ơm = Gage Variation ơp = Part Variation ơt (Total Process Variation) = √(ơm2+ ơp2)
% GRR = 100 * ơm /Tolerance % % PV = 100 * ơp /Tolerance % ndc = 1.41 * PV/GRR If %GRR > 30%, gage needs to be replaced.
Cp = (USL-LSL)/(6 * ơ), with USL – LSL representing the Process Tolerance.
The first task at a measure stage is checking resolution.
The study needs to be explored because part variation is present.
The difference between Cpl and Cpu is called the Process Capability Index, or Cpk.
The project's best available scoping tool is SIPOC.
The sample size must be calculated scientifically using methods that account for standard deviation or the population's current error rate.
Process Performance is not a means of measuring a continuous data capability index.
The mean is not centered if Cpk > Cp. Mean is centered and process is accurate if Cpk = Cp.
Every measurable phenomenon is a statistical distribution according to SPC, or statistical process control, meaning that every set of observed data is a collection of effects from a set of unidentified common causes.
The most crucial item to complete before performing any Measure computations is process stability.
When sample sizes are variable and each sample could contain more than one instance of the specified condition, a U chart is acceptable. These control charts are the ones that handle attribute data the best.
A Master Appraiser is the title given to the process expert who rates the samples.
The standard deviation of averages, abbreviated SEM or Standard Error of Mean, is calculated by dividing the population's standard deviation by the square root of the sample size.
ơm = √(ơr2+ ơo2) where ơr = Repeatability or Equipment Variation ơo = Reproducibility or Appraiser Variation
