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Six Sigma Green Belt (SSGB)

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The next Six Sigma Green Belt course will take place in Toronto between Friday, September 12th and Sunday, September 14th, 2014.

The course runs all three days between 9:00 am and 5:00pm. The venue will be confirmed closer to the start date.

The cost of this course is $1,550.00 CAD.

The next Montreal course is scheduled for Fall, 2014.

Please feel free to contact the instructor, aboussetta [at] live [dot] ca (Alex Boussetta) for any inquiries you might have on the course or the course materials.

**After completing all requirements (perfect attendance and class participation) and passing a final exam on the third day, participants will obtain a Six Sigma Green Belt certification. The certificate is issued by McGill University.*Spaces are limited and course registration is processed on a first-come first-served basis.

About Six Sigma Green Belt training

For more information on Six Sigma Green Belt training at the Desautels Faculty of Management at McGill University, please contact: 

Saibal Ray
514-398-3270
saibal [dot] ray [at] mcgill [dot] ca (subject: Six%20Sigma%20website%20enquiry)

Instructor:
Alex Boussetta, Eng. M. Eng., PMP, SMC,
Certified Six Sigma Master Black Belt
Executive Consultant, Operational Excellence
Abacus Team Inc.
Email: aboussetta [at] live [dot] ca 

Course Objective

At the end of the training, the participants will be able to:

  • Understand the Six Sigma methodology
  • Apply it to transactional and operational processes, as well as products
  • Identify root causes of a problem (moderate complexity)
  • Find and implement solutions

Prerequisites

Participants should have at least two years of full-time, professional work experience (no internships), and a basic knowledge of computer tools such as Excel.

Please bring a standard calculator.

Note that team exercises are done on paper -not using computer tools/calculator- in order to focus on the use of the Six Sigma tools and concepts.

Course description:

1. Overview of Six Sigma

  1. Context of continuous improvement
  2. Applications
    1. Process improvements
    2. Product improvements
  3. Overview of the methodology and phases
    1. The 5 phases
    2. The metrics: Sigma, DPMO, yields, cost of poor quality

2. Statistical Notions Review

  1. Average, median, mode, range, standard deviation
  2. Histograms
  3. Behaviour of the Gaussian (normal) distribution

3. Recognize and Define Phase (Phase 1): Defining the Problem

  1. Selecting the right projects to improve
  2. Defining the project (project definition, SIPOC)
  3. Setting objectives
  4. Defining the project team

4. Measure Phase (Phase 2): Measuring the Actual Performance

  1. Defining metrics related to the objectives
    1. Brainstorming
    2. Cause and effect diagrams
    3. Overview of the metrics flow down
    4. Overview of the Quality Function Deployment
  2. Mapping the process or the product
  3. Analysis of the mapping
    1. Risks, failure modes (FMEA)
    2. Value added, non value added principles
  4. Data collection
    1. Planning the data collection
    2. Overview of measurement system analysis
  5. Process capability
    1. Metrics: Cp, Cpk, DPMO
    2. Interpretation

5. Analyze Phase (Phase 3): Identifying the Vital Factors

  1. Graphical tools and interpretation
    1. Pareto Chart, run chart, pie chart, etc
  2. Understanding the variation:
    1. Control charts: natural limits and specification limits
    2. Variation: random or assignable
  3. Selection of the factors to improve

6. Improve Phase (Phase 4): Selecting the Right Solution

  1. Selecting the right solution
  2. Creativity tools
  3. Scenario evaluations and selection
  4. Pilot and implementation plan

7. Control Phase (Phase 5): Maintaining the Improvements

  1. Setting a control plan
  2. Post mortem and audits
  3. Evaluation the gains
  4. Control charts and statistical process control overview

Course Method

The course is offered over three consecutive days, Friday to Sunday, from 9:00am to 5:00pm.

The Six Sigma methodology will be explained step by step. For each phase, tools will be explained and highlighted by examples. Several exercises and a case study will be used.

After completing all requirements (perfect attendance and class participation) and passing a final exam on the third day, participants will be certified as Six Sigma Green Belt practitioners.

Learning Outcomes

  • Being able to assess a situation and identify the right improvement projects to conduct
  • Being able to plan and manage an improvement project to ensure its successful completion
  • Being equipped with a proven methodology and tool box to conduct these project successfully
  • Being able to lead an improvement project, including the change management considerations

Instructional Method

  • A case study will be used as a global exercise. Students will progress through that case study, from the problem definition to the solutions.
  • Several other exercises will be done throughout the phases
  • An improvement project will be conducted by teams of students

Career Aspects

Knowledge of the Six Sigma methodology has become a prominent skill for professionals in Development, Manufacturing and Service companies. Experience and training in that methodology is usually an asset for Management, Quality Insurance, Engineering positions.

A Six Sigma Green Belt Certificate will be given after the exam correction.

Course Text

Material will be provided, prepared by Alexandre Boussetta

Evaluation

  • 2 evaluation methods will be applied
  • An exam (2 hours)
  • Completion in class of a case study in teams. Participation in the case study, the presentations, and use of the methodology will be monitored. This method ensures a better retention.

Course schedule:

Day 1

Readings

Introduction

Phase I: Recognize and Define

Class Items

1. Overview of Six Sigma

  1. Context of continuous improvement
  2. Applications
  3. Overview of the methodology and phases

2. Explanation of the evaluation process

  1. Project
  2. Exam

3. Statistical notions review

  1. Average, median, mode, range, standard deviation
  2. Histograms
  3. Behaviour of the Gaussian (normal) distribution

4. Recognize and Define phase (phase 1): defining the problem

  1. Selecting the right projects to improve
  2. Defining the project (project definition, SIPOC)
  3. Setting objectives
  4. Defining the project team

5. Presentation of a case study

  1. Team exercise : Define phase tools

6. Homework on team Green Belt project

Day 2

Readings

Phase II: Measure

Part III: Analyze phase

Class Items

7. Measure phase (phase 2): measuring the actual performance

  1. Defining metrics related to the objectives
  2. Mapping the process or the product
  3. Analysis of the mapping
  4. Team exercise : case study process map
  5. Data collection
  6. Process capability
  7. Team exercise: validating a data collection and calculating the process capability

8. Analyze phase (phase 3): identifying the vital factors

  1. Graphical tools and interpretation
  2. Understanding the variation:
  3. Selection of the factors to improve
  4. Team exercise : analysing data and graphs supplied in order to select the critical factors

9. Homework on team Green Belt project

Day 3

Readings

Part IV: Improve

Part V: Control

Class Items

10. Improve phase (phase 4): selection the right solution

  1. Selecting the right solution
  2. Creativity tools
  3. Scenario evaluations and selection
  4. Pilot and implementation plan
  5. Team exercise : brainstorming, selecting a solution, and setting up an action plan

11. Control phase (phase 5): maintaining the improvements

  1. Setting a control plan
  2. Post mortem and audits
  3. Evaluation the gains
  4. Control charts and statistical process control overview
  5. Team exercise: build a control plan (30 min)

12. Exam

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