Lean Six Sigma Overview
This course covers the core concepts of Lean Six Sigma and its methods for boosting organizational productivity across aerospace, automotive, healthcare, and many other industries. Learn about the origins of the Lean Six Sigma concept, how it affects your business, and how to apply the DMAIC process for better results.
Define Phase and Project Selection
This course teaches how to identify, prioritize, and scope projects at your organization. It explains how to identify potentially productive projects within an organization, prioritize projects, create an initial project scope, and set objective goals. After completing this course, you’ll be emboldened to take up and help supervise projects at your company, ensuring they’re completed and that goals are met.
This training focuses on the Define phase in the Lean Six Sigma methodology. You’ll find detailed examples of how to identify and manage projects and become much more valuable to your organization.
Lean Six Sigma Organizational Deployment
This course dives into the guidelines for deploying Lean Six Sigma in your organization. It breaks down the organizational structure for Lean Six Sigma projects and the roles and responsibilities of each person contributing to the organizational success. You’ll grasp how Lean Six Sigma applies from upper management to the lowest-level employees. You’ll also gain an understanding of the different approaches to deploying Lean Six Sigma and how to choose the best one based on organizational circumstances.
This training focuses on the Define phase in the Lean Six Sigma methodology. You’ll find detailed examples of how to identify and manage projects and become much more valuable to your organization.
Process Variables Mapping
This course gives students an in-depth understanding of the Process Variables Mapping tool. You’ll learn what a Process Variables Map is and the elements needed to create one. Then, following the provided step-by-step example, you’ll create a Process Map from scratch, visualizing how activities are connected to achieve common goals.
Get ready to understand Process Mapping and how it fits into the Six Sigma DMAIC methodology. By the end of this course, you’ll have the necessary skills to create a Process Map for any project, significantly enhancing your value to employers. Process Maps empower project stakeholders to visualize and make decisions to improve the overall process, making you a valuable asset in any organization.
Cause and Effect Matrix
This course will explain how the Cause and Effects (C&E) Matrix emerges from the Process Variables Map. Get ready to learn how to create a C&E Matrix from any Process Variables map, with detailed illustrations and examples. How does the C&E Matrix fit into the Lean Six Sigma roadmap? You’re about to know the answer.
The cause-and-effect matrix lets you prioritize key process input variables (KPIVs) based on the key process output variables (KPOVs). In simpler words, it lets you establish the correlation between process input variables and giving customers their desired outputs. Understanding the C&E matrix gives you an advantage when managing business processes.
Failure Mode Effects Analysis
FMEA entails reviewing as many components and subsets of a business process as possible to find potential failure modes. It can be a qualitative or quantitative analysis based on statistics.
This module will discuss the Failure Mode Effects Analysis (FMEA) and how to apply it to recognize sources of risk and potential failures in business processes. Get ready to learn about the various uses of FMEA and how this tool helps your organization stay ahead of the competition. After completing this course, you’ll know how to create an FMEA for any project, identifying and tackling risks to improve productivity.
Waste Identification and Recommended Actions
When any team investigates its assigned business processes, one of the most important things is seeking opportunities to reduce waste. Every team needs to identify and reduce non-value-adding activities.
This self-paced course explores the 8 sources of waste, DOWNTIME: defects, Overproduction, Waiting, Non-Utilized Talent, Transportation, Inventory, Motion, and Extra-Processing. It’ll help you identify waste more effectively, mainly by breaking it down into these 8 categories. The knowledge and skills from this module will help you improve business processes and become more valuable at any organization.
Introduction To Statistics And Graphical Analysis
Statistics and analysis are an inseparable part of the Lean Six Sigma process. Professional workers must know how to analyze business processes to identify defects and brainstorm solutions. You’re about to gain valuable knowledge in this area.
This course discusses the two types of data you’ll find in any project. It explains the Shape, Center, and Spread measures for data analysis and briefly discusses the properties of a Normal distribution. It then dives into the different types of graphs and how to use them to show any sample data’s Shape, Center, and Spread. Finally, this module covers how to use graphs to compare groups within sampled data.
Introduction to Graphical Analysis with Minitab
Minitab is a well-known data analysis and process improvement tool. Mastering this tool makes it easy to spot trends, analyze business processes, and discover insights to fix the processes. This course will introduce you to Minitab and how to use it for graphical analysis.
How does Minitab work? How can I use it to create graphs and extract valuable insights from raw data? Get ready to gain an understanding of this tool and how to apply it effectively to analyze business processes. Completing this training boosts your analytical skills and gives you an upper hand in managing business projects.
Introduction to Statistical Process Control
Statistical Process Control (SPC) involves applying statistical methods to monitor the quality of a business process. It helps ensure that production processes give high-quality output and keep customers satisfied. This course covers SPC and its applications to help companies operate efficiently.
You’ll gain an understanding of the two types of process variations (Common Cause and Special Cause), the two types of control charts for continuous data, and how to interpret control charts as part of Statistical Process Control. Overall, you’ll understand how Statistical Process Control fits into the DMAIC roadmap to make companies more efficient.
Measurement Systems Analysis
Measurement Systems Analysis (MSA) is a mathematical method for determining the amount of variation that exists in a process. It helps determine the suitability of a measurement system a business wants to adopt, and it’s vital to have a well-designed measurement system to enable accurate data collection.
This course delves into Measure Systems Analysis (MSA), starting with the basics and teaching how to set up and perform this analysis. It also teaches alternative ways to determine the credibility of the process data and how to use Attribute Agreement Analysis to quantify variation. Exercises are available to practice and become an expert at MSA.
Introduction to Capability
A capability study is one of the main tools of Lean Six Sigma. It involves analyzing a process to know whether it will produce significant defects. It quantifies the probability of a process resulting in defects, and this information is applied to improve the process to meet customer demand.
This course will explain the different methods for evaluating a process’s baseline capacity, depending on the type of data being analyzed. You’ll gain an understanding of the different indices for measuring capability and the common outputs from Capability studies based on continuous data.
Multi-Vari Studies
A multi-vari analysis study shows the variation in output changes across different inputs, helping businesses determine the source of the variability. Multi-vari charts visualize the source of variation, identify inputs affecting a business process, and help reduce or eliminate variations to improve business efficiency.
This course will explain the definition and purpose of a Multi-Vari study. It’ll show you how to conduct a Multi-Vary study to identify and mitigate the sources of process variations. After completing this module, you’ll understand where the Multi-Vari study fits in the DMAIC process and the steps required to carry out this analysis.
Hypothesis Testing
Hypothesis testing is a statistical method for determining whether data sufficiently supports a specific hypothesis. It’s a vital skill when analyzing business processes to identify and solve problems. This course will dive deep into Hypothesis testing to enhance your analytical skills.
We’ll introduce you to Hypothesis Testing and explore the Null and Alternative Hypotheses. We’ll explain the use of p-values in decision-making, the Analysis Roadmap, and how to apply the Test Selection Matrix. You’ll also gain an understanding of the two types of errors that occur when using these concepts and how to navigate them.
Chi-square Test
A chi-square test is an important statistical test used to analyze contingency tables when sample sizes are large. It compares observed results with expected results, determining whether the difference between observed data and expected data is due to chance or a relationship between the variables. It tells you whether further investigations should be carried out.
This course explores the chi-square test and its applications in the DMAIC roadmap. You’ll learn about the data required for this test and how to conduct it with this data in your hands.
Correlation & Regression
Correlation & Regression are the two crucial techniques for investigating the relationships between two variables. Correlation determines whether the variables have a linear relationship, and regression determines the cause and effect between the variables.
This course will explore Correlation & Regression and how to use them to measure the relationship between two or more quantifiable elements. You’ll start from the basics and go all the way to the complex aspects of applying this statistical technique.
Roadmaps for Comparing Groups t-Test and One-Way ANOVA
The t-test is used to compare the means of two population groups, while the ANOVA technique compares the means of three or more population groups. T-tests focus on within-group variation, while ANOVA analyzes between-group and within-group variation.
These two distinct yet valuable tests are crucial in the Six Sigma methodology. This course will teach you about them.
