Control Charts
Introduction
Shewhart's discovery statistical process control or SPC, is a methodology for charting the process and quickly determining when a process is "out of control" (e.g., a special cause variation is present because something unusual is occurring in the process). The process is then investigated to determine the root cause of the "out of control" condition. When the root cause of the problem is determined, a strategy is identified to correct it.

It is management's responsibility to reduce common cause or system variation as well as special cause variation. This is done through process improvement techniques, investing in new technology, or reengineering the process to have fewer steps and therefore less variation. Management wants as little total variation in a process as possible--both common cause and special cause variation. Reduced variation makes the process more predictable with process output closer to the desired or nominal value.

Having a point outside the control limits is the most easily detectable out-of-control condition.

Control Chart Zones Control charts can be broken into three zones, a, b, and c on each side of the process center line.A series of rules exist that are used to detect conditions in which the process is behaving abnormally to the extent that an out of control condition is declared.

Types of Out-of-Control Conditions
Extreme Point Condition This process is out of control because a point is either above the UCL or below the UCL.This is the most frequent and obvious out of control condition and is true for all control charts.

Two of Three Consecutive Points in Zone A or Outside Zone A The probability of having two out of three consecutive points either in or beyond zone A is an extremely unlikely occurrence when the process mean follows the normal distribution. Thus, this criteria applies only to charts for examining the process mean.X, Y, and Z are all examples of this phenomena.

Runs Above or Below the Centerline The probability of having long runs (8 or more consecutive points) either above or below the centerline is also an extremely unlikely occurrence when the process follows the normal distribution. This criteria can be applied to both and r charts. Example X above shows a run below the center line.

Linear Trends The probability of 6 or more consecutive points showing a continuous increase or decrease is also an extremely unlikely occurrence when the process follows the normal distribution. This criteria can be applied to both and r charts. X and Y are both examples of trends. Note that the zones play no part in the interpretation of this out of control condition.

Oscillatory Trend The probability of having 14 or more consecutive points oscillating back and forth is also an extremely unlikely occurrence when the process follows the normal distribution. It also signals an out of control condition. This criteria can be applied to both and r charts.

Avoidance of Zone C The probability of having 8 or more consecutive points occurring on either side of the center line and do not enter Zone C is also an extremely unlikely occurrence when the process follows the normal distribution and signals an out of control condition. This criteria can be applied to charts only. This phenomena occurs when more than one process is being charted on the same chart

Run in Zone C The probability of having 15 or more consecutive points occurring the Zone C is also an extremely unlikely occurrence when the process follows the normal distribution and signals an out of control condition. This criteria can be applied to charts only. This condition can arise from improper sampling, falsification of data, or a decrease in process variability that has not been accounted for when calculating control chart limits, UCL and LCL.

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