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Statistical process control and capability: Cp, Cpk, Pp and Ppk (also for non-normal data), Xbar-R, Xbar-S, I-MR, P, NP, C, U, Laney, EWMA and CUSUM control charts with tests 1 to 8, attribute capability (% defective, DPU, Z and PPM), G and T charts for rare events and the multi-vari chart with run chart; shortcuts to the histogram and the simple run chart.
Paste measurements (single column, subgroups or ID) or enter mean and standard deviation: Cp, CPL, CPU, Cpk, Pp, Ppk, Cpm with 95% CI, observed and expected PPM, Z.Bench, control charts, Box-Cox, Johnson, Weibull and lognormal, and the payoff of reducing variation.
Cp, Cpk, PPM, sigma levelShows whether a process is stable over time, separating normal variation from signals that something changed and needs investigating. Paste measurements to build Xbar-R, Xbar-S, I-MR, I-MR-R/S, P, NP, C, U, Laney P′/U′, EWMA or CUSUM charts with tests 1 to 8, stages, historical limits, unequal subgroups and the within sigma for Cpk.
X̄-R, I-MR, P, U, EWMA, tests 1–8Measures process capability when the result is not a measurement but good/bad parts or a number of defects. For pass/fail characteristics or defect counts: paste the samples and get % defective or DPU with an exact confidence interval, PPM, process Z, P or U chart with tests, cumulative plot with confidence bounds, rate × sample size, histogram, report card and how many more parts to inspect to prove the target.
% defective, Z, DPUTracks whether rare defects, breakdowns or accidents are becoming more or less frequent by measuring the interval between them. For rare events, where a P or U chart would show almost only zeros: paste the event dates or the amounts between them and get the G (geometric) or T (Weibull or exponential) chart with probability limits, tests for special causes, cumulative events against expected, distribution fit, report card and annual cost.
Time between rare eventsHelps find where the variation of a measurement comes from before hunting for the cause. Paste measurements with up to 4 factors (position on the part, part, hour, shift) and see the multi-vari chart with means connected by level and each family’s share of the variation; or analyze data order on the run chart, with clustering, mixtures, trend and oscillation tests.
Families of variation, run chartA histogram shows how the measurements of one characteristic are spread: where the center is, how much they vary and whether they fit within the specification limits. It is the first tool to understand a process before computing Cpk or changing settings. Paste measurements from Excel and get a histogram with automatic or adjustable bins, normal curve, mean and ±3s, specification limits with % out, a dot plot for small samples, overlaid, stacked or paneled groups, a plain-language reading of the shape and a frequency table.
Shape, bins, % outA run chart shows a measure over time and answers whether it really changed or just wobbled by chance, without advanced statistics. It is the simplest way to prove whether an improvement worked. Paste a measure in time order (daily scrap, setup time, complaints per week) and the page draws the run chart with the median, goal and limits, highlights shifts of 6 or more points and trends of 5 or more by itself and counts the runs with the Provost and Murray table, explaining each signal in plain language.
Median, shifts, trendsImportant notice: Indus Metrics tools produce estimates and pre-sizing results from the data you enter and from published engineering methods. They do not replace design, calculations or reports signed by a licensed professional engineer (PE), nor verification against the applicable codes, standards and regulations, such as OSHA rules and the ASME codes. Material and fuel properties vary: check manufacturer data or your own process analyses before deciding. By using this site you agree to the Terms of Use.
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