Intro to Six Sigma 171

"Intro to Six Sigma" provides a comprehensive introduction to the goals, methods, and tools used during Six Sigma initiatives. This class discusses the different roles in a Six Sigma team, DMAIC steps, and how to identify variation. Intro to Six Sigma also covers the tools practitioners use to track and analyze data, such as Pareto charts, frequency distribution charts, and run charts.

Unlike some quality initiatives, Six Sigma offers tangible, measurable methods to gage a project's success. This class gives new practitioners the foundational knowledge needed to support a Six Sigma project by introducing them to key terminology and important data analysis tools.

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Class Details

Class Name:: Intro to Six Sigma 171
Version:: 2.0
Difficulty:: Beginner
Number of Lessons:: 18
Related 1.0 Class:: Intro to Six Sigma 170

Class Outline

What Is Six Sigma?
Choosing a Target Problem
Identifying Critical to Quality
Six Sigma Review
Six Sigma Roles and Responsibilities
Six Sigma Process Improvement Method: DMAIC
5 Ms and 1 P
Root Cause Analysis
Variation
Six Sigma Practices Review
The Importance of Data
Types of Data
Gathering Data
Data Analysis and Tools: Pie Charts and Pareto Charts
Data Analysis Tools: Frequency Distribution Charts
Data Analysis Tools: Run Charts
Six Sigma Charts Review
Implementing Six Sigma

Objectives

Define Six Sigma.
Describe how Six Sigma practitioners choose a target problem.
Describe the factors that impact CTQ.
Identify the roles and responsibilities of Six Sigma team members.
Identify the steps in DMAIC.
Identify the main factors that lead to process problems.
Define root cause analysis.
Define common cause variation and special cause variation.
Describe the importance of data for Six Sigma projects.
Distinguish between discrete data and continuous data.
Describe common data gathering methods.
Describe pie charts and Pareto charts.
Describe frequency distribution charts.
Describe run charts.
Distinguish between Six Sigma and lean initiatives.

Job Roles

Certifications

Glossary

Vocabulary Term	Definition
5 Ms and 1 P	An expression identifying the six major factors most likely to be the source of problems. These factors are machines, materials, methods, Mother Nature, measurement, and people.
attribute data	Data that represents a characteristic or individual count. Attribute data, also known as discrete data, cannot be added or subtracted from other attribute data sets.
bell curve	A graph of continuous data characterized by a high center, tapered sides, and flared edges. A bell curve reflects conditions that exhibit natural variation.
black belt	BB. A Six Sigma practitioner with the most training who acts as the project leader. Black belts work full time on projects and coach lower-level team members.
champion	A Six Sigma designation for an executive or manager within a company who facilitates the project by providing the necessary resources.
charter	A document that serves as a problem statement defining the Six Sigma project target. The charter is developed in the first DMAIC step.
common cause variation	A deviation that is normal and expected and that cannot be traced back to a single source. Common cause variation, also known as natural variation, does not cause a fundamental change in the process.
continuous data	Data that can be measured on a scale and compared with other data. Continuous data, also known as variable data, can be added to or subtracted from other continuous data.
critical to quality	CTQ. Specific, measurable characteristics of a product or service that are identified by customers as necessary for their satisfaction. CTQ characteristics are the focus of Six Sigma projects.
cycle time	The time that elapses from the beginning to the end of a process. Cycle time must match takt time in order for a manufacturer to meet customer demand.
data	Factual information that is used for analysis and problem solving. Data is often in the form of values or numbers.
data	Factual information, usually in the form of numbers, that is used for analysis and problem solving. Data is used to find the root causes of process problems.
discrete data	Data that represents a characteristic or individual count. Discrete data, also known as attribute data, cannot be added or subtracted from other discrete data sets.
DMAIC	Six Sigma's five steps for process improvement. DMAIC stands for define, measure, analyze, improve, and control.
external customer	An outside organization or individual that receives a product or service from the company. External customers determine which product characteristics are critical to quality (CTQ).
frequency distribution charts	A chart that displays the number of occurrences in a continuous data set. Normal distribution on a frequency distribution chart will create a bell curve.
green belt	GB. A team member trained in Six Sigma who spends about 20% of his or her time on Six Sigma projects and about 80% on regular duties.
internal customer	A department or individual within the company that relies on others to satisfy the external customer. For any cell, the next cell in a process is always the internal customer.
master black belt	MBB. A hands-on Six-Sigma practitioner who works closely with other members to set and carry out project goals. Master black belts work full time on projects and coach lower-level team members.
Pareto chart	A chart that displays discrete data as sets of bars in ascending or descending order. Pareto charts support the Pareto principle, which states that for most events, approximately 80% of the effects result from 20% of the causes.
pie chart	A circular chart that is divided into sections or 'slices' that represent a proportion of collected data. Pie charts show data as divided parts of a whole.
process mapping	A graphical method of capturing the steps of a process. Process mapping can be performed before and after a process is improved.
process owner	A temporary designation for the person responsible for process design and performance. Green belts are sometimes considered process owners.
root cause analysis	A study to determine the cause of a problem. Root cause analysis involves collecting and analyzing data to find a problem's origin.
run chart	A graph that displays process performance data tracked over time. Most run charts best represent continuous data.
Six Sigma	A management philosophy and process improvement method that uses data to identify problems and point to improvements. Six Sigma's goal is to reduce the number of defects to less than 3.4 defects per million opportunities, which is near perfection.
special cause variation	A deviation that causes an undesirable, fundamental change in a process. Special cause variations, also known as unnatural variations, can be traced back to a single source.
statistical process control	SPC. A method of measuring and controlling the processes that yield a product. In SPC, statistics are used to collect sample data and predict outcomes.
variation	Any deviation from what is normal and consistent. Common cause variation is normal and expected, while special cause variation indicates a problem.
yellow belt	YB. A designation for other staff members who help with Six Sigma projects.
yellow belt	YB. A designation for other staff members who help with Six Sigma projects. Yellow belts are less involved in Six Sigma projects than green belts.