Lean Six Sigma Transactional Green Belt

Lean Six Sigma Transactional Green Belt – overview

Lean Six Sigma Transactional Green Belt training participants receive a thorough exposure to the tools and methods that are necessary to successfully lead or participate in Lean DMAIC improvement projects in a Transactional or Service environment. Appropriate tools for the application of the Lean DMAIC improvement methodology will be introduced along with hands-on exercises and tutorials to ensure rapid learning and knowledge retention. Training material is supplied in hard copy format for delegate use.

Full details below or download course outline.

Learning objectives

This programme is designed to ensure that Green Belts are provided with a good understanding of, and the ability to apply, the most widely used tools and techniques.

By the end of the programme participants will have completed, or gone substantially towards completing, a project from their own organisation. The training will encompass:

  • The history of Lean and Six Sigma
  • The DMAIC process improvement roadmap
  • How to establish customer requirements
  • How to measure and quantify process performance
  • Lean tools and their application
  • Statistical and other analytical methods for identifying and understanding sources of variation
  • Experimental design techniques leading to mathematical models of products and processes
  • Sustainment and control techniques
  • Developing a business-wide strategic understanding of the business needs
  • Understanding key statistical concepts to aid in the development of sustainable improvements
  • Presenting data more effectively

See also the detailed ‘learner outcomes’ for each module, below.

Who should attend?

All business improvement professionals who are tasked with identifying improvement issues within their organisation.

Lean Six Sigma Green Belts are expected to be able to run small individual projects themselves, and to participate in larger projects which are typically led by Black Belts. Candidates should have good communication skills, experience of team working to improve processes or solve problems, good IT skills and ideally some basic statistical knowledge.

Course format

The course is designed to include extensive practical analysis exercises and all participants will need access in the classroom to a laptop / computer with Minitab installed.

This twelve-day Lean Six Sigma Transactional Green Belt training programme is delivered in three modules of four days each (typically with a month between modules) to allow participants to apply what they have learned to a project within their own business while under the guidance of one of our highly experienced Master Black Belts. A certificate of attendance is awarded upon successful completion of the course.

Given the practical nature of this workshop-style programme, there is a maximum limit of twelve participants (minimum four).

Special features

It is strongly recommended that participants come to the start of the programme with either a well-defined project or a number of project ideas. The project can then be used as a learning and application vehicle. During the training there will be opportunities between the modules for the participants to be mentored and coached by the Master Black Belt.

This programme is very practical and is based on all participants having a laptop or PC in the training room with Minitab installed. Minitab is the leading statistical software package used for quality improvement worldwide. If the course participants do not already have experience of using Minitab then they should attend an Introduction to Minitab first.

Lean Six Sigma Operational Green Belt – programme outline

MODULE ONE

Learner outcomes

Participants will be able to:

  • Explain the history and philosophy of Lean and Six Sigma
  • Use some of the main graphical and analytical functions within Minitab software
  • Explain the 5 main stages of a Lean Six Sigma project
  • Apply and explain basic statistical concepts such as types of data, sampling, distribution shapes and characteristics, and statistical inference
  • Select suitable Lean Six Sigma project activity within their company processes
  • Define and scope a project
  • Form a suitable project team
  • Identify Stakeholders who can influence the outcome of their project activity, and generate strategies to deal with them
  • Capture and structure customer requirements
  • Identify appropriate measures that will determine if customer requirements have been met
  • Study and measure existing processes, and apply fundamental Lean concepts such as Takt Time, Cell Design, Line Balancing, Kanban and OEE
  • Study and measure existing processes, and apply fundamental Lean concepts such as Takt Time, Cell Design, Line Balancing, Kanban and OEE

Module outline

DAY ONE

1 Introductions / expectations / agenda

2 An introduction to Lean Six Sigma

  • Understand the history of and relationship between Lean, Six Sigma and problem-solving

3 Problem-solving and the seven basic tools

  • 8D process
    • – Step 1: Define the problem
    • – Step 2: Interim action
    • – Basic tools for steps 1 and 2
  • Workshop 1: Complete steps 1 and 2 on the case study
  • Workshop feedback and discussion
    • – Step 3: Acquire and Analyse Data
    • – Step 4: Determine Root Cause
    • – Basic tools for steps 3 and 4
  • Workshop 2: Complete steps 3 and 4 on the case study
  • Workshop feedback and discussion

 

DAY TWO

1 Review of Day One

2 Problem-solving and the seven basic tools (continued)

  • 8D process
    • – Step 5: Evaluate possible solutions
    • – Step 6: Action plan and implement
    • – Basic tools for steps 5 and 6
  • Workshop 3: Complete steps 5 and 6 on the case study
  • Workshop feedback and discussion
    • – Step 7: Checklist
    • – Step 8: Standardise for future
    • – Basic tools for steps 7 and 8
  • Workshop 4: Complete steps 7 and 4 8 on the case study
  • Workshop feedback and discussion
  • General discussion on the 8D approach and the Case Study to examine applications in the participants’ business

3 DMAIC

  • An introduction to the phases of a Lean Six Sigma project
  • Participants will link to own processes and provide examples

 

DAY THREE

1 Review of Day Two

2 Understanding variable data

  • The ways that statistics can be used to describe data and draw information out of it
  • Why we use statistics
  • Types of data

3 Introduction to Minitab

  • Understanding the software
    • – Using Minitab graphical function
    • – First pass analysis
    • – Graphical analysis
  • Measures of location
    • – Mean, median, mode
  • Measures of dispersion
    • − Range, variance and standard deviation
  • Descriptive statistics
    • − Normal distribution
    • − Sigma value
    • − Non-normal data
  • Exercise – Dice game

4 DMAIC – the Define phase of the DMAIC roadmap

  • Techniques for selecting and defining projects
  • Exercise – Dashboard workshop part 1
  • Hands-on learning about performance of poorly organised processes, and opportunity later to apply simple Lean tools to improve the process performance

 

DAY FOUR

1 Review of Day Three

2 Teams

  • Understand the requirements for team formation
  • Exercise – Presidents of the USA
  • Exercise – Produce an Agenda for the Team ‘Kick Off’ meeting

3 Projects

  • Understand the project ‘quad of aims’
  • Understand what makes good Problem Goals and Statements
  • Exercise – Produce a Problem and Goal Statement for your project

4 Stakeholder analysis

  • Understand the importance of stakeholder analysis within a project environment
  • Exercise – Dashboard workshop, part 2
  • Review commonly used approaches to workplace layout and work organisation
  • Discuss and apply options for improvements which can be implemented in the game
  • Run the workshop and measure improvements

5 Identifying customer requirements

  • Ensure that participants understand the importance of understanding customer requirements before anything is designed or changed
  • Introduction to the Kano model
  • Critical-to-quality (CTQ) and affinity trees
  • Introduction to quality function deployment (QFD)

6 Summary

  • Review
  • Expectations for Module Two
  • Q and A

There is now a break of four weeks in which the participants will progress their projects. E-mail support is available from the Master Black Belt during this period if required.

 
MODULE TWO

Learner outcomes
Participants will be able to:

  • Use appropriate measures and metrics to characterise processes and drill down to variable data
  • Formulate null and alternate hypotheses and carry out appropriate hypothesis tests on their data
  • Carry out a measurement systems analysis and make appropriate decisions about any improvement needed
  • Use control charts to decide if a process is performing in a stable way
  • Use a capability study to establish the ability of a process to meet specification requirements
  • Use value stream and other process mapping techniques to increase process knowledge and identify potential sources of process performance problems
  • Use cause/effect and / or fault tree analysis to establish true root cause(s) and / or potential sources of unwanted variation in process performance
  • Use correlation and regression to identify potential process inputs (Xs) and quantify the nature of the relationship(s) in the search for sources of variation
  • Use multi-vari analysis as a simple graphical tool in the search for sources of variation

Module outline
DAY ONE

1 Introductions / expectations / agenda

  • Review Module One
  • Agenda for Module Two
  • DMAIC – the Measure phase of the DMAIC roadmap

2 Data collection

  • Ways of thinking about the right things to measure on a process
  • Using variable data
  • Data drill down
  • Exercise – examples from their own businesses or projects to develop on the flipchart

3 Measurement system analysis

  • Introducing the concept of measurement system analysis
  • Understanding analysis of variance (ANOVA)
  • Gauge R&R (repeatability and reproducibility)
  • Exercise – gauge R&R workshop
  • Attribute R&R
  • Exercise – attribute R&R workshop

4 Control charts

  • Introduction
  • Use and application
  • Theory of control limits
  • Xbar and R charts
  • Individual and moving range (I-MR) charts
  • Exercise – data mining

 
DAY TWO

1 Review of Day One

2 Process capability

  • Introduction
  • Stable and unstable processes
  • Cp and Cpk
  • Linking to Six Sigma
  • Exercise – assessing process capability
  • Pp and Ppk
  • Exercise – capability workshop
  • How to deal with non-normal data

3 How to deal with non-normal data

4 SIPOC

  • Produce a SIPOC for the projects

5 Process mapping

6 Value stream mapping

  • Future state mapping
  • Exercise – Mapping using participants’ projects

7 Root cause analysis

8 Cause and effect

9 Negative brainstorming

10 Fault tree analysis

  • Exercise – Fault tree workshop

 
DAY THREE

1 Review of Day Two

2 Correlation and regression

  • Introduction
  • A tool for identifying significant Xs or input variables on a process from a list of potential ones
  • Pearson correlation coefficient
  • Linear regression
  • Understanding residuals
  • R-squared distribution
  • Exercise – creating a linear regression model using Minitab
  • Polynomial regression
  • Exercise – creating a polynomial regression model using Minitab
  • Applying regression in your own project

3 Multi-Vari analysis

  • An alternative approach to finding significant Xs in the Analyse phase
  • Crossed and nested designs
  • Exercise

 
DAY FOUR

1 Review of Day Three

2 Hypothesis testing

  • Why hypothesis tests?
  • The most common statistical tests that participants will need in running projects
  • Alpha and Beta risks
  • Using Minitab to analyse the tests
  • Exercise – hypothesis testing case studies
  • Tests for variable data
    • − Sample T tests
    • − Analysis of variance
    • − Exercise – applying tests
  • Tests for attribute data
    • − Proportion tests
    • − Chi squared tests
    • Exercise – applying tests
  • Discussion on application of tests

There is now a break of four weeks in which the participants will progress their projects. E-mail support is available from the Master Black Belt during this period if required.

 

MODULE THREE

Learner outcomes

Participants will be able to:

  • Design and run a simple full factorial experiment
  • Design and run a fractional factorial screening experiment
  • Analyse the results from designed experiments and draw conclusions about significant and not significant relationships
  • Identify potential process or product improvement strategies based on the results of their investigations and identification of critical Xs
  • Create and select the most likely successful solutions to the process issues in their project
  • Identify and implement opportunities for better workplace organisation and the use of visual management techniques
  • Identify and implement opportunities for rapid changeover techniques where equipment needs to be re-configured for different activities
  • Identify and implement opportunities for mistake-proofing in their business processes
  • Verify improved performance by implementing a pilot run and analysing stability and capability
  • Sustain improved process performance by using appropriate control techniques such as control charts and mistake-proofing, and incorporating them into a control plan

Module outline

DAY ONE

1 Introductions / expectations / agenda

  • Review Module Two
  • Agenda for Module 3
  • DMAIC – the Analyse phase of the DMAIC roadmap

2 Design of experiments

  • Concepts and theoretical basis of designed experiments
  • Exercise – cooking workshop 1
  • Exercise – cooking workshop 2
  • Full factorial experiments
  • Exercise – moulding experiment
  • Design of experiments in Minitab
  • Exercise – design of experiments gyrocopter workshop

 
DAY TWO

1 Review of Day One

2 Design of experiments (cont)

  • Exercise – design of experiments gyrocopter workshop
  • Fractional factorial experiments
  • Screening experiments
  • Noise factors
  • Exercise
  • Interpreting results

3 DMAIC – the Improve phase of the DMAIC roadmap

  • Trials and pilots

4 Project presentations

  • Participants present a short report on their project so far and seek guidance for future actions

 
DAY THREE

1 Review of Day Two

2 Generate and select solutions

  • TRIZ
  • Pugh Matrix

3 Effective workplace organisation

  • Visual management
  • 5S
  • Kanban

4 Mistake-proofing

  • Introduction
  • Principles of mistake-proofing
  • Types of mistake-proofing
  • Exercise – Identifying effective mistake-proofing

h3>5 FMEA

  • Determining potential failures
  • Identifying effect of failure
  • Analysing risk priority number
  • Determining corrective action
  • Exercise – Applying to projects

 
DAY FOUR

1 Review of Day Three

2 The Control phase of the DMAIC roadmap

  • Tools and techniques
  • Developing a control plan
  • Developing a communication plan

3 DMAIC workshop – the whole story

  • Case study following the DMAIC process, using a transactional / service example

4 Conclusion

  • A review of the whole programme
  • Expectations and requirements for achieving Certified Green Belt status, including passing an exam and presenting projects
  • Where next?

Participants will continue to progress their projects after the end of the programme. E-mail support will still be available from the Master Black Belt.