statistical process control charts for continuous data in Excel to monitor the improved example process.
39. Level 39: Attribute Charts and Reading Control Signals
    Build control charts for attribute data and interpret all control charts using standard out-of-control rules.
40. Level 40: Sustaining Gains and Handing Over
    Lock in the improvement and formally transfer ownership of the controlled process to the process owner.
41. Level 41: Presenting Results and Closing the Project
    Learners build the final project storyboard for the running example. It traces the work from charter through baseline, root causes, pilot and control, and quantifies the before-and-after gains in Excel so the project can be formally closed with the sponsor.
42. Level 42: Final Challenge: Leading a Full DMAIC Project Exam
    A comprehensive capstone in which learners apply every stage of DMAIC to a new case dataset, from charter and SIPOC through MSA, capability, root-cause testing, solution selection with FMEA, and SPC-based control, then check each result against a worked answer workbook. It closes with a reminder that ASQ, IASSC, CSSC and other bodies certify Green Belts with different syllabi and requirements, and that learners should check their chosen body's syllabus before an exam.

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