Six Sigma Part 2: Analyze, Improve, Control from edX

Building on the concepts from the first course in the Six Sigma Program, Define and Measure, in this course, you will learn how to statistically analyze data with the Six Sigma methodology using inferential statistical techniques to determine confidence intervals and to test hypotheses based on sample data. You will also review cause and effect techniques for root cause analysis.

You will learn how to perform correlation and regression analyses in order to confirm the root cause and understand how to improve your process and plan designed experiments.

You will learn how to implement statistical process control using control charts and quality management tools, including the 8 Disciplines and the 5 Whys to reduce risk and manage process deviations.

To complement the lectures, learners are provided with interactive exercises, which allow learners to see the statistics "in action." Learners then master statistical concepts by completing practice problems. These are then reinforced using interactive case studies, which illustrate the application of the statistics in quality improvement situations.

Upon successful completion of this program, learners will earn the TUM Lean and Six Sigma Yellow Belt certification, confirming mastery of Lean Six Sigma fundamentals to a Green Belt level. The material is based on the American Society for Quality (www.asq.org) Body of Knowledge up to a Green Belt Level. The Professional Certificate is designed as preparation for a Lean Six Sigma Green Belt exam.

What you'll learn

To identify process problems and perform a root cause analysis using cause and effect diagrams and regression analysis.
To analyze data using inferential statistical techniques, including confidence intervals and hypothesis testing.
To test and quantitatively assess the impact of different improvement options using the design of an experiment.
To test for the significance of effects using an Analysis of Variance.
To implement control mechanisms for long-term monitoring using control charts for both quantitative and qualitative measurements.
To apply the Six Sigma methodology for the Analyze, Improve and Control phases in your work or research.

What's inside

Learning objectives

To identify process problems and perform a root cause analysis using cause and effect diagrams and regression analysis.
To analyze data using inferential statistical techniques, including confidence intervals and hypothesis testing.
To test and quantitatively assess the impact of different improvement options using the design of an experiment.

To test for the significance of effects using an analysis of variance.
To implement control mechanisms for long-term monitoring using control charts for both quantitative and qualitative measurements.
To apply the six sigma methodology for the analyze, improve and control phases in your work or research.

To identify process problems and perform a root cause analysis using cause and effect diagrams and regression analysis.
To analyze data using inferential statistical techniques, including confidence intervals and hypothesis testing.
To test and quantitatively assess the impact of different improvement options using the design of an experiment.
To test for the significance of effects using an analysis of variance.
To implement control mechanisms for long-term monitoring using control charts for both quantitative and qualitative measurements.
To apply the six sigma methodology for the analyze, improve and control phases in your work or research.

Syllabus

Week 1: ANALYZE - Root Cause Analysis Introduction to methods for root cause analysis, including Cause and Effect (Fishbone diagrams) and Pareto Charts. We learn how to perform statistical correlations and regression analyses.

Week 2: ANALYZE - Inferential Statistics Learn the inferential statistics techniques of confidence intervals and hypothesis testing in order to use sample data and draw conclusions about or process centering.

Week 3: IMPROVE - Design of Experiments Plan designed experiments and calculate the main and interaction effects.

Week 4: MEASURE - Analysis of Variance Review how to perform a one-way Analysis of Variance (ANOVA) for comparing the between-factor variation to the within-factor variation for a single factor experiment. Use a two-way ANOVA for testing the significance of the factor effects for a 2x2 DOE.

Week 5: CONTROL - SPC and Control Charts Implement Statistical Process Control (SPC) & Control Chart Theory for monitoring process data and distinguishing between common cause variation and assignable cause variation. Construct X-bar and R Charts by calculating the upper and lower control limits and the centerline.

Week 6: CONTROL - Other Control Charts Understand other control charts, including p-and c-charts and I/MR, and EWMA Charts and review of the Control and Response Plan for Six Sigma projects.

Week 7: Quality Tools: FMEA, 8D, 5 Whys Use several important tools used in quality management, including the 8 Disciplines (8D) and 5 Whys, and learn the concept behind Design for Six Sigma (DFSS).

Week 8: Six Sigma Scenario and Course Summary Step through a full Six Sigma scenario, covering all phases of the DMAIC process improvement cycle.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops quality management skills which are core skills for managing and improving processes

Develops problem-solving skills, which are highly relevant in industry

Emphasizes data analysis and hypothesis testing, which are highly relevant in quality management

Provides hands-on practice through exercises and case studies, strengthening an existing foundation for intermediate learners

Instructors Martin Grunow and Holly Ott are experienced practitioners in the field of quality management

Reviews summary

Six sigma fundamentals

This online course titled "Six Sigma Part 2: Analyze, Improve, Control" introduces the concepts of Six Sigma methodology for analyzing, improving, and controlling processes. It is highly regarded by students, with all reviews giving a rating of 4 or 5 stars. The course is well-structured, engaging, and provides practical examples and exercises to enhance understanding. It is particularly valuable for individuals seeking a foundational knowledge in Lean manufacturing and Six Sigma principles.

Instructor is enthusiastic and makes the material interesting.

"The instructor (Holly) seems to be genuinely excited about the subject she is teaching which makes the lectures interesting and helps to keep you motivated."

Course is well-structured and easy to follow.

"The course is very well constructed."

"Lessons are well-structure and very completed to know how to apply DMAIC for processes."

Concepts are applicable to real-world manufacturing processes.

"The content may be applied to your day to day work."

"The concepts are very much latest and related with industry."

Course provides many examples and exercises to reinforce learning.

"There are a lot of examples that clarify the calculations and show how the theory matches with the practice."

Successful completion leads to a TUM Lean and Six Sigma Yellow Belt certification.

"Upon successful completion of this program, learners will earn the TUM Lean and Six Sigma Yellow Belt certification, confirming mastery of Lean Six Sigma fundamentals to a Green Belt level."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Six Sigma Part 2: Analyze, Improve, Control with these activities:

Review Lean and Six Sigma fundamentals

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Reinforce your understanding of Lean Six Sigma fundamentals to better prepare for the course material.

Browse courses on Lean Six Sigma

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Review notes and assignments from previous Lean Six Sigma courses.
Take practice quizzes and exam questions on Lean Six Sigma concepts.
Participate in online discussions or forums related to Lean Six Sigma.

Form a study group with classmates

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Enhance your understanding of course concepts by forming a study group with classmates to discuss material, solve problems, and support each other's learning.

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Connect with classmates and identify those with similar interests.
Establish regular meeting times and a study schedule.
Discuss course material, share notes, and work through problems together.
Provide feedback and support to each other's learning.
Prepare for assessments and collaborate on projects.

Practice statistical analysis techniques

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Improve your proficiency in statistical analysis techniques to enhance your ability to analyze data in the course.

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Work through practice problems on confidence intervals and hypothesis testing.
Use statistical software to perform data analysis and interpret results.
Join study groups or online communities to discuss statistical concepts.

Four other activities

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Attend a workshop on Six Sigma tools and techniques

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Gain hands-on experience and enhance your proficiency in using Six Sigma tools and techniques through attendance at a dedicated workshop.

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Research and identify relevant workshops.
Register for and attend the workshop.
Participate in interactive exercises and simulations.
Apply tools and techniques to real-world scenarios.
Receive guidance from experienced practitioners.

Develop a Six Sigma project plan

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Gain practical experience in applying Six Sigma principles by creating a project plan for a real-world problem.

Browse courses on DMAIC

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Identify a process or system that needs improvement.
Define the problem and gather data.
Analyze the data to identify root causes.
Develop and implement improvement solutions.
Monitor and evaluate the improvements.

Join a Lean Six Sigma project team

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Experience the practical application of Lean Six Sigma by joining an active project team to contribute to a real-world improvement initiative.

Browse courses on Process Improvement

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Reach out to potential project leaders or organizations.
Interview for a role on a project team.
Attend project meetings and contribute to discussions.
Apply Six Sigma methodologies to solve problems and improve processes.
Present project results and contribute to team deliverables.

Contribute to an open-source Six Sigma software project

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Deepen your understanding of Six Sigma principles and software tools by contributing to an open-source project that focuses on Six Sigma methodologies.

Browse courses on Open Source

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Identify open-source Six Sigma projects on platforms like GitHub.
Review the project documentation and codebase.
Identify areas where you can contribute your skills.
Submit pull requests with your contributions.
Collaborate with other contributors and receive feedback on your work.

Career center

Learners who complete Six Sigma Part 2: Analyze, Improve, Control will develop knowledge and skills that may be useful to these careers:

Six Sigma Black Belt

Six Sigma Black Belts are experts in the Six Sigma methodology. They lead and manage Six Sigma projects, and they use statistical techniques to identify and eliminate defects and non-conformances. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

See salaries and explore the career path for Six Sigma Black Belt

Six Sigma Green Belt

Six Sigma Green Belts are Six Sigma practitioners who have completed the Six Sigma Green Belt training program. They support Six Sigma projects and they use statistical techniques to identify and eliminate defects and non-conformances. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

See salaries and explore the career path for Six Sigma Green Belt

Quality Assurance Manager

Quality Assurance Managers evaluate the processes, products, and services of an organization to ensure they meet the appropriate standards. They analyze data and use statistical techniques to identify areas for improvement. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

See salaries and explore the career path for Quality Assurance Manager

Statistician

Statisticians collect, analyze, and interpret data. They use statistical techniques to draw conclusions about populations based on samples. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Data Analyst

Data Analysts collect, clean, and analyze data to help organizations make informed decisions. They use statistical techniques to identify trends and patterns in data, and they develop visualizations to communicate their findings. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform inferential statistics, design experiments, and implement statistical process control.

See salaries and explore the career path for Data Analyst

Quality Engineer

Quality Engineers develop and implement quality systems and procedures. They use statistical techniques to analyze data and to improve the quality of products and services. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

See salaries and explore the career path for Quality Engineer

Operations Manager

Operations Managers oversee the day-to-day operations of an organization. They are responsible for ensuring that the organization's processes are efficient and effective, and they use data to identify areas for improvement. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

See salaries and explore the career path for Operations Manager

Data Scientist

Data Scientists use statistical techniques to analyze data and to extract insights from data. They develop models and algorithms to predict future outcomes and to make recommendations. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Process Engineer

Process Engineers develop and improve processes for the production of goods and services. They use statistical techniques to optimize processes and ensure that products meet quality standards. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Business Analyst

Business Analysts analyze business processes and systems to identify areas for improvement. They use statistical techniques to analyze data and to develop recommendations for improvement. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

See salaries and explore the career path for Business Analyst

Manufacturing Engineer

Manufacturing Engineers design, develop, and improve manufacturing processes. They use statistical techniques to optimize processes and ensure that products meet quality standards. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Quality Control Inspector

Quality Control Inspectors inspect products and materials to ensure that they meet quality standards. They use statistical techniques to identify defects and non-conformances. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. They use statistical techniques to analyze data and to develop models to predict future financial performance. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Reliability Engineer

Reliability Engineers design and develop products and systems that are reliable and safe. They use statistical techniques to analyze data and to predict the likelihood of failures. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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Project Manager

Project Managers plan, execute, and close projects. They use statistical techniques to manage risk and to ensure that projects are completed on time, within budget, and to the required quality standards. The Six Sigma Part 2 course provides you with the skills and knowledge necessary to be successful in this role, including how to perform root cause analysis, use inferential statistics, and implement statistical process control.

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