Well, thanks
for
being
here
today.
My
name
is
Ron
Andrews.
I've
got
contact
information
listed
here,
so
if
there
are
any
questions after
the
fact,
you
can
reach
me
at
these
addresses.
Going to be
talking
about
quality
improvement,
a
very, very
general
term,
but
this
is
specific
with
specific
results
from
a
project
I
worked
on
many
years
ago.
This
goes
a
long
time
ago
in
a
galaxy
far,
far
awayâ¦
Or
maybe
it
was
1986
in
Rochester,
New
York,
at
Eastman
Kodak
dealing
with
photographic
emulsions.
A
little
history.
Kodak
had
a
corporate
quality
council
that
had
known
for
years
that
we
really
needed
a
robust
statistical
process
control
program.
Management
wasn't
buying
it.
They
didn't
want
to
pay
for
it.
They
promoted
some
less
expensive
options
like
slogan
contests
and
pep
rallies,
and a
lot
of
you
know
about
how
effective
they
are.
By
1985,
sales
were
hitting
records,
but
so
was
waste.
So
the
council
finally
got
approval
for
an
SPC
program.
Though the
improvements
I'm
going
to
talk
about
are
a
small
part
of
the
total
effort.
Within
the
emulsion
manufacturing
at
Eastman
Kodak
that
I
was
working
with,
I
was
one
of
several
engineers
and
a
number
of
operators
working
on
this,
so
I
contributed
to
the
results
I'm
showing,
but
I
was
by
no
means
the
leader
for
the
whole
effort.
So
why
light-sensitive
silver
halide
emulsions?
It's
kind
of
obsolete
technology,
isn't
it?
Well,
yeah,
probably.
But
there's
still
three
companies
that
do
this
on
a
regular
basis,
and
there
are
still
a
few
million
people
who
shoot
film.
Most
of
all,
this
is
familiar
to
me,
and
I
have
some
results
I
can
share.
I'll
talk
about
the
basic
process
and
what
do
the
chemists
tell
us?
We'll
talk
about
several
different
quality
improvement
tools
like
data
sheets,
and
cause
and
effect
diagrams,
trend
charts,
and
statistical
process
control
charts.
Then
got
to
deal
with
the
people
side
of
SPC.
It's
probably
more
important
than
the
statistics.
And
then
I'll
deal
with
a
question
that
I had
to
deal
with
directly
way
back
then:
How
do
you
do
SPC
when
you
only
make
six
batches
a
year?
Before
I
really
get
started,
I
need
to
acknowledge
the
leadership
of
two
people.
In
our
group
of
engineers,
there
was
no
appointed
leader,
but
Carl
Eldridge
was
clearly
the
point
man.
He
had
this
nice,
easy-
going
manner
and
could
talk
production
supervisors
into
making
changes
that
they
really
didn't
want
to.
But
he'd come in, "W
e're
just
going
to
try
this
out
and
see
if
it
works.
"And
if
it
works,
we'll
probably
keep
doing
it
and
it'll
reduce
your
waste."
He
would
talk
them
into
it.
Kevin
Hurley
was
also
a
key
person.
He
was
2nd-floor
Emulsion M
aking
group
leader.
He
was
a
very
capable
leader
and
had
the
trust
of
all
the
people
who
worked
in
his
group.
They
decided
they
really
wanted
to
have
control
of
the
process.
Engineers
could
decide
the
specs,
but
they
wanted
to
control
the
process.
Turned
out
to
be
a
very
good
decision.
Overview
of
photographic
film
manufacturing,
and
this
is
the
50,000
-foot
level.
We
weigh
out
the
ingredients.
We
precipitate
the
silver
halide emulsions.
We
wash
them.
We
take
samples
of
each
batch
and
sensitize
them
at
three
different
temperatures,
choose
the
best
temperature,
and
then
sensitize
the
balance
of
each
batch.
Then
we
assemble
all
the
ingredients
necessary for a coating event,
and
test
each
melt.
A
melt
is
a
kettle
ful.
You
got
to melt the
gel.
That's
where
that
term
comes
from.
Then
make
corrections
for
the
layers
out
of
spec,
and
there
will
be
some.
In
those
days,
it
was
a
given.
Then
we
coat
a
short
pilot,
and
then
we
adjust
the
formulas,
and
then
we
coat a
short
re-
pilot
about
a
week
later
and
adjust
the
formulas
again.
And
then
if
things
are
looking
good,
we
coat the
remaining
emulsions
in one
or
two
large
runs
and
test
the
results.
And if
necessary,
take
the
coated rolls
back
to
the
coating
ally
and
apply
filter
dyes
to
correct
the
color
balance.
If
it's
not
already
obvious,
everything
in
red
isn't
an
adjustment
step.
These
are
things
we
did
because
we
didn't
always
get
it
right
the
first
time.
It's
basic
product
control.
Kodak
has
some
of
the
most
extensive
and
elaborate
product
control
methods
I've
ever
seen
or
heard
about.
It's
not
necessarily
a
market
distinction.
I'm
focusing
on
emulsions
because
the
products
that
I
was
dealing
with,
basically
Kodachrome
and
Ektachrome
slides,
the
light
-sensitive
silver
halide
emulsions
were
by
far
the
biggest
contributors
to
variability.
In
the
emulsion
manufacturing
process,
we
were
still
using
the
old
school
equipment.
There
were
some
computer-
controlled
systems,
but
we
were
dealing
with
open
kettles
and
gravity
flow
from
jars
into
the
main
kettle.
The
main
kettle
started
with
water,
phthalated
gel,
sodium
bromide,
and
potassium
iodide.
We
had
three
jars:
one
prepped
with
silver
nitrate,
another
with
ammonium
hydroxide,
another
with
sulfuric
acid.
We
start
by
running
the
silver
nitrate
through
disc
orifices.
There
would
be
a
set
of
discs
with
calibrated
holes
drilled
in
them.
That
was
basically
our
flow
control.
Now,
gravity
flow
is
extremely
consistent
if
you
keep
the
geometry
consistent.
Big
"if"
there.
Once
we
had
all
of the
silver
nitrate
in
there,
we
formed
a
number
of
silver
halide crystals.
We
pour
in
the
ammonium
hydroxide.
Ammonia
is
a
silver
solvent.
It
dissolves
the
little
crystals,
and
they
plate
out
on
the
big
crystals,
so that's
our
growth
step.
Then
we
go
into
the
washing
step.
We
need
to
remove
the
salts,
the
nitrate
and
the
sodium
and
the
iodideâ¦
Not the sodium, the
potassium.
Excuse
me.
We
add
acid,
which,
first
of
all,
quenches
the
ammonia
reactions,
and
second
of
all,
it gets
the
pH
low
enough
so
that
the
phthalated
gel
coagulates
and
drops
to
the
bottom
of
the
kettle
with
the
silver.
At
this
point,
we
siphon
the
supernatant
liquid
off
and
complete
the
washing
step.
Some
effects
we
knew
about.
We
knew
grain
size
was
proportional
to
the
silver
run
time.
That's
the
total
time
it
takes
for
the
silver
to
run
into
the
kettle.
If
the
silver
is
running
longer,
that
means
it
was
a
lower
flow
rate
initially,
where
the
individual
grains
are
formed.
If
you
have
fewer
grains
and
add
the
same
amount
of
silver,
you're
going
to
grow
them
larger.
Temperature
is
also
proportional
to
run
time,
as
is
the
amount
of
ammonia.
That's
not
directly
proportional.
It's
very
nonlinear.
It's
a
very
steep
slope
to
start
with,
and
then
it
levels
out.
In
addition
to
grain
size,
we
had
to
deal
with
fog.
Fog
is
what
you
get
when
a
silver
halide
crystal
develops
without
having
been
exposed
to
light.
We
don't
form
images
that
way,
so
we
need
to
minimize
this.
That's
proportional
to
the
free
ionic
silver
concentration
and
to
some
extent,
the
temperature.
Now,
for
any
chemists
in
the
group,
the
solubility
coefficient
for
silver
bromide
is
something
like
5
times
10â»Â¹Â³
.
The
free
ionic
silver
concentration
is
extremely
low,
but
it
still
makes
a
difference.
Variation
in
this
level
makes
a
difference
in
the
photographic
properties.
We
prepared c
ause
and
effect
diagrams
on
paper,
hand-
drawn.
I
really
wish
we
had
a
tool
like
the
one
in
JMP,
where
you
list
the
key p
arent
parameters.
In
this
case,
we're
looking
at
grain
size,
and
then we
have
materials,
methods,
etc.,
t
hat
might
affect
that.
And
then
you
move
these
child
parameters
over
to
the
parent
side
and
list
the
things
that
might
affect
that.
As
far
as
I
know,
there's
no
limit
to
how
many
branches
you
have
on
your
diagram.
Once
you
have
this
table
made
up,
you
identify
the
child
column
and
the
parent
column
and
hit
the
OK
button,
and
out
pops
the
diagram.
I
don't
know
of
another
way
that's
as
easy,
and
I'm
pretty
sure
there's
nothing
else
as
easy
when
you
have
to
modify
something.
Instead
of
moving
boxes
around
on
a
graphic
chart,
you
just
edit
one
or
two
of
the
lines,
or
maybe
delete
one,
add
one,
and
hit
the
button
again.
That's
all
there
is
to
it.
Now,
all
of
these
items
listed
on
this
chart
can
potentially
affect
the
grain
size.
But
when
it
came
down
to
it,
the
run time
and
the
variation
from
one
disc
orifice
to
another,
and
the
variation
from
kettle
to
kettle
were
the
most
important
things.
We
also
did
this
for
the
vAg.
vAg is a
measurement
which
is
as
close
as
we
can
get
to
measuring
the
actual
free
ionic
silver
concentration.
We
have
basically
the
same
things
listed
here,
but
in
this
case,
it's
the
percent phthalation
which
affects
the
washing,
and
the
siphon
level
which
is
directly
related
to
the
washing.
These
are
the
two
critical
things
in
controlling
the
vAg.
Going
through
some
of
the
conventional
quality
improvement
tools,
we
had
data
sheets.
We
had
14x
17
ledger
books,
about
six
inches
thick.
They
had
years
worth
of
data
of
several
hundred
emulsion kinds
,
and
they
were
in
a
lab
that
was
hard
to
get
to.
You
had
to
go
through
a
dark
hallway
to
get
there.
When
we
learned
where it
was
and
how
to
get
there,
we
started
borrowing
the
pages
and
transcribed
the
data
on
the
emulsion
kinds
of
interest
into
SAS
datasets.
It's
a
lot
easier
to
use
things
in
digital
form.
If
we'd
had
JMP,
the
data
tables
would
have
looked
something
like
this.
Each
of
the
emulsion
kinds
had
a
four-
digit
number
identifying
it.
We
had
sequential
batch
numbers.
We
recorded
the
date.
We
recorded
the
kettle
used,
and
then
we
recorded
a
number
of
parameters.
This
is
the
run time
in
seconds.
pHs
after
several
different
process
steps,
and
the
vAg at
the
end.
This
is
an
early
trend
chart.
We
hadn't
put
control
limits
on
it
yet.
This
is
the
run time.
Significant
variability
here.
We
could'
ve
done
extensive
regression
analyses
to
try
to
determine
what's
really
influencing
this.
The
first
step
was
easy.
We
overlaid
the
kettle
designations.
It's
pretty
obvious.
You
don't
need
any
special
analysis
to
know
these
kettles
are
different.
These
kettles
have
been
there
for
a
long
time,
and
it
wasn't
really
possible
to
completely
rework
them,
so
we
restricted
each
emulsion
kind
to
a
particular
kettle.
Kind 6001
was
restricted
to
kettle
602.
I'll
get
into
more
details
on
the
control
charts
later,
but
just
to
show
the
data.
This
early
unrestricted
phase.
We were not
using
control
limits
at
the
time,
but
this
was
our
initial
variability.
And
then
we
restricted
the
kettle,
and
we
got
a
large
reduction
in
the
variability.
And
then
one
of
the
other
engineers
got
the
idea
that
maybe
all
those
disc orifices
weren't
created
equal.
He
set
up
some
experiments
and
ran
some
water
batches
and
timed
them
all,
and
found
there
were
consistent
differences
with
different
sets
of
disc
orifices.
We
restricted
a
given
set
of
disc orifices
to
a
given
emulsion
kind.
We
had
a
file
drawer
with
a
folder
for
each
emulsion
kind,
and
there
were
envelopes
in
there
that
had
the
disc
orifices
in
there.
We
had
to
make
more
of
them,
but
it's
just
a
little
disc
of
metal
with
a
hole
drilled
in
it,
so
it
was
not
expensive.
That
also
gave
us
another
big
drop
in
variability.
A
number
of
things
we
learned
in
next
few
months.
I
mentioned
the
phthalated
gel
that
coagulates
when
the
pH
gets
low.
We
needed
the
percent
phthalation
to
be
correct.
The
gel
plant
couldn't
hit
it
exactly
with
a
single
batch.
They
had
to
blend
batches
together
to
hit
the
4.5%,
plus
or minus
the
of tenth of
a
percent
aim
that
we
were
shooting
for.
That
worked
if
the
batches
were
not
too
far
apart
in
their
percent
phthalation,
but
if
you
had
a
batch
that
was
very
high
in
its
percent
phthalation
and
a
batch
that
was
rather
low
in
its
percent phthalation,
when
you
mix
them
together
and
go
through
the
wash
process,
that
high-phthalation
gel
is
all
going
to
drop
out
to
the
bottom
of
the
kettle,
but
only
part
of
the
low
-phthalation
gel
is
going
to
fall
out.
So
we
had
variable
amounts
of
gel
being
transferred
to
the
next
step
in
the
process,
depending
on
the
decisions
they
made
in mixing
gel
batches.
We
came
up
with
a
rule
that
mixed
batches
had
to
be
within
1%
of
each
other.
It's
not
perfect,
but
it
was
a
big
improvement.
We
mentioned
run time
and
our
restriction
on kettles and
disc orifices.
We
also
improved
our
measuring
of
the
run time.
We
used
to
rely
on
operators
watching
the
clock
as
they
opened
the
valve,
and
watching
the
clock
as
the
last
little
bit
of
silver
nitrate
ran
out.
We
put
a
switch
on
the
valve
so that
the
clock
started
then,
and
we
had
a
sensor
in
the
line
so
that
when
the
last
little
bit
ran
out,
it
stopped
the
clock.
Better
data
always
helps.
We
learned,
quite
by
accident,
that
if
you
have
a
delay
when
you're
setting
up in
the
process
and
you
cook
the
gel
a
little
bit
longer
than
usual,
it
loses
buffering
capacity.
With
less
buffering,
when
you
add
acid
to
coagulate
the
gel,
that
pH
is
going
to
drop
farther
than
what
you
really
wanted.
We
discovered
this
during
the
trend chart phase
in
our
emulsions.
One
of
the
operators
looked
at
the
data
and
said,
"This
lot
's
different.
All
the
pHs
are
different o
n
this
particular
batch."
Looked
at
it
and
agreed,
"Yeah,
that's
different.
There's
something
really
unique
about
this
batch."
And
conversations with
the
operator,
"
Do
you
know
of
anything
that
happened
different
on
this
particular
batch?"
He
volunteered, "W
ell,
I
had
a
problem
with
the
ammonia
jar,
"and
I
had
to
dump
it
and
start
over
again,
"so
there was
a
delay
in
getting
started."
Another
operator
chimed
in,
"I
had
a
batch
that
looked
like
that
in
terms
of
the
pHs
a
while
back.
"Let's
go
look
at
that."
And
we
dug
out
the
data
for
that
one,
and
the
timestamps
said,
yeah,
there
was
a
delay
in
starting
that
one.
The
pHs all were
more
variable.
They
were
farther
off.
The
higher pHs were higher
and the
low
pHs
were
lower.
So
we
did
more
experiments
on
the
bench
scale
and
found, yeah,
there
was
a
real
effect
there.
And
the
chemist
volunteered
that,
yeah,
they
knew
it
could
happen,
but
they
had
no
idea
that it
happened
this
fast.
So
we
put
a
limit
on
the
gel
prep,
a
time
limit.
If
you
haven't
started
using
it
within
a
given
time
frame,
you
dump
it
and
start
over.
It
really
does
make
sense
to
dump
a
couple
hundred dollars worth
of
gel
and
salt
rather
than
adding
tens
of
thousands
of
dollars
worth
of
silver
to
that
kettle
and
running
a
risk
of
dumping
that.
We
also
learned
in
the
washing
process,
it
was
better
to
be
consistent
and
imperfect
than
strive
for
perfection
and
getting
greater
variability.
That
is,
our
operators
had
long
been
told
in
that
washing
process,
the
good
stuff'
s
in
the
bottom
of
the
kettle.
That
silver
and
gel
down
there
at
the
bottom,
that's
the
good
stuff.
Don't
you
dare
suck
any
of
that
out
in
the
siphon
wand,
but
get
all
of
the
supernatant
liquid
you
possibly
can
out.
The
only
problem
was
the
coagulation
didn't
always
have
the
same
density.
Sometimes
it was
nice
and
compact
in
the
bottom
of
the
kettle,
and
sometimes
it
was
a
little
fluffy
and
took
up
more
space,
and
you
couldn't
siphon
down
as
far.
Rather
than
siphoning
down
as
far
as
possible,
we
got
more
consistent
results
when
we
specified
exactly
how
far
to
siphon.
For
kind
6001,
we
went
down
to
number
23
on
the
siphon
wand.
We
put
markers.
Basically,
we
put
a
measuring
stick
along
the
siphon
wand
and
had
different
designations
for
different
kinds.
If
we
really
needed
to
get
that
free
ionic
silver
concentration
lower,
we
added
on
an
extra
washing
step.
We
re
dispersed
the
gel
by
adjusting
the
pH
and
then
recoagulated
it.
Looking
at
the
vAg
chart,
this
was
the
initial
area,
and
this
is
when
we
started
restricting
the
kettle.
Not
much
change.
It
looks
like
there
might
be
a
slight
reduction,
but
I
wouldn't
brag
about
that.
In
this
last
phaseâ¦
Well,
okay,
we
restricted
DOs
here,
but
the
real
change is
when
we
add a
standard
siphon
level
rather
than
siphoning
as
far
as
we
can.
That
made
a
real
difference.
We
had
reduced
variability,
so
we
continued
that.
Consistency
is
worth
more
than
the
ultimate
performance,
especially
if
you
can't
repeat
that
ultimate
performance
every
time.
Early
successes
like
these
were
worth
their
weight
in
gold.
The
enthusiasm
and
increase
in
morale
that
that
brought
about
was
possibly
worth
more
than
gold.
It
was
priceless.
Few
things
get
people
more
excited
than
having
them
have
their
own
results
result
in
dramatic
improvements
in
the
product.
How
do
you
sustain
improvements,
and
how
do
you
keep
learning?
Well,
I've
already
showed
you
some
control
charts,
but
SPC
charts
are
really
the
way
to
go.
As
I
indicated,
we
decided
to
make
them
operator
-centered,
as in
put
the
operators
in
control
of
the
process.
Now,
the
people
side
of
SPC
is
probably
more
important
than th
e
statistics.
Some
people
take to
SPC
like
ducks
to
water,
and
some
people,
it's
more
like
cats
to
water.
Now,
I
know
there
are
some
cats
who
actually
can
swim,
but
most
cats
are
going
to
react
more
like
this
one
does.
They're
going
to
get
out
of
that
water
as
fast
as
they
possibly
can.
Now,
that
2nd-
floor
Making
group,
they
were
in
the
ducks
to
water
category.
The
6th-
floor
Making
group,
which
is
what
I
dealt
with
more
often
with
the
Kodachrome products,
I
won't
call
them
cats
to
water,
but
they
were
skeptical.
I
had
to
prove
it
to
them
that
this
was
going
to
work
before
they
really
bought
into
it.
It
took
longer,
but
we
did
get
there.
I
hope
most
of
you
are
familiar
with
the
work
of
W.
Edwards
Deming.
I
was
fortunate
to
attend
one
of
his
four
-day
seminars back in 1992.
Happened
to
be
the
last
year
of
his
life.
He
was
92
at
the
time.
He
was
one
of
the
preeminent
quality
control
and
quality
improvement
experts
in
the
world
at
the
time.
The
Deming
Award
in
Japan
is
named
for
him.
They
still
give
that
award
every
year
to
the
company
showing
a
considerable
improvement
in
quality.
If
you
are
not
familiar
with
him,
first
of
all,
look
up
Deming's
14
points
and
read
them.
Second
of
all,
get
his
book.
Well, he
wrote
several
books.
I
think
Out
of
the
Fear
was
the
last
one.
Read
that
as
well.
But
point
number
8 of
his
14
points
says,
"Eliminate
fear."
Allow
people
to
perform
at
their
best
by
ensuring
that
they
are
not
afraid
to
express
ideas
or
concerns.
Think
about
that
operator
that
volunteered
that
he
had
made
a
mistake
and
that
caused
a
problem
with
that
particular
batch.
He
volunteered
that
freely.
I've
been
other
places
where
operators
are
often
punished
for
making
mistakes,
at
least
reprimanded.
When
that
happens,
they
don't
admit
mistakes.
They
cover
them
up,
and
you
don't
learn
things.
You
got
to
work
against
that.
Everybody
has
to
be
able
to
freely
express
what
happened,
what
good happened,
what
bad
things
happened,
and
to
communicate
freely.
It
opens
up
a
whole
world
of
possible
improvements
when
you
have a
free
exchange
of
information
like
that.
Getting
down
to
the
SPC
charts.
As
I
mentioned,
we
started
with
the
charts
in
control
of
the
operators.
To
do
this,
you
got
to
keep
it
simple.
Not
that
operators
can't
learn to
deal
with
complicated
charts
eventually,
but it's
going
to
take
longer
and
the
training
process
will
be
longer
for
new
employees.
It's
worth
something t
o
keep
it
simple.
We
used
a
chart
of
individuals.
We
omitted
the
moving
range
part
of
the
chart.
I
know
this
may
be
heresy
for
some
quality
control
purists,
but
we
looked
at
that
and
said
it
doubles
the
complexity
of
the
chart.
We
know
it
adds
additional
useful
information,
but
it
doesn't
double
the
amount
of
useful
information,
so
we're
going
to
forgo
that
for
now.
We
also
use
only
two
run
rules.
A
point
was
out
of
control
if
one
point
was
beyond
three
sigma,
or
two
out
of
three
were
beyond
two
sigma.
That was the
only
criteria.
Obviously,
there
are
six
more
traditional
rules,
and
other
sets
have
even
more
run
rules.
We
kept
it
simple,
and
this
kept
us
busy.
We
still
had
a
number
of
out-
of-
control
events
to
investigate,
so
it
kept
us
hopping.
It
was
about
all
we
could
handle.
It's
also
necessary
to
think
about
what
limits
you're
going
to
set.
I
think
that's
actually
on
the
next
slide,
so
I'll
get to that in a
second.
I'm
getting
ahead
of
myself.
We
had
daily
meetings
to
assess
the
charts.
Operators
would
present
them.
They
would
indicate
points
that
were
out
of
control,
and
engineers
were
there
to
comment
about
what
we
know
about
it
and
help
investigations.
Most
importantly,
we
had
celebrations
for
out-
of
-control
situations.
Literally.
When
an
operator
indicated
that
something
was
out
of
control,
we'd
say
thank
you.
Thank
you
for
sharing
that
with
us.
Let's
see
what
we
can
do
working
together
to
find
out
what
happened
and
maybe
fix
something.
Here's
that
slide
that
I
was
getting
ahead
of
myself
with.
How
do
you
set
the
limits?
Purists
insist
that
the
control
limits
must
be
based
on
short-term
variability.
That's
the
definition
of
control.
The
process
is
in
control when
short
-term
variability
matches
long-
term
variability.
Pragmatists
know
that
even
if
you
set
the
limits
a
little
bit
wider,
say
maybe
take
the
first
30
points,
take
the
standard
deviations,
set
the
limits
of
three
sigma,
even
at
that
point,
you're
still
going
to
have
out
-of
-control
points
to
deal
with.
If
alarms
happen
too
often,
they're
going
to
be
ignored.
Set
the
limits
that
are
a
challenge
and
achievable.
You
got
to
walk
that
tightrope.
Now,
I
would
suggest
deciding
how
you're
going
to
set
the
limits
and
then
stick
with
that
method
until you
decide
you
have
to
make
a
change.
Don't
just
do
it
totally
on
a
whim,
but
set
a
definition
that's comfortable
for
your
situation,
and
run
with
it.
Most
of
all,
you
got
to
keep
striving
for
continuous
improvement.
Looking
at
the
results.
Now,
so
far,
I've
just
been
talking
about
the
emulsion
making
operation.
The
next
operation,
the
sensitizing,
is
where
there's
a
considerable
boost
of
the
photographic
properties.
We
test
the
photographic
properties
after
the
sensitizing
step.
The
lot
-to
-lot
standard
deviation
for
the
photographic
speed
dropped
from
about
10 units,
that's
about
a
third of a
stop
for
those
familiar
with
that
photographic
term,
to
about
1 unit.
Actually, it
was
lower
than
that
because
the
standard
deviation
of
the
test
process
was
about
one
unit.
We had
more
than
a
ten
fold
reduction
in
the
standard
deviation.
If
you
want
a
more
impressive
statistic,
we
had
more
than
a hundredfold
reduction
in
the
variance.
The
formula
adjustments
from
one
coating
event
to
the
next
dropped
drastically.
We
had
some
products
that
went
from
six
changes
per
event
to
zero
changes
over
a span
of
six
months.
When
we
started
this,
we
had
no
idea
that
we
could
possibly
get
anything
that
good.
Now,
I
want
to
get
back
to
that
question
I
posed
earlier.
How
do
you
implement
SPC
when
you
only
produce
six
batches
per
year?
One
of
my
particular
products
was
Kodachrome 25.
That
was
a
old
and
venerable
product
that
had
once
been
quite
popular
and
had
been
assigned
to
the
larger
kettles.
But
a
lot
of
the
market
had
switched
to
higher-
speed
products
like
the
Kodachrome 64
or
the
even
higher
-speed
Ektachrome
slide
films.
It
was
a
rather
small
runner
by
the
time
I
was
responsible
for
it.
A
couple
of
emulsion
kinds,
we only produced
six
batches
a
year
.
n equals 6
is
not
very
good
for
statistics.
My
answer
to
the
question
is
what
I
call
creative
swiping
Simply
copy
the
procedures
that
were
found
to
be
useful
on
the
large
-running
constituents
and
copy
the
same
ones
for
the
small
runners.
Now,
they're
the
same
class
of
emulsions.
Same
basic
technology,
gravity
flow
containers,
ammonia
digest,
phthalated g
el,
coagulation
for
washing.
We're
using
the
same
basic
process.
You
find
out
what
works
in
the
large
runners,
apply
it
to
the
small
runners,
and
we
got
similar
improvements.
By
the
way,
these
charts
with
the
blue
background,
these
are
actually
scans
of
35 millimeter
slides
that
I
used
in
an
internal
presentation
at
Kodak
back
in
1988.
They
were
computer
-generated
by
a
firm
called
Genigraphics.
I
think
they
charged
$6
a
slide.
A
lot
of
things
have
changed
since
then.
This
is
looking
at
the
vAg
in finishing.
Previous
data
I'd
shown
was
in
the
making
operation.
Finishing
is
the
sensitizing
step.
This
is
the
last
step
before
you
put
the
emulsions
into
a
coating event.
We
got
a
significant
reduction
in
the
variability.
Now,
contrast
balance.
I
got
to
explain
this.
One
of
the
most
important
things
of
a
color
film
is you
have
three
different
color
records:
red,
green,
and
blue.
You
got
to
keep
the
contrast
of
those
three
different
records
the
same.
They
got
to
match
each
other.
If
they're
all
a
little
bit
off,
it's
not
too
bad,
but
they
got
to
match
each
other,
so
the
contrast
balance
is
the
most
important
parameter.
If
it's
off,
you
could
end
up
with
green
highlights
and
pink
shadows,
There's no
way
people
can
correct
that
in
these
pre
-Photoshop
days.
In 1987,
we
had
a
pretty
wide
spread
of
results
in
this
two-
dimensional
plot.
The
hexagon h
ere
are
the
spec
limits.
This
95%
confidence
ellipse
indicates
there
will
be
more
outside
of
spec.
There's
one
here,
but
there are
going
to
be
more
over
time.
By
1988,
we'd
collapsed
the
variability
down
to
this
nice,
tight
little
group
centered
pretty
close
to
the
center
of
this
hexagon.
This
made
my
work,
my
job,
so
much
easier,
especially
in
terms
of
adjusting
things
from
one
coating
event
to
the
next.
They
became
smaller
and
smaller
adjustments,
and
eventually
not
having
to
adjust.
In
summation,
there
are
many
standard
quality
improvement
tools.
You
don't
have
to
use
all
of
them.
Pick
the
ones
that
fit
your
particular
situation
and
use
them.
Technical
staff
should
define
the
formulas
and
specifications.
We
found
a
huge
benefit
to
having
the
operators
in
control
of
the
process.
They're
going
to
need
plenty
of
support,
but
this
is
the
only
way
to
get
the
really
rapid
feedback
on
what's
actually
going
on.
You
got
to
keep
it
on
the
simple
side
to
make
this
work.
And
most
important
of
all,
you
got
to
celebrate
those
opportunities
to
learn
and
make
improvements.
That's
the
end
of
my
presentation.
Repeat
the
contact
information.
If
anybody
has
questions,
I'll
be
glad
to
answer
them.
Thank
you
very
much.
