SPCVisualsFree SPC tools
The calculations quality engineers do every week, on a page instead of in a spreadsheet. No signup, no email, nothing you paste is stored — and the maths is the same tested engine that draws the charts in the product.
Capability
Cp / Cpk calculator
Paste measurements — or type a mean and a sigma — with your tolerance, and get Cp, Cpk, Pp, Ppk, the sigma level and the expected parts per million out of spec.
Open →Cpk confidence interval & sample size
A Cpk of 1.33 from 30 pieces has a 95% interval of roughly 0.97 to 1.69. See the uncertainty in your own number, and how many parts would settle it.
Open →Cpk ↔ PPM ↔ sigma level converter
What PPM is a Cpk of 1.33? What Cpk does 3.4 PPM need? Both conventions shown side by side, because the 1.5 sigma shift is why two sources disagree by a factor of ten.
Open →Control charts
Control limit calculator
Give it subgroups or individual readings and it returns the control limits for the chart, the range or sigma chart beneath it, and every constant it used to get there.
Open →Control chart generator
Paste a column of numbers, or rows of subgroups, and get a real control chart: limits from the data, Nelson rules 1–4 evaluated, out-of-control points marked.
Open →Nelson & Western Electric rules checker
Every run rule evaluated on your data, each violation named in plain English with what it usually indicates — a shift, a trend, tool wear, two machines mixed.
Open →X̄-R chart calculator
Subgroups in, X̄ and R charts out — limits from A₂, D₃ and D₄, run rules evaluated, and the range chart shown first because it decides whether the averages chart can be trusted.
Open →X̄-s chart calculator
For subgroups big enough that the range wastes them. Limits from A₃, B₃ and B₄, sigma recovered with the c₄ correction, and the s chart read first because it decides whether the averages chart can be trusted.
Open →I-MR chart calculator
For processes that give you one number at a time — a batch, an oven, a destructive test. Limits from the mean moving range, run rules evaluated, and an honest note about what an individuals chart cannot see.
Open →p, np, u and c chart calculator
Counted data rather than measured: proportion defective, number defective, defects per unit. Limits that step with the sample size instead of pretending it never changed, and an honest warning when the counts are too low for three-sigma limits to mean anything.
Open →Reference
Laboratory
Levey-Jennings chart with Westgard rules
Paste your QC results with the assigned mean and SD from the package insert, and get the chart with every sigma band drawn and all six Westgard rules evaluated — each one named, and labelled random or systematic error.
Open →Bland-Altman plot
Paired readings from two methods, plotted as difference against average — with the bias, the limits of agreement, their confidence intervals, and a test for whether the disagreement depends on the magnitude.
Open →Quality tools
Pareto chart generator
Categories and counts in, ranked bars and the cumulative line out — with the vital few named, an "Other" bucket that always sorts last, and an honest warning when the distribution is flat and there is no dominant cause to attack.
Open →Box and whisker plot generator
One column per group, boxes side by side. Quartiles, the 1.5×IQR fences, whiskers that stop at real readings and outliers drawn individually — with the quartile method stated, because that is why your plot and Excel's disagree.
Open →Histogram and normality test
A histogram with the fitted normal curve, both standard bin rules with a reasoned recommendation, and an Anderson-Darling test that refuses to tell you your data is normal — because no test can.
Open →Measurement systems
Analysis
Grubbs outlier test
The G statistic against its critical value, the p-value, and the point implicated — plus a straight answer about what to do next, which is almost never to delete the reading.
Open →Scatter diagram and correlation
Paired readings plotted, with Pearson r, Spearman rho, r², the least-squares line and its p-value — and the two reported together, because when they disagree the disagreement is the finding.
Open →Standard deviation calculator
The usual summary statistics, and the thing a spreadsheet will not tell you: the within-subgroup sigma a control chart uses, beside the overall sigma a textbook means. The gap between them is why Cpk and Ppk disagree.
Open →What these calculators are, and what they are not
Each tool on this page runs one calculation properly and shows its working. Paste a column of readings, get the answer, close the tab. Nothing is stored, nothing is emailed to you, and there is no step where the result is held back until you register. That is not a growth tactic being generous — it is the only way a calculator is actually useful to somebody who has a number in front of them right now.
The arithmetic is the same tested engine that draws the charts inside the product, so a Cpk computed here and a Cpk computed on a live chart will not disagree. What they will not do is watch anything. A calculator answers a question at the moment you ask it. It has no memory of the last run, no opinion about whether the process has drifted since, and no way to tell anyone that it has.
Picking the right one
- You have readings and want to know if the process is behaving. Start at the control chart generator, or go straight to X̄-R for subgroups and I-MR for single readings.
- You have a specification and want to know if you can hold it. That is capability, not control — the Cp/Cpk calculator. Run the control chart first: a capability number computed on an unstable process is a number about nothing.
- You suspect the gauge, not the process. The Gage R&R calculator runs the full ANOVA study, interaction term included.
- You are in a lab, not a plant. The Levey-Jennings chart takes its limits from the QC material's assigned mean and SD rather than from the run, and applies the Westgard rules.
The one mistake worth naming here
Control limits come from the process. Specification limits come from the drawing. They are not the same lines, they do not belong on the same axis, and putting the spec on a control chart is the single most common way to turn a working chart into a misleading one — it produces alarms when the process is fine and silence when it has shifted inside a wide tolerance. If only one thing from this page is worth carrying away, that is it, and this guide explains why.
Want the explanation rather than the calculator? The guides cover what each of these numbers means, and what it cannot tell you.
Want any of this to keep itself up to date from the line instead? See it running on live public data, or start now.