Capability analysis is a computational method for comparing the output of a manufacturing process to its engineered specification limits. It's also an essential set of tools for new process development, 6-sigma projects, Statistical Process Control, and process monitoring. This set of tools can be applied to product characteristics such as its size, weight and hardness, or to process characteristics such as temperature, voltage or flow.
Capability analysis is a computational method for comparing the output of a manufacturing process to its engineered specification limits. It's also an essential set of tools for new process development, 6-sigma projects, Statistical Process Control, and process monitoring. This set of tools can be applied to product characteristics such as its size, weight and hardness, or to process characteristics such as temperature, voltage or flow.
This class, "Process Capability Analysis" starts at the beginning of how manufacturing processes are developed and analyzed. It moves on to the basic concepts of capability analysis along with it applications and math (both "on paper" and in Excel). You will learn how to analyze capability data for a population, for a sample drawn from a population, and from the data found on control charts. At the end, you will also learn more advanced topics such as dealing with one-sided tolerances and an alternate capability index call Cpm. Plus, you'll receive all the Excel templates and "cheat sheets" you'll need to apply this to your manufacturing projects.
By the end of this course, you will have a thorough understanding of capability analysis, and be able to apply these tools broadly across a wide range of production problems.
Also, if you are studying for your ASQ CQE, CQT or CQIA exams, this is essential material. I carefully explained the difference between Cpk and Ppk, between analyzing a population and a sample, and how to interpret your capability analysis results; all critical elements on these exams.
Hear what you're colleagues are saying about Process Capability Analysis:
“This Process Capability Analysis class is awesome. ” - Lawrence M.
“Clarity on the confusing Process Capability concepts and how to apply them was well explained. Lecture very good and passionate about the subject. Thank you very much, really enjoyed the course from start to finish.” - Kemsley J.
“I'm a quality manager, consultant and project manager in the food industry. This course was a great way to for me to gain experience with process capability analysis. The explanations were thorough and the examples made the math and statistics come to life. I recommend this to anyone who wants to better understand the measures of process capability.” - Chris F.
“A comprehensive knowledge of utilizing Pp and Cp Indices. Also the instructor have good knowledge and understanding of the topic.” - Nasir M.
“I work in manufacturing and appreciated this courses focus on Cpk and Ppk . it gave me a better understanding of what I was looking at when i analyzed process capability data. it is definitely worth taking if you use process capability charts. Easy to follow and made a dry topic easy to follow and complete. ” - Robin S.
“Great course. If you work in a manufacturing environment, you will find that the lessons are very applicable to your everyday dealings with quality. The instructor (Ray) mentions that even many quality professionals are 'fuzzy' with some of these concepts. I have found that to be true in my experience. I much appreciate Ray Harkins for delivering this great content. ” - Charles S.
“Great refresher course. ” - Wallace Y.
If you want to excel as a quality or manufacturing professional, you must understand and be able to apply Sign up today.
An introduction to this course, "Process Capability Analysis"
By having an overview of the manufacturing development process, it's much easier to see where Process Capability Analysis is best applied. Excel spreadsheets and additional info attached to this lecture.
A continuation of the Manufacturing Development Process.
This video shows you a real manufacturing process in action: Donut-making!! The it ideas a few of the key process and product parameters.
A discussion of the available measurement systems and their accuracies.
Should you measure 100% of the parts you produce or just a sample of them? It depends on the application.
Picking the correct sampling option for your application.
Why a 30 piece sample size matters.
Understanding the arithmetic mean as a cornerstone to Process Capability Analysis
How to measure the spread, or dispersion of data.
The histogram is one of the seven quality tools. It is effective is visualizing your capability data, and estimating its underlying probability distribution.
The most common underlying statistical distribution and a key input to process capability analysis.
A continued exploration of this very important probability distribution.
The first pair of capability indices, used to examine a "population" of process data.
A continuation of this first pair of capability indices.
Wrap up of Pp and Ppk to measure the capability of a population.
A slight twist when applying Pp and Ppk to a "sample" of data.
Another of the seven quality tools, the run chart is the foundation for the second pair of capability indices: Cp and Cpk.
The math behind these critical indices.
Using Excel to calculate Cp and Cpk.
What does it all mean? Interpreting your process capability results.
One of the most commonly misunderstood aspects or capability analysis: What's the difference between Cpk and Ppk?
A graphical look at the differences between Cpk and Ppk.
Closing thoughts on interpreting your results.
The introduction to a few "advanced" topics in capability analysis.
A simple review quiz of the previous material
One of the most commonly asked questions ... how to deal with one-sided tolerances.
A model showing the effect of targeting your process on financial loss.
Calculating Cpm to determine a process's capability relative to its target.
Calculating Cpm in Excel.
Applications of Cpm.
Closing thought on the course.
"Real Life" example exercises that you can complete to practice you're newly learned skills. Solution provides within.
Once you calculate the estimated x-bar and sigma for a population, and determine that it has an underlying normal population distribution, you can plug your parameters into Excel to easily calculate the percent of the population above and/or below values you choose. This method is an excellent way to estimate the percent of a population outside your specification limits.
Continued in Excel.
A slightly more complicated, yet more realistic version of the above scenario. This version has values both above the USL and below the LSL.
Continue in Excel.
Calculating the cost of quality defects through a process requires some simple data modeling and formulas that may not be intuitive. This video shows how to model quality defect costs through a series of processes.
Combining what we learned about estimating the percent defective in a process using our capability data with costing defects through a series of processes is powerful. This video shows you how to build a data model that will show the value of improvement opportunities.
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.