### Description of Column Names

The following are all the columns available to the detailed mode of the Feature Monitor tab.

You can show or hide columns by selecting Detail from the View toolbar icon. See "View Icon".

The following are all the columns available to the Detailed View of DataMonitor+.

You can show or hide columns by selecting the Options tab, Dimension group and clicking Detail. See "Detail".

Note that Part, Variable, and Chart View cannot be hidden.

Internal Note: Math Formulas use syntax from:

http://mathcs.chapman.edu/~jipsen/mathml/asciimathsyntax.html

Part

The name of the part.

Variable

The feature variables.

PP% (PpPercent)

Capability percentage (3 sigma estimate).

Pr

Capability ratio (3 sigma estimate).

Pp

Capability index. Pp is calculated based on normal distribution parameters.

`Pp = ((USL) *( LSL)) / (6sigma)`

See "Calculations of Capability Based on Normal Distribution Parameters".

PpK

`Ppk = M\i\nim\um(Ppu, Ppl)`

(If no lower tolerance exists, then `Ppk = Ppu`)

Capability index, uncentered, based on normal distribution parameters. By default, a value of 1.33 is used, but you can set the value for Ppk by clicking the Capability Threshold button accessed through the SPC Calculations menu option from the Chart tab's Chart Options icon.

See "Calculations of Capability Based on Normal Distribution Parameters".

PC%

`PC% = 100.0 / (C p)`

A capability percentage indicating the percent of specification used. PC% is the ratio of the process width (6 ) to the specification width (USL-LSL) expressed as a percentage.

Cr

`Cr = (6sigma)/(Tol)`

Where Tol is the total tolerance.

Capability ratio. The capability ratio is used to determine whether or not the process produces products that meet the expected distribution. Usually, if Cr is 1. or greater, the process is not capable ( i.e., the process width is greater than the specification limits). Cr equals 6 divided by the total tolerance.

Cp

`Cp = (Tol)/(6sigma)`

Where Tol is the total tolerance width.

The potential capability index (Cp) helps to determine whether or not the process produces products within specification limits. Cp is a measure of how many 6 sigma curves can fit between given specification limits. If Cp is greater than 1, the entire process may fit within specification limits. A Cp of less than 1 indicates that the process has too much spread to meet specifications; that is, the process is not capable. Cp equals the total tolerance divided by 6 (the total tolerance width is calculated by subtracting the lower specification limit from the upper specification limit).

See "Capability Indexes: Table of Calculations".

CpK

`Cpk = MINIMUM(CpU, CpL)`

For one-sided measurements like flatness, `Cpk = CpU`

Actual capability index, based on subgroup size and the current control chart’s standard deviation. (For calculations of standard deviations for control charts, see Estimates of Standard Deviation Based on Control Charts.)

Cpk is a measure of how many 3 sigma half curves will fit between the process center and the closest specification limit. A value of 1.33 (i.e., the center is 4 sigma away from specification limits) or greater is a typical target.

See "Capability Indexes: Table of Calculations".

Estimates of Standard Deviation Based on Control Charts

Nominal

Target value.

Lsl

LSL = Nominal + Lower Tolerance

Lower specification limit. The LSL equals the nominal + lower tolerance.

Usl

USL = Nominal + Upper Tolerance

Upper specification limit. The USL equals the nominal plus the upper tolerance.

MeanDev

This shows the average deviation from the nominal.

Mean

This shows the average measurement when you have multiple transactions selected. If you only have one transaction selected, it shows the actual measured value.

Est Sigma

EST STD DEV

Estimated standard deviation.

Sigma

Standard deviation, represented as `sigma`. Sigma is a unit of measure indicating the width or spread of the process distribution.

See "Estimates of Standard Deviation Based on Control Charts".

3 Sigma

3S or 3 STD DEV or 3SIGMA

Three times the standard deviation. This value is generally used to define control limits

`(bar X +-3sigma)`

6 Sigma

6 STD DEV or 6SIGMA

Six times the standard deviation.

UCL

Upper control limit. This is the upper limit for points plotting above the center level on control charts. The upper control limit is used as a criterion for evaluating whether or not the process is in control.

LCL

Lower control limit. This is the lower limit for points plotting below the center level on control charts. The lower control limit is used as a criterion for evaluating whether or not the process is in control. In DataPage for Windows, the LCL is calculated from actual measurement data in the X (upper) portion of Individual and Subgroup Charts.

Actual Low

The actual lowest value in the sample.

Actual High

The actual highest value in the sample.

Est Low

`EST\ LOW = MEAN - 3sigma`

The estimated lowest value that is in control, based on the distribution.

Est High

`EST\ HIGH = MEAN + 3sigma`

The estimated highest value that is in control, based on the distribution.

% Out Spec

Actual percentage of measurements that are out of specification (that is, that are greater than the upper specification limit or less than the lower specification limit).

% Est Out Spec

Estimated percentage of measurements out of specification, based on the mean, standard deviation, and distribution type.

Samples

A “sample” is the total number of transactions used in the calculation(s) for the current operation.

Samples Out Spec

This displays number of transactions used in the calculation(s) which are out of tolerance for the current operation.

Samples In Spec

This displays number of transactions used in the calculation(s) which are inside the tolerance for the current operation.

In Control

Indicates by Y or N whether all selected AT&T Tests were passed successfully.

PpK Capable

Indicates by Y or N whether or not the process is capable in relation to the PpK.

See "Calculations of Capability Based on Normal Distribution Parameters".

Cpk Capable

`Cpk = MINIMUM(CpU, CpL)`

For one-sided measurements like flatness, `Cpk = CpU`

Actual capability index, based on subgroup size and the current control chart’s standard deviation. (For calculations of standard deviations for control charts, see Estimates of Standard Deviation Based on Control Charts.)

Cpk is a measure of how many 3 sigma half curves will fit between the process center and the closest specification limit. A value of 1.33 (i.e., the center is 4 sigma away from specification limits) or greater is a typical target.

See "Capability Indexes: Table of Calculations" and "Estimates of Standard Deviation Based on Control Charts".

25th Quartile

Twenty-five percent quartile value. This is the point midway between the median and the lowest value. 25% of all data points fall below this value and 75% fall above.

Median

The middle point of a set of data values. When used with subgroups, the median is the middle point of the subgroup values. Exactly 50% of the values are higher than the median and 50% of the values are lower. For sets containing an odd number of members, the exact middle value is used. For sets containing an even number of values the median is the average of the two middle results.

75th Quartile

Seventy-five percent quartile value. This is the point midway between the median and the highest value. 75% of all data points fall below this value and 25% fall above.

Range

The difference between the highest measurement value and the lowest measurement value in the sample.

Skewness

A distribution statistic that provides a measure of asymmetry. Negative values indicate data is skewed to the left (there are more values that are less than the mean than values that are greater than the mean). Positive values indicate data is skewed to the right (there are more values that are greater than the mean). A skewness of 0 indicates that the data is perfectly symmetrical.

Kurtosis

A distribution statistic that provides a measure of the flatness of the distribution curve as compared to normal data. Negative values indicate data is flatter than normal data. Positive values indicate data is steeper than normal data.

Upper Tol

The highest amount of acceptable deviation from the nominal.

Lower Tol

The lowest amount of acceptable deviation from the nominal. The lower tolerance should always be less than the upper tolerance. DataPage+ calculates specification limits by using the following equations:

`LSL = Nomi\nal + Lower\ Tol\erance`

`USL = Nomi\nal + Upper\ Tol\erance`

The lower tolerance should be negative so that its value is less than the nominal.

High Deviation and Low Deviation

The High Deviation is the largest deviation based on your selected transactions, while the Low Deviation is the smallest. For example, if you selected three transactions with deviations of 0.01, 0.02, 0.03, then High Deviation is 0.03 and Low Deviation is 0.01. The software calculates the range by the following:

`Rang\e = High\ Deviation – Low\ Deviation`

The range is an absolute number. For example, if you had a negative number, such as in a High Deviation of 0.05 and a Low Deviation of -0.06, the range would still be 0.11.

ChartView

Displays either a Bar-Whisker Chart or a Run Chart for each feature variable. See "Changing the Chart View Column".