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Chapter
11Statistically
BasedQuality
Improvementsfor
VariablesChapter
Objectives?Copyright
?
2017
Pearson
Education,
Inc.11-2Statistical
ThinkingCopyright
?
2017
Pearson
Education,
Inc.11-3Statistical
thinking
is
a
decision-making
skill
demonstrby
the
ability
to
draw
conclusions
based
on
data.Statistical
thinking
is
based
on
three
concepts:All
work
occurs
in
a
system
of
interconnected
processes.
All
processes
have
variation
(the
amount
of
variation
tends
to
beunderestimated).
Understanding
variation
and
reducing
variation
are
important
keysto
success.Why
Do
Statistics
Sometimes
Fail
in
theWorkplace?Copyright
?
2017
Pearson
Education,
Inc.11-4A
lack
of
knowledge
about
the
tools
leads
to
tools
beingmisapplied.General
disdain
for
all
things
mathematical
creates
a
naturbarrier
to
the
use
of
statistics.
When
was
the
last
time
youheard
someone
proclaim
a
love
for
statistics?Cultural
barriers
in
a
company
make
the
use
of
statistics
focontinual
improvement
difficult.Statistical
specialists
have
trouble
communicating
withmanagerial
generalists.Why
Do
Statistics
Sometimes
Fail
in
theWorkplace?
(cont’d)Copyright
?
2017
Pearson
Education,
Inc.11-5Statistics
generally
are
poorly
taught,
emphasizingmathematical
development
rather
than
application.People
have
a
poor
understanding
of
the
scientific
method.Organizations
lack
patience
in
collecting
data.
All
decisiohave
to
be
made
“yesterday.”Statistics
are
viewed
as
something
to
buttress
an
already-held
opinion
rather
than
a
method
for
informing
andimproving
decision
making.Why
Do
Statistics
Sometimes
Fail
in
theWorkplace?
(cont’d)Copyright
?
2017
Pearson
Education,
Inc.11-6
People
fear
using
statistics
because
they
fear
they
may
violatecritical
statistical
assumptions.
Time-ordered
data
are
messy
andrequire
advanced
statistical
techniques
to
be
used
effectively.
Most
people
don’t
understand
random
variation,
resulting
in
toomuch
process
tampering.Statistical
tools
often
are
reactive
and
focus
on
effects
rather
tcauses.
When
either
type
I
or
type
II
errors
occur,
erroneous
decisions
aremade
relative
to
products
that
can
result
in
high
costs
or
lostfuture
sales.Why
Do
Statistics
Sometimes
Fail
in
theWorkplace?
(cont’d)Copyright
?
2017
Pearson
Education,
Inc.11-7Type1
errorProducer’s
riskProbability
that
a
good
product
will
be
rejectedType2
errorConsumer’s
riskProbability
that
a
nonconforming
product
will
be
available
for
salUnderstanding
Process
VariationCopyright
?
2017
Pearson
Education,
Inc.11-8All
processes
exhibit
variationSome
variation
can
be
managed
and
some
cannot
be
managed.Types
of
process
variation:RandomNonrandomRandom
VariationAlso
called
common
causeCentered
around
themeanandoccurs
with
asomewhat
consistentamount
of
dispersionUncontrolled
variationMay
be
either
large
orsmallFigure
11-1Copyright
?
2017
Pearson
Education,
Inc.11-9Nonrandom
VariationAlso
called
special
causevariationResults
from
some
eventwhich
may
be
a
shift
in
aprocess
mean
or
someunexpected
occurrenceDispersion
and
average
ofthe
process
are
changingProcess
is
not
repeatableFigure
11-2Copyright
?
2017
Pearson
Education,
Inc.11-10Process
StabilityCopyright
?
2017
Pearson
Education,
Inc.11-11The
variation
that
we
observe
in
the
process
is
randomvariation
and
not
nonrandom.Process
charts
Graphs
designed
to
signal
process
workers
when
nonrandomvariation
is
occurring
in
a
processSampling
MethodsCopyright
?
2017
Pearson
Education,
Inc.11-12Reasons
why
sampling
is
used:
Samples
are
cheaper,
take
less
time,
are
less
intrusive,
and
allowthe
user
to
frame
the
sample.
If
quality
testing
is
destructive,
100%
inspection
would
beimpossible.Sampling
MethodsCopyright
?
2017
Pearson
Education,
Inc.11-13Reasons
why
100%
inspection
is
used:
When
a
lot
of
material
has
been
rejected
in
the
past
and
materialsmust
be
sorted
to
keep
good
materials
and
return
defectivematerials
for
a
refundWhen
employees
perform
their
own
in-process
inspectionSampling
MethodsCopyright
?
2017
Pearson
Education,
Inc.11-14Random
samples
To
sample
in
such
a
way
that
every
piece
or
product
has
an
equalchance
of
being
selected
for
inspectionSystematic
samplesTo
sample
according
to
time
or
according
to
sequenceRational
subgroup
samplesTo
sample
by
a
group
of
data
that
is
logically
homogenousPlanning
for
InspectionCopyright
?
2017
Pearson
Education,
Inc.11-15Questions
to
answer
about
sampling:What
type
of
planning
will
be
used?Who
will
perform
the
inspection?Who
will
use
in-process
inspection?What
is
the
sample
size?What
are
the
critical
attributes
to
be
inspected?Where
should
the
inspection
be
performed?Control
PlansCopyright
?
2017
Pearson
Education,
Inc.11-16Provide
a
documented,
proactive
approach
to
defining
howto
respond
when
process
control
charts
show
that
aprocess
is
out
of
controlRequired
part
of
an
ISO
9000
quality
management
system(QMS)Control
Plan
SampleFigure
11-3Copyright
?
2017
Pearson
Education,
Inc.11-17Process
Control
ChartsStatistical
process
control
charts:Tools
for
monitoring
process
variationFigure
11-4Copyright
?
2017
Pearson
Education,
Inc.11-18Variables
and
Attributes
Control
ChartsCopyright
?
2017
Pearson
Education,
Inc.11-19VariableContinuous
measurement
such
as
height,
weight,
or
volumeAttribute
An
either-or
situation,
such
as
a
motor
starting
or
not,
or
a
lensbeing
scratched
or
notVariables
and
Attributes
Control
ChartsThe
most
common
types
of
variableand
attribute
chartsTable11-1Copyright
?
2017
Pearson
Education,
Inc.11-20Variables
and
Attributes
Control
ChartsCopyright
?
2017
Pearson
Education,
Inc.11-21Central
requirements
for
properly
using
process
charts:
You
must
understand
this
generic
process
for
implementingprocess
charts.You
must
know
how
to
interpret
process
charts.You
need
to
know
when
different
process
charts
are
used.
You
need
to
know
how
to
compute
limits
for
the
different
typesof
process
charts.We
treat
each
of
these
topics
separately.Variables
and
Attributes
Control
ChartsCopyright
?
2017
Pearson
Education,
Inc.11-22Steps
in
developing
process
control
charts:
Identify
critical
operations
in
the
process
where
inspection
migbe
needed.
These
are
operations
in
which
the
product
will
benegatively
affected
if
the
operation
is
performed
improperly.
Identify
critical
product
characteristics.
These
are
the
aspectsthe
product
that
will
result
in
either
good
or
poor
functioning
ofthe
product.
Determine
whether
the
critical
product
characteristic
is
avariable
or
an
attribute.Variables
and
Attributes
Control
ChartsCopyright
?
2017
Pearson
Education,
Inc.11-23Steps
in
developing
process
control
charts
(cont’d):4.
Select
the
appropriate
process
control
chart
from
among
themany
types
of
control
charts.
(This
decision
process
and
thetypes
of
charts
available
are
discussed
later.)4.
Establish
the
control
limits
and
use
the
chart
to
continuallymonitor
and
improve.4.
Update
the
limits
when
changes
have
been
made
to
the
process.Understanding
Process
ChartsProcess
charts
are
an
application
of
hypothesis
testingwhere
the
null
hypothesis
is
that
the
process
is
stable.For
example:Null
Hypothesis:
Ho:
m
=
11
inchesAlternative
Hypothesis:
H1:
m
11
inchesCopyright
?
2017
Pearson
Education,
Inc.11-24Understanding
Process
ChartsHypothesis
TestingFigure
11-5Process
ChartFigure
11-6Copyright
?
2017
Pearson
Education,
Inc.11-25?Copyright
?
2017
Pearson
Education,
Inc.11-26Figure
11-7Standard
Process
Chart
FormCopyright
?
2017
Pearson
Education,
Inc.11-27Figure
11-8Completed
Process
Chart
FormCopyright
?
2017
Pearson
Education,
Inc.11-28Figure
11-9x
and
R
Charts
Calculation
WorksheetCopyright
?
2017
Pearson
Education,
Inc.11-29Figure
11-10Calculations
for
Figure
11-8
DataCopyright
?
2017
Pearson
Education,
Inc.11-30Interpreting
Control
ChartsSignals
forconcern
sent
bya
control
chartHansen,
Bertrand
L.
Quality
Control:
Theory
and
Applications.
Upper
Saddle
River,
NJ:
Pearson
Education(1964).
ISBN:
013745208X.
?1964,
p.65.
Reprinted
and
Electronically
reproduced
by
permission
of
PearsonEducation,
Inc.,
New
York,
NY.Figure
11-11Copyright
?
2017
Pearson
Education,
Inc.11-31Interpreting
Control
ChartsSignals
forconcern
sent
bya
control
chart(cont’d)Hansen,
Bertrand
L.
Quality
Control:
Theory
and
Applications.
Upper
Saddle
River,
NJ:
Pearson
Education(1964).
ISBN:
013745208X.
?1964,
p.65.
Reprinted
and
Electronically
reproduced
by
permission
of
PearsonEducation,
Inc.,
New
York,
NY.Figure
11-11Copyright
?
2017
Pearson
Education,
Inc.11-32Interpreting
Control
ChartsCopyright
?
2017
Pearson
Education,
Inc.11-33Out-of-control
situations:
Two
points
in
succession
farther
than
two
standard
deviationsfrom
the
mean
Process
run
–
Five
points
in
succession
either
above
or
below
thecenter
lineProcess
drift
–
Seven
points,
all
increasing
or
decreasing
Erratic
behavior
–
Large
jumps
of
more
than
three
or
fourstandard
deviationsExample
11-1Problem:
The
Sampson
Company
produces
high-tech
radar
that
is
used
in
top-secret
weapons
by
the
Secret
Service
andthe
Green
Berets.
It
has
had
trouble
with
a
particular
roundcomponent
with
a
target
of
6
centimeters.
Samples
of
size
4were
taken
during
four
successive
days.The
results
are
in
the
following
table.Copyright
?
2017
Pearson
Education,
Inc.11-34Example
11-1Copyright
?
2017
Pearson
Education,
Inc.11-35
Develop
a
process
chart
to
determine
whether
the
process
is
stable.Because
these
are
measurements,
use
x
and
R
charts.
Using
the
calculation
work
sheet,
Figure
11-12
shows
the
values
for
theprocess
control
limits.
The
x
control
chart
for
this
problem
is
shown
with
the
appropriatelimits.
The
R
chart
is
also
in
control.
The
sample
averages
were
placedon
the
control
chart,
and
the
process
was
found
to
be
historically
incontrol.
Because
the
averages
and
ranges
fall
within
the
control
limitsand
no
other
signals
of
nonrandom
activity
are
present,
we
concludethat
the
process
variation
is
random.
Note
that
this
example
is
very
simple.
Generally,
you
use
15
to
20subgroups
to
establish
control
charts.Example
11-1?Copyright
?
2017
Pearson
Education,
Inc.Figure
11-1211-36Example
11-1Calculationsusing
ExcelMicrosoft
Excel,
Microsoft
Corporation.
Used
by
permission.Figure
11-13Copyright
?
2017
Pearson
Education,
Inc.11-37X
and
Moving
Range
(MR)
Charts
forPopulation
DataCopyright
?
2017
Pearson
Education,
Inc.11-38X
and
MR
charts
are
used
if
you
have
a
variablemeasurement
that
you
want
to
monitor
and
do
not
haveenough
observations
to
use
sampling.
Central
limit
theorem
does
not
apply,
which
may
result
in
the
databeing
non-normally
distributed.
Therefore,
there
is
an
increase
in
the
likelihood
that
you
will
drawan
erroneous
conclusion.It
is
best
to
first
make
sure
that
the
data
are
normally
distributedX
and
Moving
Range
(MR)
Charts
forPopulation
DatassX
chart
limitCenter
line:Limits:MR
limits
Same
as
R
chart
(where
n=2),except
that
the
ranges
are
computedas
the
differences
from
one
sample
to
the
nextCopyright
?
2017
Pearson
Education,
Inc.11-39Example
11-2Copyright
?
2017
Pearson
Education,
Inc.11-40Problem:
The
EA
Trucking
Company
of
Columbia,
Missourihauls
corn
from
local
fields
to
the
SL
Processing
Plant
inLincoln,
Nebraska.
Although
the
trucks
generally
take
6.5hours
to
make
the
daily
trip,
recently
there
seems
to
bemore
variability
in
the
arrival
times.
Mr.
Everett,
the
ownesuspects
that
one
of
his
drivers,
Paul,
may
be
visiting
hisgirlfriend
Janice
en
route
in
Kansas
City.
The
driver
claimsthat
this
is
not
the
case
and
that
the
increase
is
simplyrandom
variation
because
of
variability
in
traffic
flows.
Tdrivers
keep
written
logs
of
departure
and
arrival
times.Example
11-2oMr.
Everett
has
listedthese
times
in
thefollowing
table.
Youare
chosen
as
theanalyst
to
investigatethis
situation.
What
dyou
think?Copyright
?
2017
Pearson
Education,
Inc.11-41Example
11-2Solution:
Youdevelop
an
X
andMR
process
chart
totest
the
hypothesis.The
results
fromExcel
are
in
Figure11-14.Microsoft
Excel,
Microsoft
Corporation.
Used
by
permission.Figure
11-14Copyright
?
2017
Pearson
Education,
Inc.11-42Median
ChartsCopyright
?
2017
Pearson
Education,
Inc.11-43Median
charts
may
be
used
if
it
is
too
time
consuming
orinconvenient
to
compute
subgroup
averages
or
you
haveconcerns
about
the
accuracy
of
computed
means.Need
to
use
an
odd
sample
size,
usually
3,
5,
or
7Median
Chart
Limits::Center
lineControl
limits::Copyright
?
2017
Pearson
Education,
Inc.11-44Example
11-3Copyright
?
2017
Pearson
Education,
Inc.11-45Problem:
The
Luftig
food
company
has
gathered
thefollowing
data
with
weights
of
its
new
health
food
product.Because
the
published
weight
on
the
package
is
6
ounces,Mr.
Luftig
wants
to
know
if
the
company
is
complying
withweight
requirements.Example
11-3Twenty
samplesof
size
5
weredrawn.Copyright
?
2017
Pearson
Education,
Inc.11-46Example
11-3
Solution:
Resultsshow
that
the
processis
not
in
control,
withan
average
median
of6.23.
The
medianprocess
chart
doesshow
that
someproduct
is
being
madethat
is
below
6
ounces.It
also
shows
thatpoints
4,
7,
and
10
areout
of
control.Figure
11-15Microsoft
Excel,
Microsoft
Corporation.
Used
by
permission.Copyright
?
2017
Pearson
Education,
Inc.11-47?Copyright
?
2017
Pearson
Education,
Inc.11-48?Where:Copyright
?
2017
Pearson
Education,
Inc.11-49?Copyright
?
2017
Pearson
Education,
Inc.11-50?Table
11-3Copyright
?
2017
Pearson
Education,
Inc.11-51Example
11-4Copyright
?
2017
Pearson
Education,
Inc.11-52Problem:
Twenty
samples
were
taken
for
a
milled
rod.
Thediameters
are
needed
to
determine
whether
the
process
isin
control.
Because
these
milled
rods
must
be
measuredwithin
1/10,000
of
an
inch,
it
is
determined
that
the
processdispersion
is
important.Therefore,
you
need
to
use
an
s
and
x
chart
to
monitor
theprocess.
The
data
are
found
in
Figure
11-16.
We
have
20samples
with
n
=
3.Example
11-4Solution:
The
controlcharts
in
Figure
11-16
show
that
theprocess
is
in
control.There
is
no
need
forcorrective
action.The
solution
methodis
demonstrated
inthe
next
section.Figure
11-16Microsoft
Excel,
Microsoft
Corporation.
Used
by
permission.Copyright
?
2017
Pearson
Education,
Inc.11-53Other
Control
ChartsSummary
of
Variables
Chart
FormulasTable11-4Copyright
?
2017
Pearson
Education,
Inc.11-54Moving
Average
ChartCopyright
?
2017
Pearson
Education,
Inc.11-55A
chart
for
monitoring
variables
and
measurement
on
acontinuous
scale
by
using
past
information
to
predict
whatthe
next
process
outcome
will
beCusum
ChartA
chart
used
toidentify
slight
butsustained
shifts
inauniverse
in
whichthere
is
noindependence
between
observationsFigure
11-17Copyright
?
2017
Pearson
Education,
Inc.11-56Choosing
the
Correct
Variables
ControlChartFigure
11-18Copyright
?
2017
Pearson
Education,
Inc.11-57Corrective
ActionCopyright
?
2017
Pearson
Education,
Inc.11-58Corrective
action
steps
when
a
process
is
out
of
control:Carefully
identify
the
quality
problem.Form
the
appropriate
team
to
evaluate
and
solve
the
problem.
Usestructured
brainstorming
along
with
fishbone
diagrams
oraffinity
diagrams
to
identify
causes
of
problems.Brainstorm
to
identify
potential
solutions
to
problems.Eliminate
the
cause.5.
Restart
the
process.5.
Documentthe
problem,
root
causes,
and
solutions.5.
Communicate
the
results
of
the
process
to
all
personnel
so
thisprocess
becomes
reinforced
and
ingrained
in
the
organization.Using
Control
Charts
to
ContinuouslyImproveCopyright
?
2017
Pearson
Education,
Inc.11-59Two
key
concepts:The
focus
of
control
charts
should
be
on
continuous
improvement.
Control
chart
limits
should
be
updated
only
when
there
is
achange
to
the
process.
Otherwise,
any
changes
are
unexpected.Effects
of
Tampering
with
the
ProcessFigure
11-19Copyright
?
2017
Pearson
Education,
Inc.11-60Process
Capability
for
VariablesCopyright
?
2017
Pearson
Education,
Inc.11-61The
capability
of
a
process
to
produce
a
product
thatmeetspecificationWorld-class
levels
of
process
capability
are
measured
byparts
per
million
(ppm)
defect
levels.Process
Capability
for
VariablesSix
Sigma
programs
result
in
highly
capable
processes
and
aaverage
of
only
3.4
defects
per
million
units
produced.Figure
11-20Copyright
?
2017
Pearson
Education,
Inc.11-62Population
versus
Sampling
DistributionsCopyright
?
2017
Pearson
Education,
Inc.11-63Population
distributions
Distributions
with
all
individual
responses
from
an
entirepopulationPopulation
A
collection
of
all
the
items
or
observations
of
interest
to
adecision
makerSampleA
subset
of
the
populationSampling
distributionsDistributions
that
reflect
the
distribution
of
sample
meansPopulation
versus
Sampling
DistributionsPopulation
and
Sampling
Distributions
for
Class
HeightsFigure
11-21Copyright
?
2017
Pearson
Education,
Inc.11-64Population
versus
Sampling
DistributionsCopyright
?
2017
Pearson
Education,
Inc.11-65In
the
context
of
quality,
specifications
and
capabilityassociated
with
population
distributions.Sample-based
process
charts
and
stability
are
computedstatistically
and
reflect
sampling
distributions.Quality
practitioners
should
not
compare
process
chartlimits
with
product
specifications.Capability
StudiesCopyright
?
2017
Pearson
Education,
Inc.11-66Reasons
to
perform
a
process
capability
study:
To
determine
whether
a
process
consistently
results
in
productsthat
meet
specifications
To
determine
whether
a
process
is
in
need
of
monitoringthrough
the
use
of
permanent
process
chartsCapability
StudiesCopyright
?
2017
Pearson
Education,
Inc.11-67Five
steps
to
perform
process
capability
studies:
Select
a
critical
operation.
These
may
be
bottlenecks,
costlysteps
of
the
process,
or
places
in
the
process
in
which
problemshave
occurred
in
the
past.Take
k
samples
of
size
n,
where
x
is
an
individual
observation.Where
19
<
k
<
26If
x
is
an
attribute,
n
>
50
(as
in
the
case
of
a
binomial)Or
if
x
is
a
measurement,
1
<
n
<
11Use
a
trial
control
chart
to
see
whether
the
process
is
stable.Capability
StudiesFive
steps
to
perform
process
capability
studies
(cont’d)4.
Compare
process
natural
tolerancelimits
with
specificationlimits.
Note
that
natural
tolerance
limits
are
three
standarddeviation
limits
for
the
population
distribution.
This
can
becompared
wit
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