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Measurement System Analysis (MSA / Gage R&R)

Assess your measurement system with the three standard MSA procedures: Type 1 as a Cg/Cgk study on a reference standard, Type 2 as a Gage R&R with appraiser influence and Type 3 as an automated study without an appraiser. On top comes the full measurement uncertainty budget per VDA 5 / ISO 22514-7 (Q_MS/Q_MP) as its own procedure. Paste measurement series straight from Excel, enter the tolerance and get the capability indices with a traffic-light rating - switchable between the AIAG, VDA 5 and ISO 22514-7 evaluation worlds, live with every input.

Calculation

A calibrated standard is measured repeatedly many times. Rated are the repeatability (Cg), the systematic deviation (bias, contained in Cgk) and the resolution (%RE). Use: release a new gauge, caliper or sensor. Capable from Cg ≥ 1.33 and Cgk ≥ 1.33 at %RE ≤ 5 %.

Cg/Cgk is defined identically in all assessment frameworks (AIAG, VDA 5, ISO 22514-7); the adjustable parameters are the spread L and the tolerance fraction p. The choice of framework takes effect for gage R&R (types 2 and 3).

Measurements

Paste values from Excel (one measurement per row or column). Decimal comma and point allowed. The Tab key inserts a tab character directly.

Parameters

Model: Gage R&R either by the average-range method (ARM, K constants per AIAG) or by ANOVA (two-way analysis of variance with interaction, pooling at p ≥ 0.25). Type 1 follows the Cg/Cgk convention (Bosch booklet 10 / VDA 5), with L switchable between ±3s and ±2s. All verdicts are relative to the entered tolerance; without a tolerance the tolerance-based metrics are omitted. The full VDA 5 / ISO 22514-7 uncertainty budget (Q_MS/Q_MP) is included as its own procedure. A sizing and rating tool, not a substitute for a normative capability proof per IATF 16949 / PPAP.

Results

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Formulas and fundamentals

Type 1: gauge capability (Cg/Cgk)

Type 1 (gauge capability) evaluates repeated measurements of a calibrated standard against a share of the tolerance. From the mean x_barg and the sample standard deviation sg (with n−1) of the n repeated measurements follow the pure-scatter capability index and the index reduced by the magnitude of the systematic deviation:

Cg = (p·T)/(L·sg) Cgk = ((p/2)·T − |bias|)/((L/2)·sg) bias = x_barg − x_m

The tolerance share p is typically 0.20, the reference convention L selects between ±3s (L = 6, DE/Bosch/VDA default, 99.73 %) and ±2s (L = 4). In addition the resolution (requirement ≤ 5 %) is checked and a two-sided t-test with n−1 degrees of freedom decides whether the systematic deviation is significant:

%RE = RE/T·100 t = |bias|/(sg/√n)

Types 2 and 3: Gage R&R (average-range method)

Type 2 (Gage R&R with appraiser) splits the total variation by the average-range method into repeatability and reproducibility. From the mean range R_bar follows the equipment variation, from the range of appraiser means X_DIFF the reproducibility, together the measurement-system variation:

EV = R_bar·K1 AV = √((X_DIFF·K2)² − EV²/(n·r)) GRR = √(EV² + AV²)

The part variation follows from the range of part means Rp, the total variation is:

PV = Rp·K3 TV = √(GRR² + PV²)

The K factors are reciprocals of the constants d2 and d2* and depend on the number of measurements r, appraisers k and parts n. In Type 3 the appraiser term drops out:

AV = 0 GRR = EV

Types 2 and 3: Gage R&R by ANOVA

Alternatively, the two-way analysis of variance (ANOVA) decomposes the variation via sums of squares and additionally detects the part × appraiser interaction. With n parts, k appraisers and r repetitions the sums of squares and mean squares are:

SS_total = SS_part + SS_appraiser + SS_int + SS_rep MS = SS/df

The variance components follow from the mean squares; a non-significant interaction (F test, p ≥ 0.25) is pooled into repeatability per the AIAG convention:

s²_rep = MS_rep s²_int = (MS_int − MS_rep)/r s²_appraiser = (MS_appraiser − MS_int)/(n·r) s²_part = (MS_part − MS_int)/(k·r)

This yields the same variation components as the average-range method, but statistically more efficient:

EV = √(s²_rep) AV = √(s²_appraiser + s²_int) GRR = √(EV² + AV²) PV = √(s²_part)

For Type 3 the model reduces to the one-way ANOVA across the parts: EV = √(MS_within) and s²_part = (MS_between − MS_within)/r. The rating via %GRR, %Contribution and ndc is identical for both methods; the method is switchable per study in the calculator.

Rating: %GRR, %Contribution and ndc

The rating uses the ratio of measurement variation to total variation or to the tolerance:

%GRR (study variation) = 100·GRR/TV %GRR (tolerance) = 100·(6·GRR)/T %Contribution = 100·GRR²/TV²

%Contribution works with variance shares and sums with the other sources to 100 %. The resolution gives the number of distinct categories (truncated, not rounded):

ndc = trunc(1.41·PV/GRR)

A measurement system is capable at %GRR ≤ 10 %, conditionally capable up to 30 %, above that not capable; additionally ndc ≥ 5 is required.

Worked example

All sample data sets of the calculator describe the same part: a bolt diameter Ø 10 ±0.1 mm, that is T = 0.20 mm with USL 10.1 mm and LSL 9.9 mm, measured with a micrometer of 0.001 mm display increment. The same bolt is assessed from four angles: against the setting standard (type 1), by three appraisers by hand (type 2), on an optical measuring cell without an operator (type 3) and as a complete uncertainty budget (VDA 5 budget). The figures below appear as soon as you click Load sample data in the calculator.

Type 1: The micrometer measures the setting standard x_m = 10.000 mm 25 times, tolerance T = 0.20 mm, resolution RE = 0.001 mm, L = 6, p = 0.20. From x_barg = 10.00016 mm and sg = 0.001106 mm follow bias = 0.00016 mm, Cg = (0.2·0.20)/(6·0.001106) = 6.03 and Cgk = (0.1·0.20 − 0.00016)/(3·0.001106) = 5.98. The resolution is sufficient at %RE = 0.5 %; the bias t-value 0.72 stays below the critical value 2.06 (n − 1 = 24 degrees of freedom), so the systematic deviation of 0.16 µm is not significant and needs no correction. The gauge is capable by a wide margin: the repeatability spread amounts to about one display increment, and the assigned spread 0.2·T = 0.04 mm is roughly six times 6·sg.

Type 2: Ten of these bolts are measured three times each by three appraisers with the same micrometer. This gives R_bar = 0.00223 mm, X_DIFF = 0.00180 mm and Rp = 0.09578 mm; with K1 = 0.5908, K2 = 0.5231 and K3 = 0.3146 the components are EV = 0.00132 mm, AV = 0.00091 mm, GRR = 0.00160 mm, PV = 0.03013 mm and TV = 0.03017 mm. That yields %GRR (study var) = 5.3 %, %GRR (tolerance) = 4.8 % and ndc = 26, so the measurement system is capable. At %EV = 4.4 % against %AV = 3.0 % the repeatability dominates slightly; the appraiser influence is present but small. Switched to ANOVA the result is 5.2 % (study var), 4.9 % (tolerance) and ndc = 26; the appraiser × part interaction is not significant at p = 0.289 and is pooled into the repeatability.

Type 3: The same ten bolts pass three times through an optical measuring cell, without an operator. Without an appraiser share GRR = EV = 0.00112 mm, together with PV = 0.02999 mm and TV = 0.03001 mm, hence %GRR (study var) = 3.7 %, %GRR (tolerance) = 3.4 % and ndc = 37; ANOVA gives 3.5 %, 3.3 % and ndc = 39. The cell separates the bolts far better than the manual station because the appraiser share is gone: a typical result for optical or fully automatic measuring cells.

VDA 5 budget: For the same bolt the uncertainty budget of the manual measuring station is drawn up, T = 0.20 mm and k = 2. The measurement system contributes the calibration certificate U_CAL = 0.002 mm (u = U_CAL/2 = 0.001 mm), the resolution RE = 0.001 mm (u = RE/√12 = 0.000289 mm), the repeatability at the standard u_EVR = 0.003 mm and an uncorrected bias of 0.001 mm (u = |bias|/√3 = 0.000577 mm). Summed in quadrature these give u_MS = 0.00323 mm, U_MS = 0.00645 mm and Q_MS = 2·U_MS/T = 6.5 % against the 15 % limit. The measurement process adds the object influence u_OBJ = 0.002 mm and the temperature u_T = 0.001 mm: u_MP = 0.00393 mm, U_MP = 0.00785 mm and Q_MP = 7.9 % against the 30 % limit. Both figures sit well inside the green range; the largest single contribution is u_EVR, the repeatability, not the calibration certificate. The budget is set with a reserve: u_EVR = 0.003 mm and the bias of 0.001 mm lie above the values measured in type 1, sg = 0.001106 mm and 0.00016 mm. The Import type-1 study button replaces the assumption with the measured values.

Frequently asked questions

When do I use Type 1, 2 or 3?

Type 1 (Cg/Cgk) releases a new gauge: many repeated measurements of a calibrated standard, rating scatter, systematic deviation and resolution. Type 2 (Gage R&R) secures a manual measuring station operated by several appraisers - the operator is a separate source of variation. Type 3 is for measurements without a human operator (optical inspection, camera, laser, automatic cell); the appraiser term drops out while the real repeatability including handling is captured. The VDA 5 budget complements the three types with the standards-compliant measurement uncertainty view per VDA 5 / ISO 22514-7 (Q_MS/Q_MP), typical for approvals in the automotive world.

What do Cg and Cgk mean?

Cg rates only the gauge repeatability against an assigned share of the tolerance (typically 20 %). Cgk additionally subtracts the magnitude of the systematic deviation (bias) and is therefore always less than or equal to Cg. The gauge is capable from Cg ≥ 1.33 and Cgk ≥ 1.33. A large bias pushes Cgk below Cg - a correction or re-adjustment of the gauge then helps.

How do %GRR (study var), %tolerance and %contribution differ?

%GRR (study var) relates the measurement variation to the observed total variation TV and is the classic AIAG headline metric. %Tolerance (P/T) relates the same measurement variation to the tolerance and is decisive under VDA 5 and ISO 22514-7. %Contribution works with variances (squares) and sums over all sources to 100 %. These are three different numbers - the calculator reports all three separately so nothing gets mixed up.

What does the ndc value tell me?

ndc (number of distinct categories) is the number of classes the measurement system can reliably distinguish within the part variation: ndc = trunc(1.41·PV/GRR). From ndc ≥ 5 the resolving power is considered sufficient. A low ndc means the measurement variation is too large relative to the part variation to tell parts apart reliably. The value is truncated, not rounded.

How do AIAG, VDA 5 and ISO 22514-7 differ?

AIAG rates the observed variation directly (Cg/Cgk, %GRR against the total variation, ndc). VDA 5 and the equivalent ISO 22514-7 instead rate the measurement uncertainty against the tolerance and separate measurement system (Q_MS, laboratory conditions) from measurement process (Q_MP, real conditions). In Types 1 to 3 the calculator shows the tolerance-based metric as the headline under the VDA/ISO view; the full Q_MS/Q_MP uncertainty budget is available in the calculator as its own procedure (VDA 5 budget).

How do ARM and ANOVA differ for Gage R&R?

The average-range method (ARM) estimates the variance components via ranges and K constants - easy to verify by hand and the classic of the AIAG worksheets. ANOVA (analysis of variance) decomposes the variation via sums of squares, additionally detects the appraiser × part interaction and uses the data more efficiently; it is the method preferred by AIAG and standard in Minitab. If the interaction is not significant (p ≥ 0.25) it is pooled into repeatability. Both methods are switchable in the calculator and give very similar %GRR values for well-behaved data.

How do I enter the measured values?

Fastest via copy-paste from Excel: copy the range, click into the measurement matrix and paste - the table fills from the focused cell onwards, decimal comma and decimal point are both accepted. Within the matrix, Tab jumps to the next cell and Enter to the next row of the same column; each row is one part, the columns are grouped by appraiser (type 2) or the trials M1 to Mr (type 3). Row + and row − adjust the number of parts, load sample data fills in a reference data set, and clear values empties all cells while keeping the rows for your own input. For type 1 a simple list of values is sufficient.

How does the VDA 5 budget work and where do the contributions come from?

The budget sums standard uncertainties in quadrature: u_MS from the system contributions (calibration, resolution, repeatability on the standard, bias), u_MP additionally from the process contributions (repeatability on the object, appraiser influence, temperature, object influence). With the coverage factor k = 2 follow U_MS and U_MP, rated as Q_MS = 2·U_MS/T with a 15 % limit and Q_MP = 2·U_MP/T with a 30 % limit. Contributions can be entered directly as u or derived from raw quantities (resolution RE/√12, uncorrected bias |bias|/√3, calibration certificate U_CAL/2). Quickest is the one-click import from the other tabs: the type-1 study provides u_EVR and u_BI, the gage R&R study provides u_EVO and u_AV - using whichever evaluation method is selected. With ANOVA, u_AV already contains the part × appraiser interaction; a separate interaction row would double-count it.

Why does the assessment framework not change the type-1 result?

Cg and Cgk are defined identically in AIAG, VDA 5 and ISO 22514-7 - the adjustable parameters are the spread L (usually 6, i.e. ±3s) and the tolerance fraction p (usually 0.20), both selectable directly in the form. That is why the calculator does not even show the framework switch for type 1. For gage R&R (types 2 and 3) the choice matters visibly: AIAG leads with %GRR relative to the total study variation, VDA 5 and ISO 22514-7 lead with the tolerance-based ratio.

What does the report PDF contain?

Everything needed for an auditable record: the verdict with its standard reference, all characteristic values, the traffic-light rating against the limits, every chart from the web page (run chart and histogram for type 1; R and X-bar chart with visible measurement points, variation by appraiser or part, interaction chart and ANOVA table for types 2 and 3; Q_MS/Q_MP utilisation for the VDA 5 budget) plus the complete raw data: the list of measured values, the measurement matrix per part and appraiser, or the full uncertainty budget. Header data such as project, component and inspector come from the export form; the PDF is available in German and English.

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