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Find which family holds the variation — within the part, part to part or over time — and whether the data sequence hides clusters, mixtures, trends or oscillation.
Pre-sizing and estimating tool: results do not replace design, calculations or reports signed by a licensed professional, nor verification against the applicable codes and standards.
Share of the total variation (sum of squares) explained by each factor, from the outermost to the innermost; the rest is repetition within the same combination.
The numbers behind the plotted points: N, mean, standard deviation, minimum and maximum.
Points in collection order with the median. Shaded band = longest run about the median; thick line = longest run up or down.
Bars below the α line indicate a non-random pattern. Log scale.
Runs about the median (clustering and mixtures) and up or down (trends and oscillation), with normal-approximation P-values.
Take this page’s results to another calculator with the fields already filled in.
The calculation report gathers this page's inputs, results, equations, assumptions and references, with fields for project, engineer and revision. The full report also includes the charts and interpretations, in color. In the print dialog, choose Save as PDF.
A chart that shows at once how a measurement changes within the part, from part to part and over time. Each point is the mean of a factor combination, and lines join the means of the same group. It helps decide which family of variation to investigate before running experiments.
Measure a few consecutive parts (3 to 5) at several positions (ends and center, for example) and repeat at several times (hourly, by shift) until you capture at least 80% of the normal process variation. Record one row per measurement with the position, part, time and value.
The page splits the total variation among the factors, from the outermost (hour, shift) to the innermost (position). In the shaft example, the hour-to-hour drift holds most of it: the problem is temporal, typical of tool wear or warm-up, rather than clamping or material.
No: it is a visual, descriptive tool with no P-value. Use it to choose where to look and then confirm with ANOVA or an experiment. The next-step button takes the same data to ANOVA.
Whether the order of the points looks random. It counts runs of points on the same side of the median (too few = clustering, too many = mixtures) and runs that only rise or only fall (too few = trend, too many = oscillation), with a P-value for each pattern.
The run chart uses no control limits; it detects order patterns even when all points are inside the limits. The control chart shows whether the process is stable relative to its natural variation. The two complement each other.
When several parts are measured at the same time (for example, 5 per hour), each subgroup becomes one point with its mean or median, and the tests look at the sequence of times. In the crankshaft example, 125 measurements form 25 subgroups of 5.
Important 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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