# Mod10-Control Charts

Module 10

CONTROL CHART

CONTROL CHART

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Basic Tools for Process Improvement

What is a Control Chart?

A control chart is a statistical tool used to distinguish between variation in a process resulting from common causes and variation resulting from special causes. It presents a graphic display of process stability or instability over time (Viewgraph 1). Every process has variation. Some variation may be the result of causes which are not normally present in the process. This could be special cause variation. Some variation is simply the result of numerous, ever-present differences in the process. This is common cause variation. Control Charts differentiate between these two types of variation. One goal of using a Control Chart is to achieve and maintain process stability. Process stability is defined as a state in which a process has displayed a certain degree of consistency in the past and is expected to continue to do so in the future. This consistency is characterized by a stream of data falling within control limits based on plus or minus 3 standard deviations (3 sigma) of the centerline [Ref. 6, p. 82]. We will discuss methods for calculating 3 sigma limits later in this module. NOTE: Control limits represent the limits of variation that should be expected from a process in a state of statistical control. When a process is in statistical control, any variation is the result of common causes that effect the entire production in a similar way. Control limits should not be confused with specification limits, which represent the desired process performance.

Why should teams use Control Charts?

A stable process is one that is consistent over time with respect to the center and the spread of the data. Control Charts help you monitor the behavior of your process to determine whether it is stable. Like Run Charts, they display data in the time sequence in which they occurred. However, Control Charts are more efficient that Run Charts in assessing and achieving process stability. Your team will benefit from using a Control Chart when you want to (Viewgraph 2) Monitor process variation over time. Differentiate between special cause and common cause variation. Assess the effectiveness of changes to improve a process. Communicate how a process performed during a specific period.

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CONTROL CHART

Basic Tools for Process Improvement

What Is a Control Chart?

A statistical tool used to distinguish between process variation resulting from common causes and variation resulting from special causes.

CONTROL CHART

VIEWGRAPH 1

Why Use Control Charts?

• Monitor process variation over time • Differentiate between special cause and common cause variation • Assess effectiveness of changes • Communicate process performance

CONTROL CHART

VIEWGRAPH 2

CONTROL CHART

3

Basic Tools for Process Improvement

What are the types of Control Charts?

There are two main categories of Control Charts, those that display attribute data, and those that display variables data. Attribute Data: This category of Control Chart displays data that result from counting the number of occurrences or items in a single category of similar items or occurrences. These “count” data may be expressed as pass/fail, yes/no, or presence/absence of a defect. Variables Data: This category of Control Chart displays values resulting from the measurement of a continuous variable. Examples of variables data are elapsed time, temperature, and radiation dose. While these two categories encompass a number of different types of Control Charts (Viewgraph 3), there are three types that will work for the majority of the data analysis cases you will encounter. In this module, we will study the construction and application in these three types of Control Charts: X-Bar and R Chart Individual X and Moving Range Chart for Variables Data Individual X and Moving Range Chart for Attribute Data Viewgraph...

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