Lean Six Sigma Green Belt Certification Exam Training Course in Riyadh, Saudi Arabia

1.0 Introduction: Overview of Six Sigma (5 Marks)
1.1 Value of Six Sigma
Recognize why organizations use Six Sigma and understand the origins of Six Sigma.

1.2 Organizational Drivers and Metrics
Recognize key drivers for business (profit, market share, customer satisfaction,
efficiency, product differentiation) and how key metrics and scorecards are
developed and impact the entire organization.

2.0 Six Sigma—Define (15 Marks)

2.1 Process Elements
Define and describe SIPOC

2.2 Owners and Stakeholders
Identify process owners, internal and external customers, and other stakeholders
in a project.

2.3 Identify Customers and Customer Segmentation

Identify and classify internal and external customers as applicable to a particular
project, and show how projects impact customers.

2.4 Collect and Classify Customer Data

VOC, Survey Methods, Kano Analysis.

2.5 Translate Customer Requirements

Translate customer feedback into project goals and objectives, including critical to
quality (CTQ) attributes and requirements statements. Use of Quality Function
Deployment (QFD) to translate customer requirements into performance measures.

2.6 Project Identification and Planning Tools

Define, select, and use: 1) Affinity Diagrams 2) Interrelationship Digraphs 3) Tree
Diagrams 4) Prioritization Matrices 5) Matrix Diagrams 6) Process Decision
Program (PDPC) Charts 7) Activity Network Diagrams – Gnatt Charts, PERT and CPM.

2.7 Organizational Goals and Six Sigma Projects

Describe the project selection process including knowing when to use Six Sigma
DMAIC methodology.

2.8 Project Charter and Project Metrics

Define and describe elements of a Project Charter. Development of metrics –
COQ, DPU, DPMO, RTY.

2.9 Team Stages and DMAIC

Define and describe the stages of team evolution, including forming, storming,
norming, performing, adjourning, and connectivity with DMAIC.

2.10 Six Sigma - Team Roles and Responsibilities

Describe and define the roles and responsibilities of participants on Six Sigma
teams, including black belt, master black belt, green belt, champion, executive,
coach, facilitator, team member, sponsor, process owner, etc.

3.0 Lean Principles in the Organization (5 Questions)

4.0 Six Sigma—Measure (20 Questions)

4.1 Process Mapping

Develop and review process maps, flowcharts, etc.

4.2 Process Inputs and Outputs

Identify process input variables and process output variables (SIPOC), classify as
CTQs and CTPs including Control & Noise CTPs.

4.3 Probability and Statistics

Distinguish between enumerative (descriptive) and analytical (inferential) studies, and
distinguish between a population parameter and a sample statistic.

4.4 Basic Probability Concepts

Describe and apply concepts such as independence, mutually exclusive,
multiplication rules, etc.

4.5 Types of Data and Measurement Scales

Identify and classify continuous (variables) and discrete (attributes) data. Describe
and define nominal, ordinal, interval, and ratio measurement scales.

4.6 Data Collection Methods

Define and apply methods for collecting data such as check sheets, stratification,
coded data, etc.
4.7 Techniques for Assuring Data Accuracy and Integrity

Define and apply techniques such as random sampling, stratified sampling, sample
homogeneity, etc.

4.8 Descriptive Statistics

Define, compute, and interpret measures of dispersion and central tendency, and
construct and interpret frequency distributions and cumulative frequency distributions.

4.9 Graphical Methods

Depict relationships by constructing, applying and interpreting diagrams and charts
such as stem-and-leaf plots, box-and-whisker plots, run charts, scatter diagrams,
Pareto charts, etc. Depict distributions by constructing diagrams such as histograms,
normal probability plots, etc.

4.10 Probability Distributions

Describe and interpret binomial, and Poisson, normal, chi square, Student’s t, and F
distributions.

4.11 Central Limit Theorem and Sampling Distribution of the Mean

Define the central limit theorem and describe its significance in the application of
inferential statistics for confidence intervals, control charts, etc.

4.12 Measurement System Analysis

Calculate, analyze, and interpret measurement system capability using repeatability
and reproducibility (GR&R), measurement correlation, bias, linearity, percent
agreement, and precision/tolerance (P/T)

5.0 Six Sigma—Analyze (10 Marks )

5.1 Cause Analysis
Root cause analysis, cause and effects analysis.

5.2 Failure Mode and Effects Analysis (FMEA)

Define and describe failure mode and effects analysis (FMEA). Describe the purpose
and use of the risk priority number (RPN).

5.3 Run Charts

Plotting sequential data and analyze for normality, trends, patterns.
5.4 Multi-Vari Studies

Create and interpret multi-vari studies to interpret the difference between positional,
cyclical, and temporal variation; apply sampling plans to investigate the largest
sources of variation.

5.5 Simple Linear Correlation and Regression

Interpret the coefficients of co-relation & determination – r & R2 and determine;
recognize the difference between correlation and causation. Interpret the linear
regression equation and determine its statistical significance. Use regression models
of Six Sigma.

6.0 Six Sigma—Improve and Control (20 marks)

6.1 Process Capability and Performance

Identify, describe, and apply the elements of designing and conducting process capability studies, including identifying characteristics, identifying specifications and tolerances,developing sampling plans, and verifying stability and normality.

6.2 Process Performance vs. Specification

Distinguish between natural process limits and specification limits, and calculate process performance metrics such as percent defective.

6.3 Process Capability Indices

Define and calculate Cp and Cpk, and assess process capability.

6.4 Process Performance Indices

Define and calculate Pp, Ppk, and assess process performance.

6.5 Short-Term vs. Long-Term Capability

Describe the assumptions and conventions that are appropriate when only short-term
data is collected and when only attributes data are available. Describe the changes in
relationships that occur when long-term data is used, and interpret the relationship
between long- and short-term capabilities as it relates to a 1.5 sigma shift.

6.6 Process Capability for Attributes Data

Compute the Sigma level for a process and describe its relationship to Ppk.

6.7 Statistical Process Control (SPC)
Define and describe how rational sub-grouping is used. Describe the objectives and
benefits of SPC, including controlling process performance, identifying special and
common causes, etc.

6.8 Selection and Application of Control Charts

Identify, select, construct, and apply the following types of control charts: X-bar −R,
Xbar−s, individuals and moving range (I-mR / X-mR), pre-Control chart, median and
moving range, p, np, c, and u.

6.7 Analysis of Control Charts

Interpret control charts and distinguish between common and special causes using rules for determining statistical control.

6.8 Control Plans, SOPs, Work Instructions

Developing these documents and assisting in implementing controls and monitoring
systems.