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Course Title: Statistical Methods for Process Improvement:

Part 3: Using Process Control Charts

Davis M. Woodruff, PE, CMC

Course Outline

This 3 hour course presents a review and overview of using process control charts (Statistical Process Control or SPC) for process improvement. Practical how-to information for gathering data and creating control charts for various types of processes is included. It is not a theoretical statistics course and is intended as a practical course on using process control charts oriented to industry.

This course will also provide help organizations that are either ISO 9001, 14001, 13485, TS 16949 or AS 9100 registered or seeking registration to meet the requirements for process and product monitoring and measurement as well as data analysis and continual improvement found in the standards.

This course discusses the following topics:

Practical illustrations are used throughout the course and these process improvement tools may be adapted to any business or business model.

This course includes a multiple choice quiz at the end, which is designed to enhance the understanding of the course materials.

Learning Objective

At the conclusion of this course, the participant will:

Intended Audience

Any professional who is involved in process or product monitoring or measurement  or who needs to understand how to apply statistical methods to sustain effective process improvements.  Engineers, consultants and managers interested in understanding process or product monitoring and measurement as a part of the CI process and to more effectively manage your business using facts will benefit from this course on understanding and using process control charts.

Benefit to Attendees

Course participants will learn how to use simple, powerful and practical statistical methods for process improvement that can guide fact based decision making thought the effective use of process control charts.

Course Introduction

The process control chart (SPC chart as often called) is primarily a tool used to analyze data which is generated over a period of time.  Developed by Dr. Walter A. Shewhart in 1924, the control chart remains one of the most important tools in the SPC arsenal.  Although simple to use, it is very powerful in data analysis.

In Part 3 of Statistical Methods for Process Improvement we will learn about using several types of control charts and how to interpret what the process information is telling us.  However, before considering any specific chart, let's examine control charts in general.

What are Process Control Charts?  First of all, while the term "control chart" has been universally accepted and used, it must be understood that the chart does not control anything.  It only provides information which serves as a basis for action.  Control charts are effective only if those responsible for making decisions act on the information the chart reveals.  In other words, control charts are tools which can be used, misused, or not used at all.  Their effectiveness is directly related to the understanding of and proper application by the people using them, you and your colleagues.

To adequately control any repetitive operation requires continuous monitoring.  The control chart is a graphical representation of this monitoring process.
How do they work?  Control charts are all basically but provide the information necessary to determine the amount and type of variability present in a process.  Along the vertical axis a scale is established consistent with the data being collected.  The horizontal axis reflects the data sequence or time interval.   Control limits are calculated to let us know if the process is behaving as expected, or if there are special causes of variation present in our process. When the chart is properly interpreted one quickly sees whether investigative, preventive or corrective actions may be in order.

This 3 hour course presents a practical and common sense approach to understanding and using process control charts as part 3 a this five part series of Statistical Methods for Process Improvement. These are simple, yet powerful tools for process improvement.

Course Content

In this lesson, you are required to download and study the following course content in PDF format:

Course Title: Statistical Methods for Process Improvement: Part 3: Using Process Control Charts

Please click on the above underlined hypertext to view, download or print the document for your study. Because of the large file size, we recommend that you first save the file to your computer by right clicking the mouse and choosing "Save Target As ...", and then open the file in Adobe Acrobat Reader. If you still experience any difficulty in downloading or opening this file, you may need to close some applications or reboot your computer to free up some memory.

Course Summary

This five part series of courses provides the information necessary to apply fundamental statistical concepts and methods for process improvement. Statistics can be theoretical and boring. In fact, many engineers dreaded taking “stats” in college, but now find that practical statistics are essential in today’s work place. This course, part 1, as well as the other 4 parts will provide an understanding of how to really use statistics for process improvement. This is not a course in probability theory or theoretical statistics.

Related Links and References

A suggested reading list and detailed glossary is included with each of these courses. Also, there are several articles posted on that can be downloaded and used along with these courses..


Once you finish studying the above course content, you need to take a quiz to obtain the PDH credits.

Take a Quiz

DISCLAIMER: The materials contained in the online course are not intended as a representation or warranty on the part of PDH Center or any other person/organization named herein. The materials are for general information only. They are not a substitute for competent professional advice. Application of this information to a specific project should be reviewed by a registered architect and/or professional engineer/surveyor. Anyone making use of the information set forth herein does so at their own risk and assumes any and all resulting liability arising therefrom.