Potential Capability Variables

 These variables are within-subgroup capability indices. The calculations are based on the variation within subgroups, so the values depend on the defined subgroup structure. The values also change if the subgroup definition changes.

These variables are always calculated using the Normal Distribution method and are not effected by the Non-Parametric Statistics flag in any way.

Cp/Cp2

Capability or potential of the process. A ratio of the specification width to the width of the normal distribution. Cp is normally calculated using an estimated standard deviation formula that uses either the mean of subgroup ranges or the mean of subgroup standard deviations with constant table values relative to the subgroup size.

~cp~

Returns Cp calculated on Tol (Tolerance).

~cp2~

Returns Cp calculated on Tol2 (Tolerance 2).

~process,cp~

Capability or potential of the process baseline. The ratio of the specification width to the width of the normal distribution. Cp is normally calculated using an estimated standard deviation formula that uses either the mean of subgroup ranges or the mean of subgroup standard deviations with constant table values relative to the subgroup size.

Cpk/Cpk2

Capability of process index relative to dispersion and centeredness. From the true process center (), Cpk indicates the closest specification limit (in terms of estimated standard deviation units/3).

~cpk~

Returns Cpk calculated on Tol (Tolerance).

~cpk2~

Returns Cpk calculated on Tol2 (Tolerance 2).

~process,cpk~

Capability of the process baseline index relative to dispersion and centeredness. From the true process center (), Cpk indicates the closest specification limit (in terms of estimated standard deviation units/3).

Cr

~cr~

Capability ratio. The reciprocal of Cp.

~process,cr~

Capability ratio using the process baseline. The reciprocal of Cp.

Cpm

~cpm~

Capability of process index influenced by the difference between the sample mean and the nominal target value.

~process,cpm~

Capability of the process baseline index influenced by the difference between the sample mean and the nominal target value.

Overall Capability Variables

Overall capability measures process performance using all available data. This means that calculations are done using all valid sample data within a DataSet. Subgroups are not considered.

Variables to resolve Non-Parametric statistics are differentiated from the same variables which resolve statistics for data using the Normal Distribution method. Process capability variables are grouped according to how their statistical calculation methods are determined:

  • Values Affected by the Non-Parametric Statistics Flag (NPS) - These variables use either the Normal Distribution or the Non-Parametric calculation method, based on the value of the Non-Parametric Statistics flag.
  • Normal Distribution (ND) Variables - These variables always use the Normal Distribution calculation method, regardless of the NPS flag setting.
  • Non-Parametric (ISO) Variables - These variables always use the Non-Parametric calculation method, regardless of the NPS flag setting.
Method Based on NPS Flag Normal Distribution (ND) Non-Parametric (ISO)
~Pp~ ~Pp,Nd~ ~Pp,Iso~
~Ppk~ ~Ppk,Nd~ ~Ppk,Iso~
~Ppu~ ~Ppu,Nd~ ~Ppu,Iso~
~Ppl~ ~Ppl,Nd~ ~Ppl,Iso~
~Process,Pp~ ~Process,Pp,Nd~ ~Process,Pp,Iso~
~Process,Ppk~ ~Process,Ppk,Nd~ ~Process,Ppk,Iso~
~Process,Ppu~ ~Process,Ppu,Nd~ ~Process,Ppu,Iso~
~Process,Ppl~ ~Process,Ppl,Nd~ ~Process,Ppl,Iso~
    ~Pisol~
    ~Pisou~
    ~SpreadIso~

For more information on the NPS Flag, see the topic Non-Parametric Statistics.

Pp/Pp2

Performance index relative to dispersion of the process. A ratio of the specification width to the width of the normal distribution. Pp is calculated using calculated or sample population standard deviation.

~pp~

Returns Pp calculated on Tol (Tolerance). The calculation method is determined by the Non-Parametric Statistics flag.

~pp2~

Returns Pp calculated on Tol2 (Tolerance 2).

~pp,iso~

Returns Pp calculated with the Non-Parametric method on Tol (Tolerance).

~pp,nd~

Returns Pp calculated with the Normal Distribution method on Tol (Tolerance).

~process,pp~

The performance index relative to dispersion of the process baseline. A ratio of the specification width to the width of the normal distribution. Pp is calculated using calculated or sample population standard deviation. The calculation method is determined by the Non-Parametric Statistics flag.

~process,pp,iso~

Returns Pp of the process baseline calculated with the Non-Parametric method on Tol (Tolerance).

~process,pp,nd~

Returns Pp of the process baseline calculated with the Normal Distribution method on Tol (Tolerance).

Ppk/Ppk2

Performance index relative to dispersion and centeredness of the process. Ppk is calculated using calculated or sample population standard deviation.

~ppk~

Returns Ppk calculated on Tol (Tolerance). The calculation method is determined by the Non-Parametric Statistics flag.

~ppk2~

Returns Ppk calculated on Tol2 (Tolerance 2).

~ppk,iso~

Returns Ppk calculated with the Non-Parametric method on Tol (Tolerance).

~ppk,nd~

Returns Ppk calculated with the Normal Distribution method on Tol (Tolerance).

~process,ppk~

The performance index relative to dispersion and centeredness of the process baseline. Ppk is calculated using calculated or sample population standard deviation. The calculation method is determined by the Non-Parametric Statistics flag.

~process,ppk,iso~

Returns Ppk of the process baseline calculated with the Non-Parametric method on Tol (Tolerance).

~process,ppk,nd~

Returns Ppk of the process baseline calculated with the Normal Distribution method on Tol (Tolerance).

Ppl

One-sided performance index of the process calculating the distance from the process mean to the Lower Spec Limit.

~ppl~

Returns Ppl calculated on Tol (Tolerance). The calculation method is determined by the Non-Parametric Statistics flag.

~ppl2~

Returns Ppl calculated on Tol2 (Tolerance 2).

~ppl,iso~

Returns Ppl calculated with the Non-Parametric method on Tol (Tolerance).

~ppl,nd~

Returns Ppl calculated with the Normal Distribution method on Tol (Tolerance).

~process,ppl~

One-sided performance index of the process baseline, calculating the distance from the process mean to the Lower Spec Limit. The calculation method is determined by the Non-Parametric Statistics flag.

~process,ppl,iso~

Returns Ppl of the process baseline calculated with the Non-Parametric method on Tol (Tolerance).

~process,ppl,nd~

Returns Ppl of the process baseline calculated with the Normal Distribution method on Tol (Tolerance).

Ppu

One-sided process performance capability index calculating the distance from the process mean to the Upper Spec Limit.

~ppu~

Returns Ppu calculated on Tol (Tolerance). The calculation method is determined by the Non-Parametric Statistics flag.

~ppu2~

Returns Ppu calculated on Tol2 (Tolerance 2).

~ppu,iso~

Returns Ppu calculated with the Non-Parametric method on Tol (Tolerance).

~ppu,nd~

Returns Ppu calculated with the Normal Distribution method on Tol (Tolerance).

~process,ppu~

One-sided performance index of the process baseline, calculating the distance from the process mean to the Upper Spec Limit. The calculation method is determined by the Non-Parametric Statistics flag.

~process,ppu,iso~

Returns Ppu of the process baseline calculated with the Non-Parametric method on Tol (Tolerance).

~process,ppu,nd~

Returns Ppu of the process baseline calculated with the Normal Distribution method on Tol (Tolerance).

Pr

~pr~

Process performance ratio. The reciprocal of pp.

PisoL/PisoU

~pisol~

The Lower Percentiles of the specified distribution for Non-Parametric calculations.

  • PisoL = P0.0135 = 0.0135th percentile of the process data

~pisou~

The Upper Percentiles of the specified distribution for Non-Parametric calculations.

  • PisoU = P99.865 = 99.865th percentile of the process data

SpreadISO

~spreadiso~

The difference between the Upper and Lower percentiles (PisoU - PisoL).

  • SpreadISO = P99.865 - P0.0135

Level Analysis Variables

The Sigma level variables are shown as Cpk, but can be used for either Cpk or Ppk level analyses. See here for information about the DataStack Level Analysis.

Sigma Level Numbers

~cpkALevel~

Returns the 6 Sigma level (0-6) for Cpk.

~cpkBLevel~

Returns the 6 Sigma level (2-4) for Cpk.

~cpk2ALevel~

Returns the 6 Sigma level (0-6) for Cpk2.

~cpk2BLevel~

Returns the 6 Sigma level (2-4) for Cpk2.

Sigma Level Values

~cpkALevel,[0-6]~3

Returns the 6 Sigma level (0-6) for Cpk.

~cpkAlevel,0~

  - Cpk < 0.33

~cpkAlevel,1~

  - Cpk >= 0.33, < 0.67

~cpkAlevel,2~

  - Cpk >= 0.67, < 1.00

~cpkAlevel,3~

  - Cpk >= 1.00, < 1.33

~cpkAlevel,4~

  - Cpk >= 1.33, < 1.67

~cpkAlevel,5~

  - Cpk >= 1.67, < 2.00

~cpkAlevel,6~

  - Cpk >= 2.00

~cpkBLevel,[2-4]~

Returns the 6 Sigma level (2-4) for Cpk.

~cpkBlevel,2~

  - Cpk >=  < 1.00

~cpkBlevel,3~

  - Cpk >= 1.00, < 1.33

~cpkBlevel,4~

  - Cpk >= 1.33

~cpk2ALevel,[0-6]~

Returns the 6 Sigma level (0-6) for Cpk2.

~cpk2Alevel,0~

  - Cpk < 0.33

~cpk2Alevel,1~

  - Cpk >= 0.33, < 0.67

~cpk2Alevel,2~

  - Cpk >= 0.67, < 1.00

~cpk2Alevel,3~

  - Cpk >= 1.00, < 1.33

~cpk2Alevel,4~

  - Cpk >= 1.33, < 1.67

~cpk2Alevel,5~

  - Cpk >= 1.67, < 2.00

~cpk2Alevel,6~

  - Cpk >= 2.00

~cpk2BLevel,[2-4]~

Returns the 6 Sigma level (2-4) for Cpk2.

~cpk2Blevel,2~

  - Cpk >= < 1.00

~cpk2Blevel,3~

  - Cpk >= 1.00, < 1.33

~cpk2Blevel,4~

  - Cpk >= 1.33

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