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MSA (Measurement System Analysis)

A measurement system analysis asks how much of the variation you see in your data comes from the parts and how much comes from the act of measuring them. It separates the two, and reports the measurement system's share as a set of components you can act on.

Find these tools on the ribbon at QXL Stat Tools > MSA / Gage R&R.

Start here: which study do you have?

The first choice is not a preference. It is a question about what physically happened when the measurements were taken, and there is one right answer for a given set of data.

The choice between a crossed and a nested study is not a preference. It is a question about what physically happened when the measurements were taken, and there is only one right answer for a given set of data:

Did every operator measure the same parts, or did each operator measure parts that no other operator touched?

If the same parts went to every operator, the study is crossed. If each operator had their own parts, it is nested. The usual reason for a nested study is that measuring destroys or changes the part, so the same part cannot be handed to a second operator.

Tool Use it when
Crossed every operator measured the same parts
Nested each operator measured their own parts, and no part was measured by more than one operator
Extended there is a factor besides part and operator, or nesting other than part within operator, or you need to set a factor as fixed, choose interactions by hand, or move a term's variation into part to part

If you have not collected the data yet, Create MSA Template builds a worksheet laid out for the study, with the columns and instructions already in place.

The four tools

Tool What it does
Create MSA Template Builds a blank data collection sheet for a study, sized to your number of operators, parts and replications
Crossed Analyses a study in which every operator measured every part
Nested Analyses a study in which parts are nested within operators
Extended Analyses any study the other two cannot express, with a Model tab for declaring factors, nesting and interactions

Crossed, Nested and Extended are the same dialog with different parts shown, so once you know one you know all three. What changes between them is covered on each tool's own page.

Crossed and nested, side by side

In a crossed study every operator measures every part. Part 1 that operator A measured is the same physical part 1 that operator B measured:

Part 1 ── measured by ── Operator A, Operator B, Operator C
Part 2 ── measured by ── Operator A, Operator B, Operator C
Part 3 ── measured by ── Operator A, Operator B, Operator C

Because the same part appears under more than one operator, two operators can be compared on the same part. That is what makes two things possible that a nested study cannot offer:

  • Reproducibility can be separated from part to part variation. A difference between operators measured on identical parts cannot be a difference between the parts.
  • An operator by part interaction can be estimated, which is the question of whether the operators disagree more about some parts than about others.

In a nested study each operator measures their own parts, and no part is measured by more than one operator. The parts are said to be nested within the operators:

Operator A
└ Part 1, Part 2, Part 3
Operator B
└ Part 4, Part 5, Part 6
Operator C
└ Part 7, Part 8, Part 9

The part labels matter here in a way they do not in a crossed study. A part label in a nested study identifies a part only within its own operator. If the sheet happens to label all three of operator A's parts 1, 2, 3 and all three of operator B's parts 1, 2, 3, those are still six different physical parts, and the analysis treats them as six. It reports the total number of distinct nested parts, which is why that count can be larger than the number of distinct labels in the column: three labels reused by three operators are reported as nine observed parts.

The consequence is that it does not matter how you label them. A nested part label is read as a position within its own operator rather than as a name, so labelling every operator's parts 1, 2, 3 and giving all nine parts their own distinct labels describe the same study and produce the same report. You do not need to invent globally unique part numbers to run a nested study.

Because no part is shared, no operator by part interaction term exists, and no interaction chart is drawn. That is not a setting; there is nothing for the term to measure.

The two layouts can look identical on the worksheet, because both are a measurement column, a part column and an operator column. What separates them is whether a part label appears under more than one operator.

Crossed Nested
the same part measured by several operators yes no
a part label means the same part everywhere yes no, only within its operator
operator by part interaction can be estimated does not exist
interaction chart drawn yes no
XbarR estimation method offered yes no
reason a study is usually run this way the ordinary case measuring destroys or changes the part

Choosing the wrong one is not caught by an error message in every case. The same numbers analysed both ways answer different questions, so the choice has to come from how the data were collected.

What the choice changes

The study type is not only a label. Four things follow from it:

Crossed Nested Extended
Model tab hidden hidden shown
Extended options hidden hidden shown
additional factor columns hidden hidden shown
confidence intervals reported reported none reported
misclassification sweep charts the two joint ones the two joint ones the two joint ones and probability the part is good
XbarR estimation method offered refused refused

The report names the study type at the top of the sheet and in the worksheet tab, so a finished report always says which of the three produced it.

What every study reports

Whichever tool you run, the report is laid out the same way, and anything your study did not produce is left out rather than shown empty.

Every sheet is laid out in the same order, top to bottom:

  1. User Input, and the Gage Info block beside it
  2. Stats Advisor
  3. Notes, when there are any
  4. the Gage R&R results table, with the confidence interval table below it
  5. the analysis of variance table, beside them
  6. Probabilities of Misclassification
  7. the charts, with the bias and linearity tables inside that band

Anything the study did not produce is left out, and the sheet closes up rather than leaving a gap.

The full description of every table and chart is on each tool's own page, and the mathematics behind every number is under MSA Math.

The mathematics

Page What it covers
Variance Components The model, the grouping rule, and the five aggregates every percentage is built from
Gage Evaluation Every reported column, the tolerance width, and the number of distinct categories
Expected Mean Squares The analysis of variance route to the components
Restricted Maximum Likelihood The route used for unbalanced data
XbarR Method The range based route, for crossed studies
Probabilities of Misclassification What the system does to accept and reject decisions
Bias and Linearity Whether the system reads correctly, not just consistently

Other MSA tools

The MSA / Gage R&R menu carries more tools below the four above: a Type 1 study, MSA Template (VBA), the older ANOVA and XbarR entries, two attribute methods for pass and fail data rather than measured values, and an update command. Those are from the previous version of Quantum XL and are not covered in this section.

Two commands on the menu make a template, and the one at the top is the one this section documents. Create MSA Template is the v18 tool, described on Create MSA Template. MSA Template (VBA) sits below the separator with the other previous-version commands and builds the sheet the old way. The v18 analyses read either sheet, so a template made by the older command still runs.