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Lean Six Sigma: Black Belt



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This workshop is designed for Lean Six Sigma team leaders and expands upon the skill set taught in the Green Belt certification. The coursework includes instruction on modules in practical DMAIC applications, Failure Mode Effects Analysis, Advanced Lean, Advanced DOE, SPC for non-normal distributions, Optimization, Scheduling & Sequencing, effective and efficient teamwork strategies, as well as a variety of other tools and analysis methodologies. The PhD professors offer practical experience in guiding students through this workshop, assisting with the attendee case-study assignments.

Training accredited by Thayer School of Engineering at Dartmouth:

Professional certification is a process in which a person proves that he or she has the knowledge, as a basis, for performing a specific job. The proof comes in the form of a certification earned by passing quizzes, an exam, case studies, actual case or some combination of these items that are provided by an accredited organization. Accreditation is recognition that an educational institution has a certain standard of quality that other reputable organizations will honor. Without accreditation the certification provider may not provide the participant lasting value. Therefore, it is imperative that you receive your certification from a trusted, accredited institution. Dartmouth College, founded in 1769, is accredited by the Commission on Institutions of Higher Education (CIHE) of the New England Association of Schools and Colleges (NEASC). Accreditation is a non-governmental, non-profit, self-regulatory, peer review process based on rigorous standards.

Workshop Schedule:

*20 – (4-hour sessions); (2 sessions per week for 10 weeks), sessions run 10:00 am to 2:00 PM Eastern Time (approximately 80 hours of training) plus you must do two LSS case studies, (approximately 80 hours homework). Lean Six Sigma Black Belt Certification from Thayer School of Engineering at Dartmouth will be awarded upon successful completion of coursework, test, and two case studies. Please review the PDF for the Schedule options: Lean Six Sigma Black Belt Schedule

You Will Learn How To

  • Apply a wide range of process improvement techniques
  • Think about your organization as a collection of processes, with inputs that determine the output
  • Apply the five-step DMAIC model to organize process improvement activity
  • Successfully lead complex process improvement projects
  • Deliver meaningful, bottom-line operational excellence to the organization

Important Course Information

  • Who would benefit from this training?

    The Black Belt workshop is for those individuals that want to gain an in-depth knowledge of lean six sigma, and also be able to manage a lean six sigma project.

  • Prerequisites

    Participants must have completed the Green Belt program or have college level statistics (in the last 4 years) and are highly confident in their statistics capability before taking this workshop. We can evaluate a person’s background if needed – at no extra charge.

    Students are highly recommended to have a copy of the Black Belt Course Manual, in either Paper or PDF copy, to use as reference.

  • Homework

    Students must complete two case studies (choosing from manufacturing, finance, or healthcare) within 10 days of the last class (approx. 80 hours of homework). You will receive all case studies before the workshop begins, and will work on them over the duration of the training.


    A laptop with a functional copy of a statistical analysis package, Minitab, will be needed for this workshop. A trial copy of Minitab is usually sufficient if you wait to sign up for Minitab just prior to using it - to make sure the trial does not run out before you do the case studies and test. Minitab must run on a Windows PC.

    A headset with microphone is required, as using built-in speakers/microphone causes echo issues. Headsets give participants complete interaction with the instructor and other students.

  • Course Materials

    Students will be provided with a pdf of the class materials.

    All sessions are recorded, placed in a dropbox, and provided to participants for download to a computer in the event of a missed class or for review in the future.

    Exam Information: This take home exam is required. You must show your own original work on the exam and must work independently. Contact the instructor for help and guidance; do not contact other participants. You must complete the exam and email it to the instructor within 10 business days of the last session on day 20. Those who do not return the exam within 10 business days will not be eligible for the LSS Black Belt Certificate (unless advanced exception was granted by Dr. Lasky).

    This is an open notes exam so you can use all of the material that the instructors have provided to you. The exam will be primarily question and answer format and should be completed in approx. 20 hours. It is a pass/fail exam.

  • Certification Information

    Dartmouth College, Thayer School of Engineering, will issue a certificate of completion, in pdf format, to participants who successfully complete the case study and pass the take home quiz.

Course Outline

  • Days 1 and 2 (Refresh)

    Review Lean Six Sigma (LSS)

    Learn Basic Definitions (Process, Lean, Six Sigma) The DMAIC Model with Gate Reviews Basic Tools (Problem Statement, SIPOC) Performance Based Metrics, DPU, DPMO Practice with examples

    Voice of Customer (VOC)

    Describe the importance of VOC, and VOB Define and clarify CTQ and COPQ Understand how to segment Customers Learn how to capture Voice of Customer Describe the development of Critical Customer Requirements (CCR) Create a CCR Tree - Practice Learn how to use Kano Analysis

    Project Justification – Building the Business Case Utilizing the VOC

    Define the Business Case – Why? Learn to utilize the business case to justify the need for the project ROI of Quality / Project ROI Pitching the Case – VOC & VOB
  • Days 3 and 4 (Define)

    Lean Methods and Selection

    Simple, Structured Methods for Workplace Improvements Event-Based Process-Improvement Methods Shorter event-based activities

    Lean Metrics In-Depth

    Process metrics Organizational Metrics
  • Days 5 and 6 (Measure)

    Lean and Six Sigma Tools and Techniques

    Value Stream Mapping Histograms Pareto Cause & Effect Diagram DFMEA PFMEA
  • Days 7 and 8


    Refresher on Algebra

    Statistics Refresher & Minitab Introduction

    Types of Data (Attribute, Variable (continuous)) Measures of Central Tendency Concept of Standard Deviation Process Capability: Cp and Cpk Working with Minitab
  • Days 9 and 10 (Analyze)

    Scales of measurement 

    Confidence Interval Review Hypothesis Testing Review Sample Size Type II Error and Power Hypothesis Testing of Variance Tolerance and Prediction Intervals Tests on a Proportion Statistical Inference for Two Samples Using Minitab to Solve Advanced Stats Problems Sampling Strategies to Determine Quality Levels

Technical Estimating

    Importance Tips Examples

    DOE I

      DOE Review Analysis of Variance Blocks Full Factorial DOE Several Minitab Examples
  • Days 11 and 12

    Advanced SPC

    SPC Review Advanced Gage R&R Shewhart Rules SPC for Non Normal Data Minitab Examples
  • Days 13 and 14 (Improve)


Fractional Factorial DOE Taguchi DOE Central Composite Design Response Curve Methodology Multiple Linear Regression Numerous Minitab Examples
  • Days 15 and 16 (Control)

    Lean Culture

    5S Workplace Visual Workplace
  • Days 17 and 18

    CQI Kaizen (Rapid Process Improvement Courses)

    Building A Culture of Kaizen 8D & Mistake Proofing 8D – The steps to root cause and control Mistake proofing
  • Days 19 and 20


    Introduction to Optimization Review Key Definitions Linear Programming Integer Programming Programming with Excel Applications   Scheduling Definitions and Jargon Overview of Different Production Scheduling Environments
  • Single machine scheduling
  • Parallel machine scheduling
  • Flow shops
  • Others
  • Typical Assumptions used in Scheduling Performance Measures Scheduling Techniques (Algorithms and Heuristics)
  • Focus on Single Machine Scheduling Techniques
  • Brief visits to other environments
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Jul 22 - Sep 24 ( 10Day)
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Oct 19 - Dec 22 ( 10Day)
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