CSSGB Certification Curriculum Outline
Six Sigma and Lean in the Organization
Overview/Description
Six Sigma is a highly disciplined, data-driven improvement program that helps companies focus on eliminating defects in any process and delivering near-perfect products and services. Six Sigma has been globally accepted as a profitable and winning business strategy. More and more companies are embracing Six Sigma in a time when competition and sluggish markets have left operational efficiency and quality improvement as the only way to protect margins and win customer loyalty. Originally developed in Toyotas manufacturing operations, Lean is a continuous improvement approach that focuses activities on reducing wastes. Whereas Six Sigma helps companies reduce defects and improve quality, Lean thinking helps reduce waste and improve process flow and speed. Due to the complementary nature of the Lean approach, many organizations incorporate it into their overall Six Sigma strategy. This course will examine how Six Sigma and Lean help organizations achieve their strategic goals and why so many successful organizations attribute their success to them. The course first introduces the key concepts and contributors associated with Six Sigma, and then moves on to basic Lean tools used to identify and remove waste and improve process flow. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.5
Lesson Objectives
Six Sigma and Lean in the Organization
Course Number:
oper_05_a01_bs_enus
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Design for Six Sigma in the Organization
Overview/Description
Design for Six Sigma (DFSS) is often called the future of Six Sigma, as it is emerging as a strategy that better serves the current innovation initiatives of many industries. DFSS uses a pay me now or pay me later approach by spending more effort and time on process or product design up front to avoid spending time and effort in those areas later. Whereas Six Sigma just focuses on improving existing designs at a later stage, DFSS focuses on creating new and better products and processes from scratch. It designs virtually error-free products and services from the very beginning and, due to its complementary methodology and amazing results, it is now adopted as a key strategy in Six Sigma implementations. This course will examine how Six Sigma combines DFSS methodologies and tools to reach organizational goals. It distinguishes DFSS methodologies from those of Six Sigma, and outlines some of the key DFSS tools such as quality function deployment (QFD) and Failure Modes and Effects Analysis (FMEA). This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and Champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.0
Lesson Objectives
Design for Six Sigma in the Organization
Course Number:
oper_05_a02_bs_enus
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Processes and Customer Analysis in Six Sigma Projects
Overview/Description
A process is a means of creating and delivering products and services needed by customers. According to Takashi Osada, Japanese author and quality pioneer, if the process is right, the results will take care of themselves. By Six Sigma standards, a right process is one that creates and delivers precisely what the customer needs. By this logic, no Six Sigma effort can start without having a high-level picture of an organizations customers and other stakeholders, their needs, and the business processes meant to fulfill those needs. A thorough analysis of the existing business processes - and the products and services they churn out - is the first step in Six Sigma projects. You need to listen to the voice of the customer to find out what customers need, identify opportunities for change and improvement, and translate customer needs into goals and customer deliverables. In this course, learners will examine how to analyze process components and stakeholders in an organization. They will also learn about concepts and tools for collecting and analyzing customer information and feedback. The course also explains how customer requirements are translated into goals and deliverables using such tools as Kano analysis, CTQ analysis, and the House of Quality matrix. The course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.5
Lesson Objectives
Processes and Customer Analysis in Six Sigma Projects
Course Number:
oper_06_a01_bs_enus
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Basics of Six Sigma Projects and Teams
Overview/Description
Effective leadership is putting first things first. Effective management is discipline, carrying it out, says famous motivator and author, Stephen R. Covey. Six Sigma needs both effective leadership and management to deliver its promised results to an organization. It requires all Six Sigma leaders – Master Black Belts, Black Belts, and Green Belts – to effectively lead project teams to deliver their expected results. Understanding team building processes, tools, and role structures helps Six Sigma team members produce desired results and resolve negative team dynamics. In order to achieve this, disciplined schedules, costs, and deliverables are required when managing such projects. The management of Six Sigma projects involves developing and adhering to a project charter that reflects a shared understanding of project expectations, scope, deliverables, and schedule. This course will examine the fundamental project management tools used in a successful Six Sigma project. The course introduces the essential elements of a project charter, explains how project scope and metrics are developed, and gives an insight into the tools used to plan and implement improvement in a Six Sigma initiative. It also looks at team building, team roles, and team dynamics, and examines a variety of team tools that are commonly used in Six Sigma. Along with that, it identifies the most common communication techniques used in the workplace and the situations they are best suited to. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.5
Lesson Objectives
Basics of Six Sigma Projects and Teams
Course Number:
oper_06_a02_bs_enus
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Tools for Planning and Managing Six Sigma Project Opportunities
Overview/Description
In many situations your results are only as good as the tools you use. Knowing which tools to use, and how to apply them effectively, is the key to any endeavors success. This assertion holds true for process and quality improvement strategies, and Six Sigma and quality improvement teams throughout the world use a set of management and planning tools to analyze and understand a variety of issues. This course will examine the tools used in Six Sigma to help organizations make decisions and plan and communicate findings. These tools include affinity diagrams, interrelationship digraphs, tree diagrams, prioritization matrices, matrix diagrams, process decision program charts, and activity network diagrams. The course describes these tools, identifies their benefits, and uses real-life examples to show the situations that they are best suited to. It also outlines the steps for using each tool in a Six Sigma context. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.5
Lesson Objectives
Tools for Planning and Managing Six Sigma Project Opportunities
Course Number:
oper_06_a03_bs_enus
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Using Six Sigma Analysis Tools and Metrics for Project Decisions
Overview/Description
Six Sigma is a business improvement methodology that begins by comparing the current state of a companys products and processes to their desired levels. The goal of the Define phase in the Six Sigma DMAIC methodology is to identify improvement opportunities that have the maximum potential for return on time, money, and resource investments. Knowing what projects to select for improvement requires an assessment and analysis of existing business processes. For a precise, objective, and accurate assessment of the existing processes, you need to have correct metrics and knowledge of where and how to use them. Later in a Six Sigma project, during the Control phase, the overall performance of business processes is recalculated to identify process improvement. This course will examine how and when to use the metrics and tools to select Six Sigma projects. The course explores some of the number-driven metrics, such as defects per unit (DPU), rolled throughput yield (RTY), defects per million opportunities (DPMO), and process capability indices. It also explains cost of poor quality (COPQ) as a metric used to assess and indirectly present the potential gains to the company if the quality of products and processes is improved. In addition, the course explores how failure modes and effects analysis (FMEA) is used to identify improvement opportunities that have the highest priority for Six Sigma teams. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Using Six Sigma Analysis Tools and Metrics for Project Decisions
Course Number:
oper_06_a04_bs_enus
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Modeling and Analyzing Processes in Six Sigma
Overview/Description
If you cant describe what you are doing as a process, you dont know what you are doing, says W. Edwards Deming, a well-known American quality advocate, statistician, and educator. During the Measure stage of the Six Sigma methodology, you need to identify and map processes and procedures for problem areas identified during the Define stage, and present them to the Six Sigma team for a closer look. As you start uncovering and analyzing these processes, the likely causes of problems become clearer. This course will examine the tools and techniques used to model and analyze existing processes. From a process modeling perspective, the course looks at techniques such as process mapping, written procedures, and work instructions. From a process analysis point of view, the course examines the use of SIPOC analysis to identify process input and output variables, and explores how cause-and-effect diagrams and relational matrices are used to establish relationships between problems and potential causes. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and Champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.0
Lesson Objectives
Modeling and Analyzing Processes in Six Sigma
Course Number:
oper_07_a01_bs_enus
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Statistics and Probability in Six Sigma
Overview/Description
Six Sigma bases its analysis and findings on the facts and figures at hand. Statistical studies and probability are the key tools that Six Sigma teams use to measure and analyze issues that are identified in the early stages of Six Sigma projects. This course explores basic statistical concepts that apply to Six Sigma. It distinguishes between enumerative and analytical statistics and population and sample characteristics, and describes the Central Limit Theorem. It also examines basic probability concepts and looks at dependent, independent, and mutually exclusive events, and multiplication and addition rules. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.0
Lesson Objectives
Statistics and Probability in Six Sigma
Course Number:
oper_07_a02_bs_enus
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Data Classification and Collection in Six Sigma
Overview/Description
Measure what is measurable, and make measurable what is not so said Galileo Galilei, the famous Italian physicist, mathematician, astronomer, and philosopher. Measuring the key characteristics in your current processes is a very significant step in any Six Sigma improvement journey. As such, sample data from existing processes needs to be identified, collected, presented, and analyzed. Collecting data that is correct and useful is one of the first steps in the measurement process. Various types of data exist, and they all need appropriate treatment during the collection, presentation, and analysis stages. You also need to be careful when applying sampling techniques to ensure data accuracy and integrity. This course will explore continuous and discrete types of data, and nominal, ordinal, interval, and ratio measurement scales. It will also introduce methods for data collection, such as check sheets and coded data, and deals with the issue of data accuracy and integrity, focusing particularly on sampling techniques such as random sampling and stratified sampling. The course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Data Classification and Collection in Six Sigma
Course Number:
oper_07_a03_bs_enus
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Summarizing and Presenting Data in Six Sigma
Overview/Description
Six Sigma teams use measures of central tendency and dispersion to reveal key facts about process data and the existing processes. They summarize data and put forth the relationships between various data components for further analysis. The teams then present these relationships in easy-to-understand graphical forms that facilitate comparison and help to identify possible trends. This course deals with the basic concepts of descriptive statistics, such as measures of central tendency and dispersion, and their significance in Six Sigma data analysis. The course also shows how to apply graphical methods, such as stem-and-leaf plots, box-and-whisker plots, run charts, and scatter diagrams, for illustrating relationships among various components of a given dataset. In addition, it examines how to depict distributions using histogram and normal probability plots. The course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Summarizing and Presenting Data in Six Sigma
Course Number:
oper_07_a04_bs_enus
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Probability Distributions and Measurement Systems Analysis in Six Sigma
Overview/Description
Probability distributions are an essential part of descriptive statistics that Six Sigma teams can use to assist in fitting collected data into various types of distributions. Probability distributions help to ascertain specific probability values in the distribution and lead the Six Sigma teams down the hypothesis testing roadmap to the next stage of the Six Sigma DMAIC process. Of course, all this is meaningless if the data you have gathered and used is not accurate or precise, which is where measurement systems analysis (MSA) comes into play. MSA is a task in the Measure stage of the Six Sigma DMAIC process and is used to identify the variability caused by the measurement system itself. This course will examine how to calculate normal, binomial, Poisson, chi-square, Students t-distributions, and F distributions. It will also look at how to assess the precision and accuracy of an organizations current measurement system using Gauge Repeatability and Reproducibility (GR&R), bias, linearity, percent agreement, and Precision/tolerance (P/T) studies. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.0
Lesson Objectives
Probability Distributions and Measurement Systems Analysis in Six Sigma
Course Number:
oper_07_a05_bs_enus
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Measuring Process Capability and Performance in Six Sigma
Overview/Description
Businesses exist to meet the needs of the customers they serve. As such, you must listen to the voice of your customers and build processes that deliver products and services to them. It is also necessary to review processes to ensure they remain within the targets and specifications set by your customers. Measuring the capability and performance of a process is an important activity in Six Sigma DMAIC methodology. Six Sigma teams use process capability and performance measurements, such as process capability (Cp), process capability index (Cpk), process performance (Pp), and process performance index (Ppk), to indicate the current state of a process and its sigma levels. This course will examine the key concepts of process capability and performance, and the methods of measuring and interpreting them in a process capability study. It covers the calculation and interpretation of process capability and performance measurements. It also identifies key considerations for measuring process capability, such as short-term and long-term capability and process capability for discrete data. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.0
Lesson Objectives
Measuring Process Capability and Performance in Six Sigma
Course Number:
oper_07_a06_bs_enus
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Exploratory Data Analysis in Six Sigma
Overview/Description
In the Analyze stage of the Six Sigma DMAIC process, you closely examine the output variable (known as y) and its possible causes or input variables (known as xs) collected in the Measure stage to get a deeper understanding of their relationships. The goal of this analysis is to narrow down the many possible xs identified earlier during the Measure stage, to a few probable ones. This analysis is generally conducted through the use of two important toolsets: exploratory data analysis and hypothesis testing. Methods and tools used in these broad toolsets help to identify a few probable root causes impacting process performance and the Six Sigma project goal. This course introduces some key exploratory data analysis tools used in Six Sigma such as multi-vari studies, correlation, and regression models. The course takes you through the multi-vari analysis to identify positional, cyclical, and temporal variations and how to apply an effective sampling plan for conducting this analysis. It also explains the correlation coefficient, its statistical significance, and how it is different from causation. In addition, the course helps you interpret the linear regression equation and explores how you can use it to model relationships for prediction and estimation of data. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Exploratory Data Analysis in Six Sigma
Course Number:
oper_08_a01_bs_enus
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Introduction to Hypothesis Testing and Testing for Means in Six Sigma
Overview/Description
The Analyze phase in Six Sigma closely examines the many process inputs identified in the Measure phase to determine if they are related to outputs, and if a relationship does exist, if it is statistically significant. An important tool for this analysis is hypothesis testing. Hypothesis testing uses statistical analysis to determine if the observed relationship between two or more samples is real or due to random chance. A variety of tests are used to find statistical evidence to reject or not to reject a hypothesis. Once this is accomplished, the Six Sigma team is ready to move forward with identifying, testing, and implementing solutions to address the root causes of failure. This course covers the key hypothesis testing concepts and the tests used in Six Sigma. The course will explore the steps for testing hypotheses for one-sample t-tests and two-sample t-tests with the help of real-life examples and case studies. The key terms and the common procedures used to test hypotheses are also introduced. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.0
Lesson Objectives
Introduction to Hypothesis Testing and Testing for Means in Six Sigma
Course Number:
oper_08_a02_bs_enus
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Hypothesis Tests for Variances, Proportions, ANOVA, and Chi-Square in Six Sigma
Overview/Description
The hypothesis test is one of the most important tools used in the Analyze stage of the Six Sigma DMAIC methodology. A hypothesis test helps to determine whether or not an observed relationship or difference truly exists between inputs and outputs identified in the earlier stages of the process. Six Sigma teams are interested in determining whether this relationship or difference is due to random chance or if it is a true difference. If it is a real difference, Six Sigma teams like to determine if it has practical significance. The goal of this course is to explore several of the hypothesis tests used in Six Sigma. The course covers the key steps for testing hypotheses for proportions, variances, and paired comparisons with the help of real-life examples and case studies. It also covers how to use single-factor analysis of variance (ANOVA) and how to test hypotheses using a chi-square test. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Hypothesis Tests for Variances, Proportions, ANOVA, and Chi-Square in Six Sigma
Course Number:
oper_08_a03_bs_enus
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Design of Experiments and Validation of Solutions in Six Sigma
Overview/Description
We are, I think, in the right road of improvement, for we are making experiments, said Benjamin Franklin. In the Improve stage of the DMAIC process, Six Sigma teams design and conduct experiments to study the nature of relationships between input variables and the response variable(s). They do this by controlling and changing the input variables and observing the effects on the response variable(s). After determining what and how much needs to be changed to meet the desired improvement, teams generate solution ideas to optimize the response, and then the ideas are tested, implemented, and validated. Later in the control stage, efforts are made to keep the improved processes, products, or services under statistical control and to retain the gains. This course explains the basic design of experiments (DOE) concepts and outlines how to select, test, and validate improvement solutions in the final stages of a Six Sigma project. During the course, basic DOE concepts such as factors, levels, interactions, and main effects are introduced. The course also explores the full and fractional factorial designs and the DOE process. In addition, it teaches how to select, test, and validate solutions using a variety of analysis, screening, and testing tools commonly used in Six Sigma. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Design of Experiments and Validation of Solutions in Six Sigma
Course Number:
oper_09_a01_bs_enus
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Statistical Process Control and Control Plans in Six Sigma
Overview/Description
In the final stages of the Six Sigma DMAIC methodology, once process improvement opportunities are identified and implemented, you need to make sure that the improved processes are controlled to sustain the process improvement gains. Statistical process control (SPC) provides tools which can be used to ensure that the processes are continuously monitored, that results are evaluated through the use of various control charts, and that each process is prevented from reverting to its previous state. The goal of this stage is also to develop a control plan to document and hold the gains, and to assist in monitoring and implementing controls. This course aims to introduce basic SPC and control chart concepts and how to develop a control plan to hold the gains prior to the closure of a Six Sigma project. The course identifies the key objectives and benefits of SPC and explains the concept of rational subgrouping. It also introduces the different types and the key elements of control charts, and identifies control chart patterns that indicate an out-of-control process. In addition, the types of control plans and the steps used to construct a control plan are discussed. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
1.5
Lesson Objectives
Statistical Process Control and Control Plans in Six Sigma
Course Number:
oper_09_a02_bs_enus
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Using Basic Control Charts in Six Sigma
Overview/Description
In a Six Sigma DMAIC project, once youve measured your current processes, analyzed the gaps and causes of problems, and improved processes to the desired level, you need to monitor and control them over an extended period of time. The process may show variation, and control charts are used to determine if the variation is natural to the process or if there is another reason for the discrepancy. Control charts can also be used in other stages of Six Sigma – to examine how a process is performing over time and also to identify and analyze any special cause variations. Depending on the type of data, different types of control charts can be used. They are broadly organized into two categories: charts for variable data, and charts for attribute data. As the journey continues, findings from the control charts may be used as the beginning point for a new improvement initiative. This course deals primarily with basic control chart concepts and how they are created and analyzed in Six Sigma. It teaches methods of creating and analyzing key variable and attribute control charts. The course also identifies the control charts to use in specific situations and the various steps in the standard control charting process. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level
Expected Duration (hours)
2.5
Lesson Objectives
Using Basic Control Charts in Six Sigma
Course Number:
oper_09_a03_bs_enus
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1yr license: $187.00 per course
*Contact a Training Advisor for Discounted Student and Corporate pricing*
*Contact a Training Advisor for Discounted Student and Corporate pricing*
Six Sigma Training - CSSGB Certification
(Certified Six Sigma Green Belt)
Six Sigma® Green Belt professionals focus on analyzing and solving quality problems, driving quality improvements and supporting
those who have Six Sigma Black Belt certifications. To obtain the Six Sigma Green Belt, individuals must possess proficient team
building and project management skills in order to successfully execute Six Sigma projects. To qualify for the Six Sigma Green Belt,
professionals need to participate in a comprehensive Six Sigma Green Belt training program.
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CBT Direct’s Six Sigma Green Belt training introduces the foundations of Six Sigma and concept of Lean, a continuous improvement approach that focuses activities on reducing wastes. It examines how Six Sigma and Lean help organizations achieve their strategic goals and why so many successful organizations attribute their success to them.
Six Sigma Green Belt candidates will learn that successful management of Six Sigma projects involves developing and adhering to a project charter that reflects a shared understanding of project expectations, scope, deliverables, and schedule. Our Six Sigma Green Belt training introduces the essential elements of a project charter, explains how project scope and metrics are developed, and gives insight into the tools used to plan and implement improvement in a Six Sigma initiative.
Our Six Sigma Green Belt training program teaches Six Sigma Green Belt certification candidates how to translate customer requirements into goals and deliverables using such tools as Kano analysis, CTQ analysis, and the House of Quality matrix.
Six Sigma Green Belt certification professionals must also possess strong team building skills. With our Six Sigma Green Belt training program, they will learn the processes, tools and role structures of Six Sigma teams to produced desired results and resolve negative team dynamics. Click here to see a detailed curriculum outline.
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Exam#
Certification
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Hours
Hours
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| CSSGB | Six Sigma CSSGB (Certified Six Sigma Green Belt) Certification | ü | ü |
Six Sigma Green Belt Prerequisites
Required Experience
The Six Sigma Green Belt requires three years of work experience in one or more areas of the Six Sigma Green Belt Body of Knowledge
Click Here for Six Sigma Green Belt Facts.
Six Sigma Training - CSSGB Certification
