Quality Progress - September 2017 - 47

Differences between a standard and expanded GR&R study
include:
+ The expanded GR&R study allows additional factors to be
evaluated.
+ Interactions between the additional factors and the operator
and part also can be assessed.
+ The expanded GR&R study allows analysis of the data-even
if there are missing data points.
+ The data collection plan commonly is adjusted for the
expanded GR&R. Repeating the standard plan for each
additional factor is costly, so the number of parts is often
reduced. For example, five parts are to be measured by
three operators using three randomly selected gages, and
each operator will measure each part twice. Thus, the total
sample will be 5 × 3 × 3 × 2 = 90. In a standard GR&R study,
more parts can be selected, but this is an unacceptably large
sample size for expanded GR&R.
+ When there isn't enough data for a standard GR&R study, an
expanded GR&R is an ideal tool to comprehensively characterize the measurement system.

Analyzing the results

There are several important metrics to analyze in a GR&R study
output, such as percentage contribution, percentage study
variation and distinct categories.
+ Percentage contribution is the percentage of variation due
to the measurement system compared to total variation-all
sources add up to 100%.
 Less than 1%: The measurement system is acceptable.
 1 to 9%: The measurement system is acceptable-depending on the application, cost of the measuring device, cost
of repair and other factors.
 More than 9%: The measurement system is unacceptable
and should be improved.
+ Percentage study variation is the percentage of variation
due to the measurement system compared to total variation-all sources do not add up to 100%, which allows for
extrapolation.
 Less than 10%: The measurement system is acceptable.
 10 to 30%: The measurement system is acceptable-
depending on the application, cost of the measuring
device, cost of repair and other factors.
 More than 30%: The measurement system is unacceptable
and should be improved.
+ Distinct categories represent how well
a measurement system can differentiate between parts. The more distinct
categories, the more precise the measurement system.
 Distinct category 1: The measurement system cannot distinguish

FIGURE 6

Expanded GR&R study
Expanded GR&R

Gage variation
(repeatability)

Variation due to measurement
procedure (reproducibility)

Within-gage
variation

Operator-tooperator variation

Gage-to-gage
variation

Operator-toparts variation

Part-to-gage
variation

Operator-togage variation

GR&R = gage repeatability and reproducibility

between parts.
 Distinct category 2: The data can be divided into
two groups-high and low, for example.
 Distinct category 3 or 4: The data can be divided
into three groups-low, middle and high, for
example.
 Distinct category 5 or higher: The measurement
system can acceptably discriminate parts and
denotes an acceptable measurement system.

Critical for success

GR&R is a method used to evaluate the repeatability
and reproducibility of a measurement system because
measurement systems can themselves cause variations
in measurements. GR&R is a critical tool used to identify
and address that variation, which is crucial for the success of Six Sigma projects and statistical improvement
initiatives.
Consider the feasibility of measuring the part, the
number of parameters to account for, the number of
operators and the data points available when deciding
which GR&R study will be suitable for the MSA.

Neetu Choudhary has a master's degree in computer
applications from Rajiv Gandhi Technological University in
Bhopal, India. She is an ASQ member and an ASQ-certified
Six Sigma Black Belt, ISACA Certified in the Governance
of Enterprise IT, European Foundation for Quality
Management-certified assessor, Capability Maturity Model
Integration associate and ISO 9001:2015 lead auditor.

qualityprogress.com ❘ September 2017

QP 47


http://www.qualityprogress.com

Table of Contents for the Digital Edition of Quality Progress - September 2017

Seen and Heard
Progress Report
Mr. Pareto Head
Career Coach
Expert Answers
Field Notes
Data Disruption
The Deal With Big Data
Better Intelligence
A Study in Measurement
Innovation Imperative
Statistics Spotlight
Standard Issues
ASQ's 2017 Quality Resource Guide
Marketplace
Footnotes
Back to Basics
Quality Progress - September 2017 - Intro
Quality Progress - September 2017 - cover1
Quality Progress - September 2017 - cover2
Quality Progress - September 2017 - 1
Quality Progress - September 2017 - 2
Quality Progress - September 2017 - 3
Quality Progress - September 2017 - 4
Quality Progress - September 2017 - 5
Quality Progress - September 2017 - Seen and Heard
Quality Progress - September 2017 - 7
Quality Progress - September 2017 - Progress Report
Quality Progress - September 2017 - 9
Quality Progress - September 2017 - Mr. Pareto Head
Quality Progress - September 2017 - 11
Quality Progress - September 2017 - Career Coach
Quality Progress - September 2017 - 13
Quality Progress - September 2017 - 14
Quality Progress - September 2017 - Expert Answers
Quality Progress - September 2017 - Field Notes
Quality Progress - September 2017 - 17
Quality Progress - September 2017 - 18
Quality Progress - September 2017 - 19
Quality Progress - September 2017 - Data Disruption
Quality Progress - September 2017 - 21
Quality Progress - September 2017 - 22
Quality Progress - September 2017 - 23
Quality Progress - September 2017 - 24
Quality Progress - September 2017 - 25
Quality Progress - September 2017 - The Deal With Big Data
Quality Progress - September 2017 - 27
Quality Progress - September 2017 - 28
Quality Progress - September 2017 - 29
Quality Progress - September 2017 - 30
Quality Progress - September 2017 - 31
Quality Progress - September 2017 - 32
Quality Progress - September 2017 - 33
Quality Progress - September 2017 - Better Intelligence
Quality Progress - September 2017 - 35
Quality Progress - September 2017 - 36
Quality Progress - September 2017 - 37
Quality Progress - September 2017 - 38
Quality Progress - September 2017 - 39
Quality Progress - September 2017 - 40
Quality Progress - September 2017 - 41
Quality Progress - September 2017 - A Study in Measurement
Quality Progress - September 2017 - 43
Quality Progress - September 2017 - 44
Quality Progress - September 2017 - 45
Quality Progress - September 2017 - 46
Quality Progress - September 2017 - 47
Quality Progress - September 2017 - Innovation Imperative
Quality Progress - September 2017 - 49
Quality Progress - September 2017 - 50
Quality Progress - September 2017 - Statistics Spotlight
Quality Progress - September 2017 - 52
Quality Progress - September 2017 - 53
Quality Progress - September 2017 - Standard Issues
Quality Progress - September 2017 - 55
Quality Progress - September 2017 - 56
Quality Progress - September 2017 - 57
Quality Progress - September 2017 - ASQ's 2017 Quality Resource Guide
Quality Progress - September 2017 - 59
Quality Progress - September 2017 - 60
Quality Progress - September 2017 - 61
Quality Progress - September 2017 - 62
Quality Progress - September 2017 - 63
Quality Progress - September 2017 - 64
Quality Progress - September 2017 - 65
Quality Progress - September 2017 - 66
Quality Progress - September 2017 - 67
Quality Progress - September 2017 - Marketplace
Quality Progress - September 2017 - 69
Quality Progress - September 2017 - Footnotes
Quality Progress - September 2017 - 71
Quality Progress - September 2017 - Back to Basics
Quality Progress - September 2017 - cover3
Quality Progress - September 2017 - cover4
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