mqr.process.

Capability#

class mqr.process.Capability(sample: Sample, spec: Specification)#

Process capability values.

Attributes:
sampleSample

Sample that has this capability.

specSpecification

Specification for which sample has this capability.

cpfloat

Process potential. The capability of the process if it was centred at Specification.target.

cpkfloat

Process capability. The number of standard deviations of process variation that fit in the specification, normalised by 3*sigma. Ie. a 6-sigma process has capability 2.0.

defects_stfloat

Short-term defect rate, based on a fitted normal distribution.

defects_ltfloat

Long-term defect rate, based on a normal distribution with 1.5*stddev larger than short-term.

Examples

Construct this object with a sample and a mqr.process.Specification:

data = pd.read_csv(mqr.sample_data('study-random-5x5.csv'))
summary = mqr.process.Summary(data['KPI1'])
spec = mqr.process.Specification(150, 147, 153)
mqr.process.Capability(summary['KPI1'], spec)

In a jupyter notebook, this produces the HTML table below. Iterables of Capability are shown as the same table with multiple columns.

KPI1

USL

Target

LSL

Cpk

0.844

Cp

0.852

Defectsst (ppm)

1.06e+04

Defectslt (ppm)

8.83e+04
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