Transcript Measurement System Analysis for Continuous Processes

MSA Example:
Attribute or
Categorical Data
MSA Operational Definitions
 Accuracy: Overall agreement of the measured value with the true
value (which may be an “expert” value). Bias plus precision.
 Attribute Data: Discrete qualitative data.
 Attribute Measurement System: Compares parts to a specific set
of criteria and accepts the item if the criteria are satisfied.
 Bias: A systematic difference from the true value. Revealed in the
differences in averages from the true value.
 Precision: Variation in the measurement process.
 R&R: Repeatability and Reproducibility. Two elements of precision.
 Repeatability: The variation observed when the same operator
measures the same item repeatedly with the same device.
 Reproducibility: The variation observed when different operators
measure the same parts using the same device, sometimes it can
be the same operator using different devices.
MSA for Continuous Processes 2 .PPT
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The Fundamental MSA Question
“Is the variation (spread) of the measurement system
too large to study the current level of process
variation?”
Product Variability
Process Variability
Variation
in the
measurement
process
+
MSA for Continuous Processes 3 .PPT
(Observed Variability)
Total Variability
=
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Bias
True
Value or
Standard
Possible Causes of Bias
 Sensor not properly
calibrated
Bias
 Improper use of sensor
 Unclear procedures
Observed
Average
MSA for Continuous Processes 4 .PPT
 Human limitations
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Repeatability
Possible Causes of Poor
Repeatability
Equipment
 Gage instrument needs
maintenance
 The gage needs to be more
rigid
Repeatability
MSA for Continuous Processes 5 .PPT
People
 Environmental conditions
(lighting, noise)
 Physical conditions (eyesight)
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Reproducibility
Mean of
the measurements
of Operator B
Mean of
the measurements
of Operator A
Possible Causes of Poor
Reproducibility
 Measurement procedure is not
clear
 Operator is not properly trained
in using and reading gage
Reproducibility
MSA for Continuous Processes 6 .PPT
 Operational Definitions not
established
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Attribute Measurement Systems Study
 Discrete qualitative data
 Go/no-go basis; or limited data categories
 Compares parts to specific criteria for accept/not accept or
to be placed in category
 Must screen for effectiveness to discern good parts from
bad
 At least two appraisers and two trials each
 If available, have Quality Master rate parts first
MSA for Continuous Processes 7 .PPT
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Attribute MSA Study
Attribute MSA Example
Appraiser A
Master
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
MSA for Continuous Processes 8 .PPT
G
G
G
NG
G
G
NG
NG
G
G
G
G
G
G
NG
G
G
G
G
NG
Appraiser B
1
2
1
2
G
G
NG
NG
G
G
NG
NG
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
NG
G
G
NG
NG
G
G
G
G
NG
G
G
G
G
G
G
G
G
G
G
NG
G
NG
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
NG
G
G
NG
G
G
G
G
G
G
G
G
G
G
G
G
G
G = Good
NG = Not Good
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Challenges of Continuous Process MSA
 MSA study is an experiment
 Requires two or more trials for calculating Repeatability
 Needs a way to present the inspection units to the appraiser
multiple times
 Is not possible within the continuous process
MSA for Continuous Processes 9 .PPT
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Case Example: Visual Inspection of Glass
Packers
Catwalk
Cutter
Inspector
Glass
MSA for Continuous Processes 10 .PPT
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Case Example: Challenges to Overcome
 Bias to the standard could be evaluated on-line.
 Repeatability and Reproducibility (R & R) could not be
evaluated on-line.
 A method had to be devised to allow the inspectors to view
the same pieces of glass repeatedly.
 The solution was an off-line conveyor which simulated the
on-line condition as closely as possible.
MSA for Continuous Processes 11 .PPT
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Case Example: Attribute MSA Method Employed
 20 pieces of glass from the process that included both good
and bad samples were selected.
 A team of people well versed in the quality standard
classified each piece of glass as either “pass” or “fail.”
 All regular inspectors independently evaluated each piece
twice (in random order).
 The inspectors used a log sheet to record the data.
 Minitab® was used to analyze the data.
MSA for Continuous Processes 12 .PPT
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Case Example: Attribute MSA Study Data
Excerpt of
full data
for 20
inspectors
MSA for Continuous Processes 13 .PPT
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Case Example: Attribute MSA Study Results
Date of study :
Reported by :
Name of product:
Misc:
Assessment Agreement
Within Appraisers
Appraiser vs Standard
100
95.0% C I
P ercent
90
90
80
80
Percent
Percent
100
70
60
9/13 and 9/19/07
Bill Sunderland and Bob Panatieri
Solar
Mainline Mark ing
95.0% C I
P ercent
70
60
50
50
40
40
l
t
n y o lly Tim E a r e v e ni e oh n n ie lin rry
o
n
n
a
T M
S t J ea J Ro C L
l
t
n y o lly T im E a r e v e ni e oh n n ie lin rry
o
n
n
a
T M
S t J ea J Ro C L
Appraiser
Appraiser
MSA for Continuous Processes 14 .PPT
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Case Example: Attribute MSA Study Results (continued)
MSA for Continuous Processes 15 .PPT
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Case Example: Attribute MSA Study Results (continued)
MSA for Continuous Processes 16 .PPT
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Case Example: Attribute MSA Study Results (continued)
MSA for Continuous Processes 17 .PPT
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Case Example: Attribute MSA Study Conclusions
 What could have caused the poor agreement?
 What was done to improve consistency?
MSA for Continuous Processes 18 .PPT
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