SPC_Overview.pdf

Introduction to

STATISTICAL

PROCESS

CONTROL

TECHNIQUES

SPC OVERVIEW

Preface

New Demands On Systems Require Action

Socratic SPC -- Overview Q&A

Steps Involved In Using Statistical Process Control

Specific SPC Tools And Procedures

Identification and Data gathering

Pareto Charts

Analysis Of Selected Problem

Cause-and-Effect or Fishbone Diagram

Flowcharting

Scatter Plots

Data Gathering And Initial Charting

Check Sheets

Histograms

Probability Plot

Control Charts

Fundamental Concepts And Key Terms

Zones In Control Charts

Control Limits

Subgroups

Phases

Using Process Control Charts

Data Definitions For Proper Chart Selection

 2007 Statit Software, Inc., 1128 NE 2nd Street, Ste 108, Corvallis, Oregon 97330

iii

Quality Control Today

Prioritizing

Rules Testing

SPC OVERVIEW

Types Of Charts Available For The Data Gathered

Variable Data Charts – Individual, Average And Range Charts

Average Charts – X-bar Chart

Range Chart – R-Chart

Moving Range Chart – MR Chart

Combination Charts

Individual And Range Charts – IR Charts

Average & Range Charts – X-Bar And R Charts

X-Bar Standard Deviation Charts – X-Bar And S Charts

Process Capability Chart – cp Chart

Attribute Data Charts

Attribute Charts – Defects and Rejects Charts

c Chart – Constant Subgroup Size

u Chart – Varying Subgroup Size

Rejects Charts

np Chart – Number of Rejects Chart for Constant Subgroup Size

p Chart – Percentage Chart for Varying Subgroup Size

Conclusion – Time to put it all together…

Appendix 1: AT&T’s Statistical Quality Control Standards

Glossary

Bibliography

URLs

Individual Charts – I chart

Defects Charts

Preface: by Marilyn K. Hart, Ph.D. & Robert F. Hart, Ph.D.

Quality Control Today

In this era of strains on the resources and rising costs of manufacturing, it becomes

increasingly apparent that decisions must be made on facts, not just opinions.

Consequently, data must be gathered and analyzed. This is where statistical process

control (SPC) comes in. For over 70 years, the manufacturing arena has benefited from

the tools of SPC that have helped guide the decision-making process. In particular, the

control chart has helped determine whether special-cause variation is present implying

that action needs to be taken to either eliminate that cause if it has a detrimental effect on

the process or to make it standard operating procedure if that cause has a beneficial

effect on the process. If no special-cause variation is found to be present, SPC helps

define the capability of the stable process to judge whether it is operating at an

acceptable level.

The strength of SPC is its simplicity. And with the use Statit on the computer to make the

calculations and to plot the charts, the simplicity becomes complete.

New Demands On Systems Require Action

Accountability with hard data, not fuzzy opinions, is being demanded. Existing processes

must be examined and new ones discovered. The good news is that improved quality

inherently lowers costs as it provides a better product and/or service. Statistical Process

Control provides accountability and is an essential ingredient in this quality effort.

Statistical Process Control is not an abstract theoretical exercise for mathematicians. It is

a hands-on endeavor by people who care about their work and strive to improve

themselves and their productivity every day. SPC charts are a tool to assist in the

management of this endeavor. The decisions about what needs to be improved, the

possible methods to improve it, and the steps to take after getting results from the charts

are all made by humans and based on wisdom and experience. Everyone should be

involved in this effort!

SPC OVERVIEW

Socratic SPC -- Overview Q&A

So what is Statistical Process Control?

Statistical Process Control is an analytical decision making tool which allows you to

see when a process is working correctly and when it is not. Variation is present in

any process, deciding when the variation is natural and when it needs correction is

the key to quality control.

Where did this idea originate?

The foundation for Statistical Process Control was laid by Dr. Walter Shewart working

in the Bell Telephone Laboratories in the 1920s conducting research on methods to

improve quality and lower costs. He developed the concept of control with regard to

variation, and came up with Statistical Process Control Charts which provide a simple

way to determine if the process is in control or not.

Dr. W. Edwards Deming built upon Shewart’s work and took the concepts to Japan

following WWII. There, Japanese industry adopted the concepts whole-heartedly.

The resulting high quality of Japanese products is world-renowned. Dr. Deming is

famous throughout Japan as a "God of quality".

Today, SPC is used in manufacturing facilities around the world.

What exactly are process control charts?

Control charts show

the variation in a

measurement during

the time period that

the process is

observed.

In contrast, bell-curve

type charts, such as

histograms or

process capability

charts, show a

summary or snapshot

of the results.

Process control charts are fairly simple-looking connected-point charts. The points

are plotted on an x/y axis with the x-axis usually representing time. The plotted

points are usually averages of subgroups or ranges of variation between subgroups,

and they can also be individual measurements.

Some additional horizontal lines representing the average measurement and control

limits are drawn across the chart. Notes about the data points and any limit violations

can also be displayed on the chart.

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