STATISTICA Process Analysis
Introduction
STATISTICA Process Analysis is a comprehensive package for process capability, Gage R&R, and other quality control/improvement applications.
STATISTICA Process Analysis is comprised of two modules which include comprehensive implementations of process capability analysis, gage repeatability and reproducibility analysis, Weibull analysis, sampling plans, and variance components for random effects.
Process capability analysis
Includes a comprehensive selection of options for computing process capability indices for grouped and ungrouped data (e.g., Cp, Cr, Cpk, Cpl, Cpu, K, Cpm, Pp, Pr, Ppk, Ppl, Ppu), normal/distribution-free tolerance limits, and corresponding process capability plots (histogram with process ranges, specification limits, normal curve). In addition, instead of these normal distribution indices and statistics, the user can choose estimates (e.g., Cpk, Cpl, Cpu based on the percentile method) based on general non-normal distributions (Johnson and Pearson curve fitting by moments), as well as all other common continuous distributions including the Beta, Exponential, Extreme Value (Type I, Gumbel), Gamma, Log-Normal, Rayleigh, and Weibull distributions. The program will compute maximum-likelihood parameter estimates for those distributions, and it provides numerous options for evaluating the fit of the respective distribution to the data, including the frequency distribution with observed and expected frequencies, the Kolmogorov-Smirnov d statistic, histograms, Probability-Probability (P-P) plots, and Quantile-Quantile (Q-Q) plots. An option is also available for automatically fitting all distributions, and choosing the distribution that best fits the data.