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 away…
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 iodide…
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 10⁻¹³ .
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 phase…
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.