Course Title: Statistical Methods for Process Improvement:

Part 1: Using Data for Process Improvement

Davis M. Woodruff, PE, CMC

Course Outline

This 3 hour course presents a review and overview of practical and simple statistical methods that can be used for process improvement. Practical how-to information for gathering data and converting it into useful information for process improvement is presented. It is not a theoretical statistics course and is intended as a review/overview type course which is practical and 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:

• Introduction to Statistical Methods and Data Analysis as a Process
• Variability: The Enemy of Process Improvement
• Data Display is the First Step
• Descriptive Statistics: Using Numbers to Describe Distributions or “Families of Data”
• Using Samples to Represent Distributions

Practical  examples and illustrations are used throughout the course and these process analysis 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:

• Understand the basic concepts of statistical methods;
• Understand variability and how to identify sources of variability;
• Be able to use simple tools for using data for process analysis;
• Be able to describe families of data or distributions using the measures of central tendency and the measures of variability;
• Know the 3 measures of central tendency and 2 measures of variability;
• Understand the relationships between samples and populations;
• Know the practical meaning of the central limit theorem of statistics and how it relates to industry;
• Be able to calculate or use software to calculate descriptive statistics;
• Know how to create and use histograms to present data; and
• Understand that sample averages can be used even if the parent population is non-normal.

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 continual 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.

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.

Course Introduction

To prosper in today's economic climate, companies and their suppliers must be dedicated to never-ending improvement in quality and productivity.  Leaders must constantly search for more efficient ways to produce products and services that meet customers’ needs.  Most organizations clearly state their dedication to achieve continual quality improve­ment in the company's Quality Policy.

Most everyone agrees that "Doing it right the first time" and the policy of prevention are sensible and even obvious philosophies which will, when adopted, improve the quality of all the products manufactured or services provided by any company.

Quantitative measures are needed to effectively monitor process and product or service performance.  Statistical methods can provide the data and information to more effectively manage your business. The recent emphasis on Six Sigma and other similar “programs” is really nothing more than an organized approach to gathering, analyzing, managing and acting on data. The underlying principles are found in the basic concepts of statistics and Statistical Process Control or SPC and its associated problem solving techniques. These are simply the quantitative tools which will allow us to get a more objective handle on quality and productivity.  These concepts have been taught under the banner of SPC, Statistical Methods and most recently the Six Sigma approach. All of these are based on simple statistical methods that can help manage process variability and thus improve quality.

This 3 hour course presents a practical and common sense approach to foundational statistical methods for process analysis as the first of a five part series.

Course Content

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

Course Summary

This five part series of courses will provide 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.

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