IPC-TM-650 EN 2022 试验方法--.pdf - 第17页

IPC-TM-650 Page 3 of 6 Number 1.8 Subject Measurement Precision Estimation for Binary Data Date 01/03 Revision A c. Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method, E…

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Table 1 Recommended evaluation criteria
Metric Acceptable Marginal Inadequate
IPC-TM-650
Page 2 of 6
Number
1.8
Subject
Measurement
Precision
Estimation
for
Binary
Data
Date
01/03
Revision
A
test
groups.
Prepare
more
than
the
material
required
to
ensure
an
adequate
amount
is
available
for
the
study
in
case
of
lost
or
damaged
specimens,
errors,
test
set-up,
etc.
Carefully
package
and
label
the
material.
Assign
serial
num¬
bers,
if
possible.
Identify
the
version
of
the
test
procedure.
Specify
care
and
handling
procedures.
Provide
a
data
sheet,
and
describe
any
documentation
required.
Require
a
test
log,
and
insist
that
observations
of
any
unusual
events
be
recorded.
5.2
Conducting
the
Evaluation
Ensure
the
samples
are
inspected
on
receipt.
Send
replacement
material
if
damaged
or
tests
are
performed
improperly.
Inspect
the
data
sheets
when
returned.
Review
the
test
logs
for
unusual
events.
Review
the
results.
Question
unusual
dis¬
positions
or
comments.
Incorrect
dispositions
and
typos
must
be
fixed
prior
to
analysis.
5.3
Analyzing
the
Data
Analysis
may
be
performed
on
the
data
sheet
or
on
the
Excel
spreadsheet
(see
6.2).
The
basic
techniques
involve
beginning
with
a
set
of
parts
or
materials
for
which
the
classification
has
been
previously
determined.
Several
inspectors
or
testers
then
examine
and
classify
the
parts
and
the
results
are
compared
with
the
known
standard
classification.
The
effectiveness
of
the
test
is
the
number
of
correct
determi¬
nations
divided
by
the
total
number
of
classification
opportu¬
nities
(number
of
parts
times
the
number
of
inspectors).
E
_
Number
of
correct
dispositions
~
Number
of
parts
x
Number
of
testers
'
'
The
probability
of
a
false
reject
and
the
probability
of
a
false
accept
can
be
defined
as
follows:
p
fr
_
Number
of
dispositions
where
good
parts
were
rejected
' '
-
Number
of
good
parts
x
Number
of
testers
'
'
p
，FA
_
Number
of
dispositions
where
bad
parts
were
accepted
(飞
' '
-
Number
of
bad
parts
x
Number
of
testers
'
'
5.4
Preparing
Analysis
Conclusions
Goals
for
measure¬
ment
precision
should
be
established
before
the
study
begins.
The
goals
should
be
established
using
knowledge
of
the
anticipated
levels
of
product
variability
(or
process
capability),
specifications,
customer
needs
and
the
possible
impact
of
dispositioning
test
samples
improperly.
As
a
rule
of
thumb,
the
guidelines
shown
in
Table
1
have
been
extensively
applied.
E
>0.9
0.8
to
0.9
<0.8
P(FR)
<0.05
0.05
to
0.10
>0.10
P(FA)
<0.02
0.02
to
0.05
>0.05
If
the
test
effectiveness
is
inadequate,
then
steps
should
be
taken
to
diagnose
and
improve
the
causes
of
the
deficiency.
The
probabilities
of
false
acceptance
and
false
rejection
should
help
in
this
diagnosis.
Marginal
tests
should
also
be
improved.
An
acceptable
test
effectiveness
rating
(E)
indicates
that
the
test
method
dispositions
the
products
with
reasonable
cor¬
rectness.
The
results
of
this
evaluation
should
be
compared
to
the
test
efficiency
goals
for
this
inspection.
The
rules
of
thumb
noted
above
have
been
found
to
be
useful.
These
goals
could
be
amended,
depending
on
the
criticality
of
the
inspection,
and
the
impact
of
incorrect
disposition.
6
Notes
6.1
Methods
for
Analyzing
Repeatability
and
Reproduc¬
ibility
This
test
method
covers
situations
where
the
mea¬
surements
result
in
binary
data,
such
as
go
and
no-go,
or
pass
and
fail
tests.
The
precision
of
the
test
is
determined
by
calculating
the
consistency
and
correctness
of
the
sample
dispositions.
Measurements
that
result
in
variables
data
can
be
analyzed
using
I
PC
Test
Method
IPC-TM-1
.9.
In
some
cases,
the
measurement
cannot
be
repeated
more
than
once
on
the
same
sample.
This
is
common
where
the
sample
is
consumed
during
the
test,
such
as
chemical
analy¬
sis,
or
changed
during
testing,
such
as
solderability
evalua¬
tions.
In
these
cases,
the
analysis
using
a
modified
average
and
range
method
is
possible.
This
method
is
under
develop¬
ment.
6.2
References
a.
ISO
5725-1
Accuracy
(trueness
and
precision)
of
measure¬
ment
methods
and
results
(parts
1
to
6),
1998(E),
Interna¬
tional
Organization
for
Standardization,
Geneva,
Switzer¬
land
(www.iso.org).
b.
Measurement
Systems
Analysis,
2nd
edition,
June
1998,
Automotive
Industry
Action
Group
(AIAG),
26200
Lahser
Road,
Southfield,
Ml
48034
(www.aiag.org).
IPC-TM-650
Page 3 of 6
Number
1.8
Subject
Measurement
Precision
Estimation
for
Binary
Data
Date
01/03
Revision
A
c.
Standard
Practice
for
Conducting
an
Interlaboratory
Study
to
Determine
the
Precision
of
a
Test
Method,
E691
-99,
ASTM,
Philadelphia,
PA
(www.astm.org).
d.
Concepts
for
R&R
Studies,
Larry
B.
Barrentine,
(ISBN
0-87389-108-2),
ASQC
Press,
Milwaukee,
Wl
((www.quali-
typress.asq.org).
e.
Basic
Statistics,
4th
Edition,
Mark
J.
Kiemele,
Stephen
R.
Schmidt,
Ronald
Berdine,
Air
Academy
Press,
1997,
ISBN
1-880156-06-7,
pages
9-71
to
9-77
f.
'Is
100%
Test
100%
Effective,”
W.
Russell,
1998
IPC
EXPO,
San
Jose,
CA
(gives
methods
for
calculating
the
likely
outcomes
on
product
test
for
differing
levels
of
mea¬
surement
precision.)
6.3
Software
Measurement
precision
studies
are
greatly
facilitated
by
use
of
software
to
perform
the
calculations.
Below
are
just
a
few
of
the
many
software
packages
which
can
be
used
for
this
purpose.
Reference
(a)
is
an
Excel
spreadsheet
written
to
perform
the
calculations
in
this
proce¬
dure.
a.
Measurement
Precision
Calculator
For
Binary
Data,
Excel
spreadsheet,
available
at
http://www.ipc.org/html/
testmethods.htm,
free
of
charge.
b.
Statgraphics
Plus,
Manugistics
Corp,
2115
East
Jefferson
Street,
Rockville,
MD,
20852-4999
(
ww
w
.
statg
rap
h
i
c
-
s.com).
c.
SPC
XL,
Air
Academy
Press,
1155
Kelly
Johnson
Blvd,
Colorado
Springs,
CO
80920
(www
.
ai
racad
.
oom)
.
d.
Minitab,
Minitab.
Inc.,
3081
Enterprise
Dr,
State
College,
PA
16801
(www.minitab.com).
e.
Interlaboratory
Data
Analysis
Software
for
E691
,
ASTM,
100
Barr
Harbor
Dr,
West
Conshohocken,
PA
19428
(www.astm.org).
Table 1: Data Entry Form
Enter test results into the table below.
Tester
Samples
1 2 3 4 5 6 7 8 9 10
Table 2: Samples Dispositioned Correctly
Score a ‘‘1’’ where disposition in Table 1 above matched the true standard.
Score a ‘‘0’’ where disposition did not match the true standard.
Note these scores for each of the testers in the table below.
Tester
Samples
1 2 3 4 5 6 7 8 9 10 Total
IPC-TM-650
Page 4 of 6
Number
1.8
Subject
Measurement
Precision
Estimation
for
Binary
Data
Date
01/03
Revision
A
Measurement
Precision
Study
-
Binary
Data
True
Standard
1
2
3
4
5
6
7
8
9
10
Calculations
True
Standard
1
2
3
4
5
6
7
8
9
10