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DUANE BONING: So I want
to welcome everybody here

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in Singapore-- or
there in Singapore,

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and here in Cambridge.

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My name is Duane Boning.

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I'll be one of the two
lecturers for our class.

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We'll get into some
of those logistics

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and details in a
minute, but we've

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got some preliminary things.

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00:00:40,470 --> 00:00:45,510
Since we've started
videotaping you already,

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00:00:45,510 --> 00:00:49,620
one thing you need to know
is there is a video recording

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policy.

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00:00:50,580 --> 00:00:54,630
Pretty much everybody
here will be videotaped.

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00:00:54,630 --> 00:00:57,360
If you don't want
to be videotaped,

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there are a couple of
seats here on the right.

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If you do want to
be videotaped, you

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can come and be
accessible and viewable.

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Right at the front, you can see
there's these little red tabs

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on the desk.

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That's in the blind
spot of the video.

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I think some of these
were being handed out

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as you were coming in, but
if you didn't get them,

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here's another copy of
that videotaping policy.

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So what we do is most of these
lectures are, of course, live,

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video linked with Singapore.

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There are occasions
in the calendar

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where it's a holiday in
one place or the other.

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00:01:43,830 --> 00:01:46,380
When it's a holiday
here, we don't meet.

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When it's a whole holiday in
Singapore, but not a holiday

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here, we will still
meet here in Cambridge,

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but the video version
of the local lecture

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will be available on the website
so that folks in Singapore

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can catch up on that.

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00:02:04,330 --> 00:02:06,720
And in fact, we understand
the first one of those

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is this coming Thursday.

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Is everybody ready
for your holiday?

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It's been a long, hard
term already, right?

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Is that right, Singapore?

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OK.

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Yeah, that's the
Chinese New Year,

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so there will be no class
meeting in Singapore

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on Thursday evening.

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Let's see.

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OK.

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00:02:31,910 --> 00:02:39,140
Has everybody found their way
to the Stellar website already?

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00:02:39,140 --> 00:02:43,430
Anybody who has not seen the
Stellar website for this class?

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I'm asking in part because,
if you are not actually

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registered-- let me go to
the Stellar site here--

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oh, this may not be
viewable in Singapore.

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This is accessible only to
those registered in the class,

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I believe.

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So if you're having trouble
getting to the website,

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please email me right away, and
we will add you to the roster,

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even before you get registered.

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It will be important,
because all

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of the materials
for the class are

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deployed through the website.

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In fact, it'll be very rare when
we have any kind of handouts

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to give in class.

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Lecture notes, reading material,
reading back-up, assignments,

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weekly problem sets--
all of that material

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is through the website.

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Now, what I will typically do--

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let me see if I
can get back here--

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usually I will try to have
the PowerPoint slides loaded

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a day before the lecture.

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One thing that I noticed in
a few past years is sometimes

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little groups of students
would work together

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and delegate somebody to
print out the lecture slides

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and bring a set of copies
for their little group.

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So for example, the LFM
students would often

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have one person printing out
that morning or the night

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before, if they were available.

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So you guys can self-organize.

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If you actually like having
any kind of print-out

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to take notes on a copy
of the PowerPoint slides,

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feel free to print those
out or self-organize

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to share that duty.

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Again, we're not going to
be making copies available

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directly in the class.

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So what I want to do, first
off, is talk a little bit

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about the class and the assumed
prerequisites for the class,

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and then we'll come
back and I want

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to get us to know each other.

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I know many of you have
had some classes together.

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Others of you are perhaps
new to each other,

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so want to share a
little bit of experiences

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so we know what the
basin of experience is--

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because this class is meant
to be fairly interactive.

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It is a manufacturing
process control class,

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and one of the best things
about it is many of the students

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in the class have an
awful lot of experience.

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For example, the
students and the leaders

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for manufacturing program,
LFM, are typically

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coming from several years
of industrial experience.

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Similarly, students
have had a lot

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of experience, whether it
be doing experimental work

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with processes in--

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as part of their program,
or what have you.

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So it is meant to
be interactive.

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We depend on you sharing
your experiences,

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your insights, your doubts.

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In many cases, those can be
often the most interesting part

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of the subject--

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say, I tried that-- didn't work.

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Here's why-- because a lot
of the classes about tools

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and experiences for dealing
with manufacturing processes.

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And then we'll get into a
little bit more of the details,

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some of the course schedule,
and some of the other logistics.

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Jumping ahead a little
bit here, there's

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kind of a long chain listed
formally on the course

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catalog for prerequisites--

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says things like 2.008,
or 2.810, or 6152J,

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and then also a couple of other
subjects like 6041 or 15064J.

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What we intend to convey with
these prerequisites is, number

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one, they're not specific
hard prerequisites

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00:06:49,200 --> 00:06:50,460
for those subjects.

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What we mean to convey is
you should have hopefully

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some substantial experience
with some manufacturing process.

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So that's things
like 2810, 6152J.

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So 2810 is essentially the
manufacturing physics subject--

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00:07:08,850 --> 00:07:11,715
manufacturing processes
subject in course two.

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I recognize some
of you for that.

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I think I gave a guest
lecturer in that subject

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on semiconductor manufacturing.

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So that would be one example.

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6152J is a course six,
electrical engineering computer

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science subject on
microfabrication--

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not only semiconductor, but
also MEMS microfabrication.

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And so that would be another
example through coursework,

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where you might have gotten
that kind of experience.

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And then similarly, you
might have actual true

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industrial experience.

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So the goal here is actually
to just go deep enough

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or build on a deep enough
knowledge of some process

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technology.

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This semester of the
subject, I will actually

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be using semiconductor process
technology a little bit

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00:08:06,440 --> 00:08:09,380
more than we have some
semesters in the past

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to illustrate, and
demonstrate, and to get

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00:08:13,220 --> 00:08:16,040
some practice with
some of the concepts

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that we're dealing with here.

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But many of the
problems will also

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deal with macroscopic
processes, from metal

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bending to forming and
other sorts of processes.

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A little later, we expect Dave
Hardt, who is the collector.

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He'll be here.

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And his background
especially emphasizes

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the panoply of mechanical
and broad based process

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technologies, whereas my
experience is a little bit more

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solidly in microfabrication--

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both in semiconductor,
and more recently,

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in micro-electromechanical
systems, or MEMS fabrication.

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So that's one of
the prerequisites.

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Now, the other prerequisite
that we kind of assume--

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and if you don't have, you
might be doing a little bit

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of quick background reading--

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00:09:05,120 --> 00:09:08,870
is indicated by things
like 6041 or 15064,

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and that is some basic
probability and statistics.

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We'll actually be developing
quite a bit of the statistical

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machinery, so if you don't--

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haven't had a full subject
in that, not to worry--

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I recognize many
of you also from--

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is it 2.853, 2.854?

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Get that subject right--

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that's Stan Gershwin's
manufacturing process?

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What is it?

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Manufacturing
systems-- manufacturing

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systems, where we had a two
or three-lecture sequence

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on basic statistics and
statistical modeling.

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We'll actually
revisit some of that,

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so you'll see some of
that again, but then

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00:09:51,170 --> 00:09:54,110
be applying that to
problems of manufacturing.

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00:09:58,840 --> 00:10:00,520
I'll go over this
detail, and then we'll

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00:10:00,520 --> 00:10:05,260
come back to get some
introductions from you guys.

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This semester we actually
have two required textbooks.

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The great thing is a
new book has come out.

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It came out nominally 2006,
but it was only available

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starting last year.

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00:10:18,610 --> 00:10:23,140
And that's a book by Gary
May and Costas Spanos.

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00:10:23,140 --> 00:10:24,390
Gary May is at Georgia Tech.

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00:10:24,390 --> 00:10:29,470
Costas Spanos at UC Berkeley,
and they had developed a course

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00:10:29,470 --> 00:10:32,680
on semiconductor
process control that

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00:10:32,680 --> 00:10:36,190
was very close to a subject
in the dim, dark past

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00:10:36,190 --> 00:10:39,700
that I used to teach dedicated
entirely to semiconductor

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00:10:39,700 --> 00:10:41,030
process control.

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00:10:41,030 --> 00:10:43,090
So finally, we have
a book for that.

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It's a nice condensed book, and
you all should try to get that,

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00:10:47,590 --> 00:10:49,480
because we're going
to have readings

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from this book starting
pretty quickly.

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So you might have
to go to Amazon,

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do two-day shipping or
something like that.

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If somebody has
Amazon Prime, you

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00:11:00,772 --> 00:11:02,230
can use that and
get free shipping.

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I don't know if
any of you do that.

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The other book is Introduction
to Statistical Quality Control.

203
00:11:08,380 --> 00:11:11,080
This is more broad based.

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May and Spanos illustrate
everything the semiconductor

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00:11:14,050 --> 00:11:17,050
process technology.

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00:11:17,050 --> 00:11:22,210
Montgomery is basically a
statistical process control,

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00:11:22,210 --> 00:11:25,000
a little bit of
design of experiment.

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00:11:25,000 --> 00:11:27,400
It really emphasizes the
statistical machinery

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00:11:27,400 --> 00:11:29,750
that we're going to be using.

210
00:11:29,750 --> 00:11:32,680
So you are expected
to either go and get

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00:11:32,680 --> 00:11:34,780
both of those--
both of these books

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have been put on reserve
in the MIT library,

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00:11:38,170 --> 00:11:41,800
so if you don't want to spend
the money, you can, I guess,

214
00:11:41,800 --> 00:11:44,440
do the painful thing of
trying to go to the library

215
00:11:44,440 --> 00:11:45,790
and read there.

216
00:11:49,670 --> 00:11:52,250
At least the Montgomery
book is a great book

217
00:11:52,250 --> 00:11:55,020
to have on your
bookshelf long term.

218
00:11:55,020 --> 00:11:58,190
It'll be a great reference
book throughout your career.

219
00:11:58,190 --> 00:12:00,200
The semiconductor process
control-- certainly,

220
00:12:00,200 --> 00:12:02,600
if you're going in the
semiconductor area, that's

221
00:12:02,600 --> 00:12:05,170
also very useful.

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00:12:05,170 --> 00:12:06,760
OK, so the grading
in the class--

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00:12:06,760 --> 00:12:10,240
the way this works
is we will have--

224
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I think it's something like
eight weekly problem sets,

225
00:12:13,060 --> 00:12:15,402
primarily in the first
2/3 of the class.

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00:12:15,402 --> 00:12:17,110
And then, in the last
third of the class,

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00:12:17,110 --> 00:12:23,090
we stop the problem sets and
you'll go into a team project.

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00:12:23,090 --> 00:12:25,090
The problem sets will
comprise about 40%

229
00:12:25,090 --> 00:12:26,620
of the grade in the class.

230
00:12:26,620 --> 00:12:29,200
We'll have two quizzes--

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00:12:29,200 --> 00:12:33,520
one about a little bit more
than a third of the way through,

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00:12:33,520 --> 00:12:38,570
another one a little bit more
than 2/3 of the way through.

233
00:12:38,570 --> 00:12:42,950
Those are about 40% of
the grade in the class.

234
00:12:42,950 --> 00:12:45,590
The good thing about having
those quizzes during the term

235
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is we do not have a final exam.

236
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Anybody heartbroken about that?

237
00:12:51,310 --> 00:12:52,810
[APPLAUSE]

238
00:12:52,810 --> 00:12:53,950
OK.

239
00:12:53,950 --> 00:12:57,070
However, the reason
we don't is that,

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00:12:57,070 --> 00:12:59,560
in that last third
quarter of the class,

241
00:12:59,560 --> 00:13:01,870
we switched gears a
little bit and ask

242
00:13:01,870 --> 00:13:05,440
you to start applying some of
the techniques and tools that

243
00:13:05,440 --> 00:13:07,600
will have been talked
about through most

244
00:13:07,600 --> 00:13:09,922
of the semester
in a team project.

245
00:13:09,922 --> 00:13:11,380
I'll talk more
about what that team

246
00:13:11,380 --> 00:13:15,110
project is a little bit later.

247
00:13:15,110 --> 00:13:20,880
So that's meant to be a
fairly substantial effort.

248
00:13:20,880 --> 00:13:24,600
The team project is going
to be a team project.

249
00:13:24,600 --> 00:13:30,630
It's going to be typically
three-student teams.

250
00:13:30,630 --> 00:13:35,250
And of course, that should be
very collaborative in nature.

251
00:13:35,250 --> 00:13:38,310
In contrast to that,
the other assignments

252
00:13:38,310 --> 00:13:43,170
are meant to be
individual efforts.

253
00:13:43,170 --> 00:13:46,230
Now, working on
the problem set, I

254
00:13:46,230 --> 00:13:49,410
think it's great to interact,
talk with each other

255
00:13:49,410 --> 00:13:52,230
to understand the problems,
even to bounce off

256
00:13:52,230 --> 00:13:56,190
possible lines of attack
or solution approaches,

257
00:13:56,190 --> 00:13:57,390
but where we mean--

258
00:13:57,390 --> 00:14:00,130
especially on the assignments--
the weekly assignments,

259
00:14:00,130 --> 00:14:02,160
the problems sets--
is everybody should do

260
00:14:02,160 --> 00:14:04,170
their own independent write-up.

261
00:14:04,170 --> 00:14:08,130
I find that writing
and explaining not just

262
00:14:08,130 --> 00:14:10,560
writing down the answer
number, by the way.

263
00:14:10,560 --> 00:14:13,890
We will expect
actual articulation

264
00:14:13,890 --> 00:14:16,770
of your thought process.

265
00:14:16,770 --> 00:14:20,620
That should be an
individual effort.

266
00:14:20,620 --> 00:14:24,170
Now, we'll come back to that
the assignments a little bit.

267
00:14:24,170 --> 00:14:26,860
We'll try to emphasize this,
perhaps, as well a little bit

268
00:14:26,860 --> 00:14:29,050
more on the
assignments themselves.

269
00:14:29,050 --> 00:14:30,610
The perspective I'd
kind of like you

270
00:14:30,610 --> 00:14:33,700
to take on these
weekly problem sets

271
00:14:33,700 --> 00:14:38,740
is not that you're trying to
come up with the answer number

272
00:14:38,740 --> 00:14:43,310
like you might on an exam
or something like that,

273
00:14:43,310 --> 00:14:46,510
where you just needed
the number, but instead,

274
00:14:46,510 --> 00:14:52,600
a little bit of what I think of
as a practicing manufacturing

275
00:14:52,600 --> 00:14:55,060
perspective--

276
00:14:55,060 --> 00:14:57,100
I couldn't call it an
industrial perspective

277
00:14:57,100 --> 00:14:59,890
or an academic perspective,
but the key thing

278
00:14:59,890 --> 00:15:01,360
that you have to
do, and will have

279
00:15:01,360 --> 00:15:03,175
to do throughout your
career is convince.

280
00:15:05,680 --> 00:15:09,040
So you have to convince
us that the answer

281
00:15:09,040 --> 00:15:14,500
that you're putting down makes
sense, why it's reasonable.

282
00:15:14,500 --> 00:15:17,020
So you need to articulate
the thought process,

283
00:15:17,020 --> 00:15:19,370
not just come up with answers.

284
00:15:19,370 --> 00:15:21,370
And that's part of the
reason why we really

285
00:15:21,370 --> 00:15:26,123
want that to be an individual
effort, an individual write-up.

286
00:15:26,123 --> 00:15:27,540
And of course,
everybody's already

287
00:15:27,540 --> 00:15:31,780
gotten to the course URL.

288
00:15:31,780 --> 00:15:35,680
So going backwards a step
here, let me introduce--

289
00:15:35,680 --> 00:15:37,900
I hoped that Dave
would be here by now--

290
00:15:37,900 --> 00:15:40,810
must be having a very
difficult decision point

291
00:15:40,810 --> 00:15:44,930
and in the voting booth
there-- who to vote for.

292
00:15:44,930 --> 00:15:46,240
Again, I'm Duane Boning.

293
00:15:46,240 --> 00:15:49,000
I'm a professor of electrical
engineering and computer

294
00:15:49,000 --> 00:15:50,620
science.

295
00:15:50,620 --> 00:15:51,250
Dave Hardt.

296
00:15:51,250 --> 00:15:52,630
Will be here a little bit later.

297
00:15:52,630 --> 00:15:56,170
Let me introduce for you
the teaching assistant,

298
00:15:56,170 --> 00:15:58,270
Hayden Taylor.

299
00:15:58,270 --> 00:15:59,450
We do have microphones here.

300
00:15:59,450 --> 00:16:01,120
Why don't you say
a couple of words?

301
00:16:01,255 --> 00:16:02,338
HAYDEN TAYLOR: [INAUDIBLE]

302
00:16:02,338 --> 00:16:03,508
DUANE BONING: Yeah-- good.

303
00:16:03,508 --> 00:16:04,300
There's the camera.

304
00:16:04,407 --> 00:16:05,740
HAYDEN TAYLOR: Hello, Singapore.

305
00:16:05,740 --> 00:16:07,930
I'm Hayden.

306
00:16:07,930 --> 00:16:09,260
I'm in electrical engineering.

307
00:16:09,260 --> 00:16:12,430
I work with Duane on
manufacturing approaches

308
00:16:12,430 --> 00:16:14,650
for microfluidic devices.

309
00:16:14,650 --> 00:16:16,540
We work a lot with polymers.

310
00:16:16,540 --> 00:16:19,630
And I'm excited to work
with you all this time.

311
00:16:19,630 --> 00:16:22,840
Feel free to email
me at any time.

312
00:16:22,840 --> 00:16:25,910
I'll be organizing
office hours, and I'll

313
00:16:25,910 --> 00:16:29,680
announce that on the website
when the time has come.

314
00:16:29,680 --> 00:16:32,050
For those of you in
Singapore, I suppose

315
00:16:32,050 --> 00:16:33,820
we'll have to have
virtual office hours.

316
00:16:33,820 --> 00:16:36,100
I'm very happy to talk
over Skype or something

317
00:16:36,100 --> 00:16:39,651
like that, if you want, so
feel free to drop me an email.

318
00:16:39,651 --> 00:16:40,151
Thanks.

319
00:16:44,005 --> 00:16:45,380
DUANE BONING: And
Hayden just got

320
00:16:45,380 --> 00:16:49,077
back a little over a week ago--
is that right-- from Singapore.

321
00:16:49,077 --> 00:16:50,600
HAYDEN TAYLOR: That's right.

322
00:16:50,600 --> 00:16:52,517
DUANE BONING: [? We ?]
spent a couple of weeks

323
00:16:52,517 --> 00:16:54,920
there for some of the
SMA program things.

324
00:16:54,920 --> 00:16:57,350
The core secretary
will be my assistant

325
00:16:57,350 --> 00:17:03,500
over near my office in EECS
headquarters in building 38.

326
00:17:03,500 --> 00:17:05,359
And that's
[? Charlene Blake. ?] So if you

327
00:17:05,359 --> 00:17:07,790
have some administrative
questions,

328
00:17:07,790 --> 00:17:12,140
your best bet is probably
emailing Hayden and me

329
00:17:12,140 --> 00:17:13,460
directly.

330
00:17:13,460 --> 00:17:16,790
I'll be the lead
lecturer this term.

331
00:17:16,790 --> 00:17:18,890
Normally, Dave Hardt
is the lead lecturer.

332
00:17:18,890 --> 00:17:23,569
He's actually nominally on
sabbatical this term, but--

333
00:17:23,569 --> 00:17:26,930
so I'll be taking care of more
of the administrative things,

334
00:17:26,930 --> 00:17:30,300
and he'll get to
give fun lectures.

335
00:17:30,300 --> 00:17:33,260
So if you have administrative
things, please--

336
00:17:33,260 --> 00:17:36,500
probably best to contact
either me or Hayden directly.

337
00:17:36,500 --> 00:17:39,920
If you have questions
or need to drop off,

338
00:17:39,920 --> 00:17:44,030
for example, late
problem sets, that

339
00:17:44,030 --> 00:17:46,830
can be done with [? Charlene. ?]

340
00:17:46,830 --> 00:17:49,260
And we'll have to have to
let [? Charlene ?] know

341
00:17:49,260 --> 00:17:52,900
that she really outdid
herself on the breakfast here.

342
00:17:52,900 --> 00:17:55,620
So at any time, as soon
as you're done with one,

343
00:17:55,620 --> 00:17:57,150
we have lots more
to eat, so feel

344
00:17:57,150 --> 00:18:00,570
free to wander over and
grab a little bit more.

345
00:18:03,320 --> 00:18:05,480
OK, we'll dive back
into a little bit more

346
00:18:05,480 --> 00:18:08,450
about the course, but I thought
it would be a little bit

347
00:18:08,450 --> 00:18:13,370
fun to just quickly go around
and hear a sentence or two

348
00:18:13,370 --> 00:18:14,300
about--

349
00:18:14,300 --> 00:18:17,420
and I'm particularly
interested in what kind

350
00:18:17,420 --> 00:18:21,500
of process background, or
manufacturing background,

351
00:18:21,500 --> 00:18:24,140
or technology
background you have--

352
00:18:24,140 --> 00:18:27,230
or if you don't have much
background, what kind of areas

353
00:18:27,230 --> 00:18:32,430
you're especially interested in,
or potentially interested in.

354
00:18:32,430 --> 00:18:37,610
So we'll do that quickly here
on the Cambridge end first.

355
00:18:37,610 --> 00:18:41,250
I know many of you, again, have
been taking classes together,

356
00:18:41,250 --> 00:18:43,930
so you know each other
better than I you.

357
00:18:43,930 --> 00:18:47,060
I recognize some faces
here a little bit.

358
00:18:47,060 --> 00:18:50,540
But this is part of my way to
get to you as well as for you

359
00:18:50,540 --> 00:18:52,910
guys to get to know each other.

360
00:19:03,520 --> 00:19:07,243
OK, let me go through a
few of the other logistics,

361
00:19:07,243 --> 00:19:09,160
and then we'll start
getting into a little bit

362
00:19:09,160 --> 00:19:13,340
of introductory material.

363
00:19:13,340 --> 00:19:15,340
I think we've already
done some of that.

364
00:19:18,390 --> 00:19:20,813
Let me come back to
the team projects,

365
00:19:20,813 --> 00:19:22,230
because I think
it'll be important

366
00:19:22,230 --> 00:19:25,440
for you folks to be
starting to think very

367
00:19:25,440 --> 00:19:31,770
early about possible projects
and possible team formation,

368
00:19:31,770 --> 00:19:35,400
because that will help--
as you're learning some

369
00:19:35,400 --> 00:19:38,880
of the tools and techniques
in these different kinds

370
00:19:38,880 --> 00:19:43,360
of topical areas, you
can pay more attention,

371
00:19:43,360 --> 00:19:45,210
because you'll
know, OK, I really

372
00:19:45,210 --> 00:19:47,820
want to think about
process diagnosis

373
00:19:47,820 --> 00:19:50,830
for this particular
project, or what have you.

374
00:19:50,830 --> 00:19:53,310
So the typical kinds of topics--

375
00:19:53,310 --> 00:19:56,400
generically, the topics
in these team projects

376
00:19:56,400 --> 00:20:00,060
involve things like
process diagnosis;

377
00:20:00,060 --> 00:20:02,490
process improvement,
often with a little bit

378
00:20:02,490 --> 00:20:07,170
of statistical process
control, detection,

379
00:20:07,170 --> 00:20:11,550
and debug kinds of things;
process optimization

380
00:20:11,550 --> 00:20:13,230
and robustness--

381
00:20:13,230 --> 00:20:15,930
things like use of
design of experiments

382
00:20:15,930 --> 00:20:19,290
to characterize the
process, and then

383
00:20:19,290 --> 00:20:23,460
seek to optimize some
outputs, as well as minimize

384
00:20:23,460 --> 00:20:26,910
some variations and get
to a robust process;

385
00:20:26,910 --> 00:20:29,910
and then a number of more
advanced applications,

386
00:20:29,910 --> 00:20:32,850
perhaps dealing with things
like yield modeling or defect

387
00:20:32,850 --> 00:20:34,020
modeling--

388
00:20:34,020 --> 00:20:36,750
these sorts of projects.

389
00:20:36,750 --> 00:20:39,270
And the basic expectation
in these team projects

390
00:20:39,270 --> 00:20:41,040
is you'll need to
learn a little bit

391
00:20:41,040 --> 00:20:44,820
more background on
the basic process

392
00:20:44,820 --> 00:20:47,550
and what the problem is.

393
00:20:47,550 --> 00:20:53,670
A really interesting aspect of
these projects is it's best--

394
00:20:53,670 --> 00:20:56,540
it really works
nicely if we can tap

395
00:20:56,540 --> 00:21:00,800
into a nice rich set
of existing data,

396
00:21:00,800 --> 00:21:03,590
or in some cases, even
generation of new data

397
00:21:03,590 --> 00:21:06,043
arising out of either
your past experience

398
00:21:06,043 --> 00:21:07,085
or your current research.

399
00:21:10,340 --> 00:21:13,940
So for example, one of the,
say, typical three-team members

400
00:21:13,940 --> 00:21:16,730
might have access to--

401
00:21:16,730 --> 00:21:21,560
hopefully only public,
shareable-- nothing secret--

402
00:21:21,560 --> 00:21:24,740
public data from
their work experience.

403
00:21:28,130 --> 00:21:31,280
Some of you may have
generated a big set of data

404
00:21:31,280 --> 00:21:34,140
for your master's
thesis, or this or that,

405
00:21:34,140 --> 00:21:38,090
and we're only able to look
at this aspect of the problem,

406
00:21:38,090 --> 00:21:39,920
because that was
the key question,

407
00:21:39,920 --> 00:21:41,900
but it was sort
of nagging at you.

408
00:21:41,900 --> 00:21:43,820
There's all this other
rich data that you

409
00:21:43,820 --> 00:21:47,210
would have thought it
interesting to look

410
00:21:47,210 --> 00:21:49,430
at from other perspectives--

411
00:21:49,430 --> 00:21:55,070
things like building very simple
response surface models for.

412
00:21:55,070 --> 00:21:58,000
But you didn't really have the
chance to go down that path.

413
00:21:58,000 --> 00:22:02,030
So keep your mind open,
thinking ahead to the project

414
00:22:02,030 --> 00:22:04,340
as we go out-- go
throughout the term,

415
00:22:04,340 --> 00:22:06,650
and say, oh, that's
an interesting topic.

416
00:22:06,650 --> 00:22:08,510
That's an interesting technique.

417
00:22:08,510 --> 00:22:10,910
That reminds me of a
very interesting data

418
00:22:10,910 --> 00:22:14,750
set that I came across back
a year ago or whatever--

419
00:22:14,750 --> 00:22:16,940
because that might form
the basis for a very

420
00:22:16,940 --> 00:22:18,090
interesting team project.

421
00:22:21,560 --> 00:22:24,180
The output of this
are two parts.

422
00:22:24,180 --> 00:22:27,510
There will be a
world presentation.

423
00:22:27,510 --> 00:22:29,440
So the team will present--

424
00:22:29,440 --> 00:22:31,790
in fact, the last
two class periods,

425
00:22:31,790 --> 00:22:34,820
the very last week of
class, will be dedicated

426
00:22:34,820 --> 00:22:36,680
to these team presentations.

427
00:22:36,680 --> 00:22:39,530
And then there will also
be a project report.

428
00:22:39,530 --> 00:22:41,480
Unlike the problem
sets, where everybody

429
00:22:41,480 --> 00:22:44,540
writes their own
separate problem set,

430
00:22:44,540 --> 00:22:47,630
the team writes
the project report.

431
00:22:47,630 --> 00:22:50,660
So that's one document that
comes together from the team.

432
00:22:53,390 --> 00:22:58,535
Good-- so let me pop back.

433
00:22:58,535 --> 00:23:00,410
We're not going to ask
you who you voted for,

434
00:23:00,410 --> 00:23:04,120
but we figured it was a
tough decision, because it

435
00:23:04,120 --> 00:23:07,102
was taking a little while.

436
00:23:07,102 --> 00:23:08,810
We've already done
all the introductions,

437
00:23:08,810 --> 00:23:11,655
so now you, fortunately,
know most everybody.

438
00:23:11,655 --> 00:23:13,405
DAVID HARDT: I hope
everybody knows that I

439
00:23:13,405 --> 00:23:16,403
got dressed for the occasion.

440
00:23:16,403 --> 00:23:17,320
What am I [INAUDIBLE]?

441
00:23:17,320 --> 00:23:19,612
DUANE BONING: You have to
wear a tie to vote in the US.

442
00:23:19,612 --> 00:23:21,000
You may not know that.

443
00:23:21,000 --> 00:23:22,390
DAVID HARDT: For those of you
who don't already know me,

444
00:23:22,390 --> 00:23:23,200
I'm David Hardt.

445
00:23:23,200 --> 00:23:25,660
And I'm actually on sabbatical
this semester, which

446
00:23:25,660 --> 00:23:27,250
means I don't teach
any classes and I

447
00:23:27,250 --> 00:23:28,420
don't sit on any committees.

448
00:23:28,420 --> 00:23:29,860
DUANE BONING: Why do you wear
a tie if you're on sabbatical?

449
00:23:29,860 --> 00:23:31,660
DAVID HARDT: So I'm here
today to sit on a committee

450
00:23:31,660 --> 00:23:32,535
and do some teaching.

451
00:23:32,535 --> 00:23:34,150
Yeah.

452
00:23:34,150 --> 00:23:37,450
But I welcome you all
to probably the best

453
00:23:37,450 --> 00:23:39,190
class at MIT--

454
00:23:39,190 --> 00:23:43,312
and hello to all of our students
there in Singapore as well.

455
00:23:43,312 --> 00:23:44,770
I hope you're
enjoying the weather.

456
00:23:44,770 --> 00:23:46,240
It's beautiful here.

457
00:23:46,240 --> 00:23:48,130
And the only reason
I'm late is that I

458
00:23:48,130 --> 00:23:50,800
had to drive the other way to
get to the polling station,

459
00:23:50,800 --> 00:23:52,640
and I got trapped by
a huge traffic jam.

460
00:23:52,640 --> 00:23:55,600
So I'm a dedicated voter.

461
00:23:55,600 --> 00:23:56,850
DUANE BONING: Thank you, Dave.

462
00:24:03,000 --> 00:24:05,895
OK, so let's get a
little bit into the--

463
00:24:05,895 --> 00:24:07,770
an overview of what
we're going to be dealing

464
00:24:07,770 --> 00:24:10,560
with throughout the
semester, and then dive

465
00:24:10,560 --> 00:24:14,790
in a little bit on some
concepts and basic background

466
00:24:14,790 --> 00:24:16,180
and terminology.

467
00:24:16,180 --> 00:24:20,100
So some of the key ideas that
we're after in this subject

468
00:24:20,100 --> 00:24:25,610
is really dealing with basically
the problems in manufacturing.

469
00:24:25,610 --> 00:24:28,790
And the biggest problem
of all is really

470
00:24:28,790 --> 00:24:32,710
dealing with quality and
manufacturing variation.

471
00:24:32,710 --> 00:24:36,770
Other aspects of
manufacturing are often

472
00:24:36,770 --> 00:24:42,050
very particular to the specific
process technology that's

473
00:24:42,050 --> 00:24:45,920
arising, but there's a
lot of very generic issues

474
00:24:45,920 --> 00:24:49,580
with variation, and the
control, and elimination,

475
00:24:49,580 --> 00:24:52,550
and modeling of the
process, and the variation,

476
00:24:52,550 --> 00:24:54,230
and ways to reduce it.

477
00:24:54,230 --> 00:24:58,310
So in some sense,
dealing with variation

478
00:24:58,310 --> 00:25:01,880
is one of the key
themes in the subject.

479
00:25:01,880 --> 00:25:04,520
And what we're going to start
with in the first couple

480
00:25:04,520 --> 00:25:07,970
of lectures is basically
dive in, get a little bit

481
00:25:07,970 --> 00:25:11,030
of process physics background.

482
00:25:11,030 --> 00:25:13,820
On Thursday, we'll dive
in a little bit more

483
00:25:13,820 --> 00:25:17,060
on semiconductor fabrication,
and then, on Tuesday, we'll

484
00:25:17,060 --> 00:25:19,280
see a variety--

485
00:25:19,280 --> 00:25:25,230
Dave will talk about a variety
of forging and other process

486
00:25:25,230 --> 00:25:28,970
examples that give a wider
perspective on manufacturing,

487
00:25:28,970 --> 00:25:32,180
and the physics that
are at work, and where

488
00:25:32,180 --> 00:25:38,610
variation naturally, inherently
arises in those processes.

489
00:25:38,610 --> 00:25:41,900
Then, well, once we've got a
little bit of a feel for where

490
00:25:41,900 --> 00:25:43,970
variation comes
from, we want to dive

491
00:25:43,970 --> 00:25:47,750
into some of the techniques for
understanding that and dealing

492
00:25:47,750 --> 00:25:48,350
with it.

493
00:25:48,350 --> 00:25:50,990
And that really gets us
into statistical models.

494
00:25:54,950 --> 00:25:58,310
And we'll talk in great
length about the contrast

495
00:25:58,310 --> 00:26:01,700
between physical models
of the process based

496
00:26:01,700 --> 00:26:07,400
on detailed understanding
of the specific mechanisms

497
00:26:07,400 --> 00:26:12,080
at work versus empirical
modeling of the process based

498
00:26:12,080 --> 00:26:13,310
on data--

499
00:26:13,310 --> 00:26:16,100
data and observations.

500
00:26:16,100 --> 00:26:20,810
The wonderful thing
about data is it's real

501
00:26:20,810 --> 00:26:24,740
and it encompasses all of
both the ideal behavior

502
00:26:24,740 --> 00:26:26,840
and the non-ideal behavior.

503
00:26:26,840 --> 00:26:29,000
And a lot of what we've
dealing with, again,

504
00:26:29,000 --> 00:26:32,000
is the problems, really
trying to understand

505
00:26:32,000 --> 00:26:37,760
where variation is coming from,
what its characteristics are.

506
00:26:37,760 --> 00:26:41,790
If we can start to get a model
for some of that variation,

507
00:26:41,790 --> 00:26:43,280
now we've got a
handle that we can

508
00:26:43,280 --> 00:26:46,270
use to try to eliminate it--

509
00:26:46,270 --> 00:26:48,640
either eliminate it
up front or control it

510
00:26:48,640 --> 00:26:51,930
and compensate for it.

511
00:26:51,930 --> 00:26:54,540
Some of the techniques that
we deal with for dealing with,

512
00:26:54,540 --> 00:26:57,120
again, that data is
building effects models,

513
00:26:57,120 --> 00:26:58,680
designed experiments.

514
00:26:58,680 --> 00:27:02,010
You may have run across
DOE, design of experiments.

515
00:27:02,010 --> 00:27:04,110
It's a form of
statistical technique,

516
00:27:04,110 --> 00:27:07,560
and we will be learning
the details of that

517
00:27:07,560 --> 00:27:10,410
and applying some
of those approaches

518
00:27:10,410 --> 00:27:14,190
with basic input-output
data sets and data models,

519
00:27:14,190 --> 00:27:19,010
both in specifying the
right set of experiments

520
00:27:19,010 --> 00:27:22,670
to perform to very
efficiently sample sample

521
00:27:22,670 --> 00:27:26,290
our process, and then
the ways to model that.

522
00:27:26,290 --> 00:27:28,040
And perhaps one of the
most important ways

523
00:27:28,040 --> 00:27:31,280
of using those empirical models
that we get of the process

524
00:27:31,280 --> 00:27:34,820
is to improve the process, do
process optimization, really

525
00:27:34,820 --> 00:27:38,960
looking for improved operating
points that have reduced

526
00:27:38,960 --> 00:27:43,550
sensitivity to variation, that
really improve the robustness,

527
00:27:43,550 --> 00:27:46,170
as well as meet
multiple objectives.

528
00:27:46,170 --> 00:27:48,860
So we'll do a little bit of
optimization-- multi-objective

529
00:27:48,860 --> 00:27:52,240
optimization coverage as well.

530
00:27:55,180 --> 00:27:58,440
So let's talk a little
bit about, what are the--

531
00:27:58,440 --> 00:28:05,220
oops-- what are the goals of
manufacturing process control

532
00:28:05,220 --> 00:28:06,540
and manufacturing processes?

533
00:28:06,540 --> 00:28:08,460
What are some of the
key characteristics you

534
00:28:08,460 --> 00:28:11,843
would have of a good process?

535
00:28:11,843 --> 00:28:13,260
What are the things
you would like

536
00:28:13,260 --> 00:28:15,960
to either minimize or optimize?

537
00:28:15,960 --> 00:28:21,200
So I already gave you
an advanced look at one.

538
00:28:21,200 --> 00:28:22,250
I'll throw out one.

539
00:28:22,250 --> 00:28:24,230
Of course, we're
very often interested

540
00:28:24,230 --> 00:28:28,190
in minimizing the
cost, and cost rises

541
00:28:28,190 --> 00:28:29,640
in a lot of different ways.

542
00:28:29,640 --> 00:28:31,400
What are some of the
ways that cost arise?

543
00:28:31,400 --> 00:28:34,897
There's the inherent
materials coming in.

544
00:28:34,897 --> 00:28:37,355
What are some of the other
costs associated with a process?

545
00:28:40,010 --> 00:28:41,960
Anybody-- Singapore as well--

546
00:28:41,960 --> 00:28:42,820
AUDIENCE: Labor.

547
00:28:42,820 --> 00:28:44,410
DUANE BONING: Labor, yeah.

548
00:28:44,410 --> 00:28:46,350
AUDIENCE: [INAUDIBLE]
overhead, support.

549
00:28:46,350 --> 00:28:48,660
DUANE BONING: Overhead, support.

550
00:28:48,660 --> 00:28:49,710
AUDIENCE: Time.

551
00:28:49,710 --> 00:28:51,540
DUANE BONING: Time.

552
00:28:51,540 --> 00:28:53,490
Yeah, in fact time process--

553
00:28:53,490 --> 00:28:55,710
time is certainly
a characteristic

554
00:28:55,710 --> 00:28:57,480
that we might want
to optimize for.

555
00:28:57,480 --> 00:28:59,490
That would be a
typical characteristic.

556
00:28:59,490 --> 00:29:02,310
Cost has many of these flavors.

557
00:29:02,310 --> 00:29:03,670
Yes?

558
00:29:03,670 --> 00:29:04,980
AUDIENCE: Setup costs--

559
00:29:04,980 --> 00:29:06,840
DUANE BONING: Setup costs--

560
00:29:06,840 --> 00:29:12,420
so setup costs are
an interesting one.

561
00:29:12,420 --> 00:29:14,850
In various times,
we'll touch on some

562
00:29:14,850 --> 00:29:16,830
of these operational issues.

563
00:29:16,830 --> 00:29:19,950
Many of you have had
[? 2853. ?] We said--

564
00:29:19,950 --> 00:29:22,830
which was really about
manufacturing systems

565
00:29:22,830 --> 00:29:26,970
and things like
scheduling, throughput--

566
00:29:26,970 --> 00:29:28,870
those kinds of issues.

567
00:29:28,870 --> 00:29:32,590
And so time is a little
bit of that as well--

568
00:29:32,590 --> 00:29:36,110
not just the inherent
manufacturing,

569
00:29:36,110 --> 00:29:39,140
physical action on
the product time,

570
00:29:39,140 --> 00:29:42,650
but also transport time-- all
of these kinds of other issues.

571
00:29:42,650 --> 00:29:47,720
This subject will not be
dealing so much with logistics.

572
00:29:47,720 --> 00:29:50,180
It'll really be much
closer to the things

573
00:29:50,180 --> 00:29:53,400
that impact directly
the product itself.

574
00:29:53,400 --> 00:29:59,010
But certainly, setup time
can have an interaction--

575
00:29:59,010 --> 00:30:02,330
processes setup in general
can have a strong impact

576
00:30:02,330 --> 00:30:03,320
on processed quality.

577
00:30:06,550 --> 00:30:10,540
Very often, for example, in
semiconductor processing--

578
00:30:10,540 --> 00:30:13,870
maybe this will resonate
with your experiences

579
00:30:13,870 --> 00:30:15,190
in other processes--

580
00:30:15,190 --> 00:30:19,510
if we change substantially
the process setup

581
00:30:19,510 --> 00:30:22,320
in a particular
piece of equipment,

582
00:30:22,320 --> 00:30:25,440
the first few wafers will
behave very differently

583
00:30:25,440 --> 00:30:28,200
before the equipment
gets to a stable state.

584
00:30:28,200 --> 00:30:30,150
Sometimes we even
run dummy wafers

585
00:30:30,150 --> 00:30:32,370
in order to
equilibrate that setup.

586
00:30:32,370 --> 00:30:33,930
So setup is a good one.

587
00:30:33,930 --> 00:30:36,930
Some more-- what
are other things?

588
00:30:36,930 --> 00:30:37,760
I'm sorry--

589
00:30:37,760 --> 00:30:38,640
AUDIENCE: [INAUDIBLE]

590
00:30:38,640 --> 00:30:39,840
DUANE BONING: [INAUDIBLE].

591
00:30:39,840 --> 00:30:41,610
Certainly.

592
00:30:41,610 --> 00:30:42,510
AUDIENCE: Equipment.

593
00:30:42,510 --> 00:30:44,550
DUANE BONING: Equipment, yep.

594
00:30:44,550 --> 00:30:48,120
We want to use the equipment
as efficiently as possible,

595
00:30:48,120 --> 00:30:49,200
and maintain it.

596
00:30:49,200 --> 00:30:51,720
AUDIENCE: [INAUDIBLE] a good
machine or a bad machine--

597
00:30:51,720 --> 00:30:54,180
DUANE BONING: Good machines
and bad machines-- absolutely.

598
00:30:54,180 --> 00:30:56,610
And in fact, probably
the first third

599
00:30:56,610 --> 00:30:59,790
of the class, the classic
statistical process control,

600
00:30:59,790 --> 00:31:02,610
will be all about detecting
whether the equipment is

601
00:31:02,610 --> 00:31:03,660
behaving as it should.

602
00:31:03,660 --> 00:31:08,425
Is it in a good state
or in a bad state?

603
00:31:08,425 --> 00:31:10,033
AUDIENCE: [INAUDIBLE]

604
00:31:10,033 --> 00:31:11,950
DUANE BONING: So here
we had quality control--

605
00:31:11,950 --> 00:31:12,825
AUDIENCE: And rework.

606
00:31:12,825 --> 00:31:16,480
DUANE BONING:
--and rework, yeah.

607
00:31:16,480 --> 00:31:17,200
AUDIENCE: Energy.

608
00:31:17,200 --> 00:31:19,150
DUANE BONING: Energy, yeah.

609
00:31:19,150 --> 00:31:21,370
Yes, that's a good point.

610
00:31:21,370 --> 00:31:27,760
Actually, I think, dealing
with energy, as well

611
00:31:27,760 --> 00:31:32,230
as the consumption of materials
and the output of materials,

612
00:31:32,230 --> 00:31:33,940
is becoming a more
and more interesting

613
00:31:33,940 --> 00:31:37,760
aspect of manufacturing
processes.

614
00:31:37,760 --> 00:31:38,260
Let's see.

615
00:31:38,260 --> 00:31:38,760
When was it?

616
00:31:38,760 --> 00:31:43,360
Sunday night-- just to
share another anecdote--

617
00:31:43,360 --> 00:31:48,610
I was serving on a panel at a
big semiconductor conference.

618
00:31:48,610 --> 00:31:51,140
Actually, it's the
semiconductor--

619
00:31:51,140 --> 00:31:53,050
biggest circuit
design conference

620
00:31:53,050 --> 00:31:54,400
in the semiconductor industry.

621
00:31:54,400 --> 00:31:58,870
And I was on a panel all
about environmental or green

622
00:31:58,870 --> 00:32:00,130
manufacturing.

623
00:32:00,130 --> 00:32:03,340
And so the reduction
of energy usage

624
00:32:03,340 --> 00:32:07,690
is becoming a very big deal, as
well as the output of things--

625
00:32:07,690 --> 00:32:11,740
in semiconductor side, output
of global warming gases and so

626
00:32:11,740 --> 00:32:13,190
on-- the reduction of those.

627
00:32:13,190 --> 00:32:15,700
So that's a good point.

628
00:32:15,700 --> 00:32:20,020
By the way, I was on a panel
at 7:30 on Sunday evening.

629
00:32:23,060 --> 00:32:26,330
People here-- what
happened on Sunday?

630
00:32:26,330 --> 00:32:27,980
That was Super Bowl here.

631
00:32:27,980 --> 00:32:31,670
I was not very happy to
have to attend the panelist

632
00:32:31,670 --> 00:32:34,550
dinner the second half
of the Super Bowl,

633
00:32:34,550 --> 00:32:39,270
but as it turned out, I'm
very glad I missed it.

634
00:32:39,270 --> 00:32:42,590
OK, so we've hit some of
these other ideas here.

635
00:32:42,590 --> 00:32:44,840
Here's one that
nobody mentioned.

636
00:32:44,840 --> 00:32:50,180
Flexibility is also very key
in manufacturing processes

637
00:32:50,180 --> 00:32:50,750
as well.

638
00:32:50,750 --> 00:32:54,170
We're increasingly finding
that the same manufacturing

639
00:32:54,170 --> 00:32:57,650
line needs to be
adaptable rapidly

640
00:32:57,650 --> 00:33:03,510
to be able to deal with a bigger
product mix than ever before.

641
00:33:03,510 --> 00:33:06,570
So some of the focus
in this subject,

642
00:33:06,570 --> 00:33:09,830
again, is going to really be on
the processes, and variation,

643
00:33:09,830 --> 00:33:12,560
and quality in the processes.

644
00:33:12,560 --> 00:33:18,740
A little bit bigger emphasis is
going to be on unit processes.

645
00:33:18,740 --> 00:33:23,030
The entire aggregation of the
overall sequence of product

646
00:33:23,030 --> 00:33:25,040
to make the overall--

647
00:33:25,040 --> 00:33:28,460
or sequence of processes,
aggregation of the unit

648
00:33:28,460 --> 00:33:32,510
processes to make the entire
process line, and process flow,

649
00:33:32,510 --> 00:33:36,120
and the final
product is important.

650
00:33:36,120 --> 00:33:39,020
We'll touch on some of these
kinds of things of stack up

651
00:33:39,020 --> 00:33:42,470
of quality across
multiple processes,

652
00:33:42,470 --> 00:33:47,240
but we'll be-- end up
emphasizing developing

653
00:33:47,240 --> 00:33:51,230
techniques like statistical
process control, design

654
00:33:51,230 --> 00:33:54,740
of experiments and optimization,
with a little bit more

655
00:33:54,740 --> 00:33:58,910
of an emphasis on
the unit operations.

656
00:33:58,910 --> 00:34:05,350
Part of the reason is more and
more for really high-quality

657
00:34:05,350 --> 00:34:06,520
manufacturing--

658
00:34:06,520 --> 00:34:08,980
the recognition is
you can't simply

659
00:34:08,980 --> 00:34:12,550
inspect or hope to control at
the end of the overall process.

660
00:34:12,550 --> 00:34:18,040
You have to have every unit
process along the way running

661
00:34:18,040 --> 00:34:23,179
as effectively and at the
highest quality possible.

662
00:34:23,179 --> 00:34:25,900
So again, the
number one emphasis

663
00:34:25,900 --> 00:34:28,600
here is going to be
dealing with maximizing

664
00:34:28,600 --> 00:34:31,988
quality, conformance to
specifications, and so on.

665
00:34:31,988 --> 00:34:34,030
And some of these other
things that we've already

666
00:34:34,030 --> 00:34:35,440
talked about here--

667
00:34:35,440 --> 00:34:37,840
things like improving
throughput, improving

668
00:34:37,840 --> 00:34:40,600
flexibility, reducing cost--

669
00:34:40,600 --> 00:34:44,199
those are going to be secondary.

670
00:34:44,199 --> 00:34:47,020
There will be interactions
with some of these topics

671
00:34:47,020 --> 00:34:49,060
that you have run
into or might run

672
00:34:49,060 --> 00:34:51,190
into another in other subjects.

673
00:34:51,190 --> 00:34:57,060
And actually, a very
interesting area of research--

674
00:34:57,060 --> 00:34:59,970
in fact, an active area of
research of Stan Gershwin,

675
00:34:59,970 --> 00:35:02,550
who some of you had in 2853--

676
00:35:02,550 --> 00:35:06,450
is this interaction between
quality and quantity--

677
00:35:06,450 --> 00:35:09,570
that is, typical
operations and how

678
00:35:09,570 --> 00:35:15,390
you manage the sequencing
of parts through the line--

679
00:35:15,390 --> 00:35:19,800
the interaction between
throughput and quality--

680
00:35:19,800 --> 00:35:23,430
for example, dealing
with issues of setup,

681
00:35:23,430 --> 00:35:27,750
dealing with issues of slight
degradations in quality

682
00:35:27,750 --> 00:35:31,440
and how that might impact things
like scheduled maintenance

683
00:35:31,440 --> 00:35:33,060
or unscheduled maintenance.

684
00:35:33,060 --> 00:35:34,950
So it's a very
interesting topic.

685
00:35:34,950 --> 00:35:37,680
We'll occasionally, again,
overlap slightly with that,

686
00:35:37,680 --> 00:35:42,480
but our number one emphasis here
is dealing with the process,

687
00:35:42,480 --> 00:35:44,160
understanding and
modeling the process,

688
00:35:44,160 --> 00:35:47,770
and dealing with
quality and variation.

689
00:35:47,770 --> 00:35:52,000
So here's a few typical
process control problems.

690
00:35:52,000 --> 00:35:53,880
I'll share a couple of these.

691
00:35:53,880 --> 00:35:57,240
And just to wake up
Dave, on the next slide,

692
00:35:57,240 --> 00:35:59,010
we'll let him say a
few words about some

693
00:35:59,010 --> 00:36:01,860
of the other examples.

694
00:36:01,860 --> 00:36:04,500
So here's a typical example.

695
00:36:04,500 --> 00:36:08,220
Probably, in fact, the
number one problem--

696
00:36:08,220 --> 00:36:12,090
or number one challenge in
semiconductor manufacturing

697
00:36:12,090 --> 00:36:15,570
is the minimum feature
size is very, very

698
00:36:15,570 --> 00:36:18,780
small-- becoming smaller with
each technology generation.

699
00:36:18,780 --> 00:36:21,090
The minimum feature
size is typically

700
00:36:21,090 --> 00:36:25,890
the channel length of an
individual MOS transistor.

701
00:36:25,890 --> 00:36:30,690
That's often the most critical
parameter, and it varies.

702
00:36:30,690 --> 00:36:32,940
With current
technology, we're down

703
00:36:32,940 --> 00:36:35,880
in heavy-duty manufacturing
at 90 nanometers.

704
00:36:35,880 --> 00:36:38,430
Some of the leading
edge manufacturers

705
00:36:38,430 --> 00:36:43,740
have gate or channel patterned
lengths of 65 nanometer.

706
00:36:43,740 --> 00:36:46,660
Occasionally, you'll hear
those terms thrown out.

707
00:36:46,660 --> 00:36:50,730
What that means is the minimum
feature size being patterned

708
00:36:50,730 --> 00:36:55,460
is about 65 nanometers wide.

709
00:36:55,460 --> 00:36:56,480
That's small.

710
00:36:56,480 --> 00:36:57,590
That's tiny.

711
00:36:57,590 --> 00:37:00,830
And as we continue to
scale, that variability

712
00:37:00,830 --> 00:37:07,400
in the width of that is becoming
tougher and tougher to achieve.

713
00:37:07,400 --> 00:37:13,550
So very often, there will be
challenges on the manufacturing

714
00:37:13,550 --> 00:37:16,070
line to detect--

715
00:37:16,070 --> 00:37:18,500
monitor, detect,
and then compensate

716
00:37:18,500 --> 00:37:20,030
for those kinds of variability.

717
00:37:22,820 --> 00:37:25,670
An emerging technology--
here's an interesting one

718
00:37:25,670 --> 00:37:28,020
that connects up
with, for example,

719
00:37:28,020 --> 00:37:31,190
some of the Singapore MIT
Alliance research efforts.

720
00:37:31,190 --> 00:37:36,960
A DNA diagnostic chip might
have uneven flow channels.

721
00:37:36,960 --> 00:37:41,960
So for example, here, these
are often microfluidic devices

722
00:37:41,960 --> 00:37:46,190
manufactured through
embossing processes, where

723
00:37:46,190 --> 00:37:48,770
one might be using
a polymer and trying

724
00:37:48,770 --> 00:37:52,730
to create channels that
might be 10 microns wide, 10

725
00:37:52,730 --> 00:37:54,080
microns deep--

726
00:37:54,080 --> 00:37:58,280
and maybe, in some places,
very, very narrow, for example,

727
00:37:58,280 --> 00:37:59,810
or very, very shallow--

728
00:37:59,810 --> 00:38:02,840
maybe 20 to 40 nanometers deep.

729
00:38:02,840 --> 00:38:05,480
I mention those because
those are actually

730
00:38:05,480 --> 00:38:09,440
real numbers for some
of the researchships

731
00:38:09,440 --> 00:38:15,720
that are being developed here at
MIT in electrical engineering,

732
00:38:15,720 --> 00:38:18,410
mechanical engineering, and
elsewhere-- very interesting

733
00:38:18,410 --> 00:38:22,040
properties, when one gets
down to that small dimension.

734
00:38:22,040 --> 00:38:23,630
And some of those
properties depend

735
00:38:23,630 --> 00:38:28,400
critically on those
dimensions, as you can imagine.

736
00:38:28,400 --> 00:38:31,220
So in fact, the
manufacturing process problem

737
00:38:31,220 --> 00:38:34,970
is, how do you
get processes that

738
00:38:34,970 --> 00:38:36,600
work in a controllable fashion?

739
00:38:36,600 --> 00:38:43,220
How do you inspect and
detect feature sizes,

740
00:38:43,220 --> 00:38:47,300
geometric parameters,
roughness of the geometry,

741
00:38:47,300 --> 00:38:51,950
as well as some other
material properties in order

742
00:38:51,950 --> 00:38:54,530
to achieve the
optimal functionality

743
00:38:54,530 --> 00:38:56,630
that one might need--

744
00:38:56,630 --> 00:39:03,250
for example, controlling the
flow of individual DNA from one

745
00:39:03,250 --> 00:39:08,890
place to another through these
incredibly tiny, tiny channels?

746
00:39:08,890 --> 00:39:10,630
What's another example?

747
00:39:10,630 --> 00:39:13,130
Somebody mentioned assembly.

748
00:39:13,130 --> 00:39:16,480
Assembly is a
manufacturing process,

749
00:39:16,480 --> 00:39:22,040
and the worst example of
this is that toys that come

750
00:39:22,040 --> 00:39:24,980
disassembled-- they
never fit, at least when

751
00:39:24,980 --> 00:39:29,180
I try to assemble them at home.

752
00:39:29,180 --> 00:39:36,350
Geometric fit and how those
imperfections can build up,

753
00:39:36,350 --> 00:39:37,430
even if--

754
00:39:37,430 --> 00:39:41,150
an interesting aspect--
even if a few parts

755
00:39:41,150 --> 00:39:44,600
are close to nominal when
you try to put them together,

756
00:39:44,600 --> 00:39:49,918
sometimes the aggregate
doesn't work out so well.

757
00:39:49,918 --> 00:39:51,460
And then there may
be other example--

758
00:39:51,460 --> 00:39:55,515
for example, very high-density
electrical connectors.

759
00:39:55,515 --> 00:39:57,940
And I think, Dave,
you had some example--

760
00:39:57,940 --> 00:39:59,503
this comes out of
an LFM thesis, or?

761
00:39:59,503 --> 00:40:00,920
DAVID HARDT: No,
this was actually

762
00:40:00,920 --> 00:40:03,690
research we did [INAUDIBLE]
a number of years ago.

763
00:40:03,690 --> 00:40:05,970
And it's actually just like--

764
00:40:05,970 --> 00:40:07,470
it's actually a
trend with all these

765
00:40:07,470 --> 00:40:11,333
that [INAUDIBLE] for years.

766
00:40:11,333 --> 00:40:13,420
Of course, [INAUDIBLE].

767
00:40:13,420 --> 00:40:17,490
DUANE BONING: Can you guys
in Singapore hear Dave?

768
00:40:17,490 --> 00:40:18,000
No?

769
00:40:18,000 --> 00:40:19,208
AUDIENCE: No, we cannot hear.

770
00:40:19,208 --> 00:40:20,317
AUDIENCE: [INAUDIBLE]

771
00:40:20,317 --> 00:40:24,120
DAVID HARDT: [INAUDIBLE]
mic's not working.

772
00:40:24,120 --> 00:40:28,200
Just because this
is sort of a theme--

773
00:40:28,200 --> 00:40:30,990
you can imagine electrical
connectors-- big heavy ones,

774
00:40:30,990 --> 00:40:34,560
like used in cars or in old
electronics back in the tube

775
00:40:34,560 --> 00:40:37,740
days, where you could grab hold
of some of these connectors

776
00:40:37,740 --> 00:40:38,940
with your hand--

777
00:40:38,940 --> 00:40:42,250
just the metal part itself.

778
00:40:42,250 --> 00:40:45,300
Now, as electronics has
become more and more dense,

779
00:40:45,300 --> 00:40:47,130
as things have become
smaller and smaller,

780
00:40:47,130 --> 00:40:50,310
the requirement for higher and
higher density of connectors--

781
00:40:50,310 --> 00:40:53,803
if not just to handle
these high-density chips,

782
00:40:53,803 --> 00:40:56,220
but just look at the back of
your computer-- some of those

783
00:40:56,220 --> 00:40:59,100
connectors there-- particularly
the interconnect type

784
00:40:59,100 --> 00:41:00,870
of connectors.

785
00:41:00,870 --> 00:41:02,460
Well, the industry
that made that

786
00:41:02,460 --> 00:41:06,090
made it the same way for
years, and it worked fine.

787
00:41:06,090 --> 00:41:10,860
And it's a great example of
how variability is actually

788
00:41:10,860 --> 00:41:12,340
a relative term.

789
00:41:12,340 --> 00:41:16,440
And so the variability
was relatively small.

790
00:41:16,440 --> 00:41:19,140
It was small relative to
the characteristic dimension

791
00:41:19,140 --> 00:41:20,100
that you needed.

792
00:41:20,100 --> 00:41:24,330
But as that shrunk down,
these major manufacturers

793
00:41:24,330 --> 00:41:26,100
found out that they
really couldn't

794
00:41:26,100 --> 00:41:28,373
use their old
technology to meet this.

795
00:41:28,373 --> 00:41:30,540
Of course, they went through
a lot of the procedures

796
00:41:30,540 --> 00:41:33,180
we're going to go through
and they improved things,

797
00:41:33,180 --> 00:41:34,920
but they couldn't
meet those dimensions,

798
00:41:34,920 --> 00:41:38,772
and had to make a
technology change as well.

799
00:41:38,772 --> 00:41:40,230
DUANE BONING: This
is my sneaky way

800
00:41:40,230 --> 00:41:42,900
to get an extra [INAUDIBLE].

801
00:41:42,900 --> 00:41:45,660
DAVID HARDT: Also, on this
minimum feature size--

802
00:41:45,660 --> 00:41:47,370
and I'd ask Duane
to comment on this--

803
00:41:47,370 --> 00:41:51,210
I was once with a
gentleman from IBM Research

804
00:41:51,210 --> 00:41:53,280
who told me they were
just now-- this was maybe

805
00:41:53,280 --> 00:41:54,930
five, six years ago--
just now getting

806
00:41:54,930 --> 00:41:56,280
into some of the
advanced techniques

807
00:41:56,280 --> 00:41:58,860
that we're going to talk about
near the end of the term here.

808
00:41:58,860 --> 00:42:00,390
And I was a little
bit surprised,

809
00:42:00,390 --> 00:42:03,540
but then he pointed out,
back when the feature

810
00:42:03,540 --> 00:42:05,730
size on the chips was large--

811
00:42:05,730 --> 00:42:09,240
I don't know what large
was-- micron scale or several

812
00:42:09,240 --> 00:42:10,380
microns--

813
00:42:10,380 --> 00:42:14,340
the inherent variability
of the processes was fine--

814
00:42:14,340 --> 00:42:15,910
fine to manufacture
these things.

815
00:42:15,910 --> 00:42:17,850
But when you get down
to the nanometer range,

816
00:42:17,850 --> 00:42:22,120
all of a sudden, you have to
look at some other techniques.

817
00:42:22,120 --> 00:42:26,370
So there are these
timeless things,

818
00:42:26,370 --> 00:42:28,710
like toys that
don't fit together

819
00:42:28,710 --> 00:42:31,410
and other things related
to larger dimensions,

820
00:42:31,410 --> 00:42:34,470
but then this idea of the
ever-shrinking mechanical

821
00:42:34,470 --> 00:42:38,010
dimensions of things leads to
an ever-increasing importance

822
00:42:38,010 --> 00:42:40,683
of process control.

823
00:42:40,683 --> 00:42:41,850
So our future is guaranteed.

824
00:42:41,850 --> 00:42:44,220
DUANE BONING: I'll skip
ahead, because maybe [? not ?]

825
00:42:44,220 --> 00:42:47,250
going through all of these, but
if there's another one or two

826
00:42:47,250 --> 00:42:49,708
of these from your experience
that you wanted [INAUDIBLE]..

827
00:42:49,708 --> 00:42:54,930
DAVID HARDT: Well, these are
three large-scale issues.

828
00:42:54,930 --> 00:42:56,790
This is usually where
I ask if anybody here

829
00:42:56,790 --> 00:43:00,337
works for Boeing or any
other airframe manufacturer.

830
00:43:00,337 --> 00:43:01,920
DUANE BONING: We
have some automotive.

831
00:43:01,920 --> 00:43:03,180
We have some [INAUDIBLE].

832
00:43:03,180 --> 00:43:04,380
DAVID HARDT: Yeah.

833
00:43:04,380 --> 00:43:06,720
The automotive actually
does a lot better

834
00:43:06,720 --> 00:43:09,120
on variation control,
because they have--

835
00:43:09,120 --> 00:43:12,450
as you'll see, it helps
to have some volume

836
00:43:12,450 --> 00:43:15,330
and to be able to learn
and to get your processes

837
00:43:15,330 --> 00:43:16,320
in steady state.

838
00:43:16,320 --> 00:43:19,800
Things like airframes are
still sort of one-off.

839
00:43:19,800 --> 00:43:21,805
And because of the
large dimension there,

840
00:43:21,805 --> 00:43:24,180
it's really not an unpleasant--
it's not a pleasant thing

841
00:43:24,180 --> 00:43:27,443
to watch two halves of an
airplane being put together--

842
00:43:27,443 --> 00:43:29,860
although they've gotten a lot
better than they used to be.

843
00:43:29,860 --> 00:43:33,720
What was it they used to say--
that the number of thousands

844
00:43:33,720 --> 00:43:36,600
of pounds [INAUDIBLE]
flying in a 747?

845
00:43:36,600 --> 00:43:39,092
[INAUDIBLE] we're also
going to talk later--

846
00:43:39,092 --> 00:43:40,800
actually, I'm not sure
we will this term,

847
00:43:40,800 --> 00:43:43,200
but there's an
interesting LFM thesis

848
00:43:43,200 --> 00:43:45,708
done on these plastic throttle
bodies for fuel injection.

849
00:43:45,708 --> 00:43:47,250
This is a little
bit different issue.

850
00:43:47,250 --> 00:43:50,690
This was an entirely different
way of making a classical part.

851
00:43:50,690 --> 00:43:54,390
It had been made for
years out of aluminum--

852
00:43:54,390 --> 00:43:56,670
machined aluminum--
well-defined process,

853
00:43:56,670 --> 00:43:58,525
well-understood process control.

854
00:43:58,525 --> 00:44:00,150
Then, for good and
sufficient reasons--

855
00:44:00,150 --> 00:44:02,370
mainly weight and
production economy--

856
00:44:02,370 --> 00:44:05,220
they went to injection
molded parts,

857
00:44:05,220 --> 00:44:07,170
and variation became
a big problem.

858
00:44:07,170 --> 00:44:09,990
And how to get rid of
it was a-- was and still

859
00:44:09,990 --> 00:44:11,050
is an interesting issue.

860
00:44:11,050 --> 00:44:15,900
So a number of things come
up, often because of change--

861
00:44:15,900 --> 00:44:18,500
not always just because
of things being in stasis.

862
00:44:18,500 --> 00:44:19,500
DUANE BONING: Thank you.

863
00:44:24,120 --> 00:44:29,070
So again, some of
these points that Dave

864
00:44:29,070 --> 00:44:32,492
made about, for example, the
question or example you posed

865
00:44:32,492 --> 00:44:34,950
on semiconductor manufacturing
we'll talk a little bit more

866
00:44:34,950 --> 00:44:36,450
about on Thursday,
because it was

867
00:44:36,450 --> 00:44:38,130
a very interesting
transformation

868
00:44:38,130 --> 00:44:42,960
from defect-oriented problems
as the real yield and quality

869
00:44:42,960 --> 00:44:46,170
limiter to dimensional control.

870
00:44:46,170 --> 00:44:54,020
And essentially, parametric
variation is the killer now.

871
00:44:54,020 --> 00:44:56,760
OK, so one of the things--

872
00:44:56,760 --> 00:45:00,960
this connects up again also to
a point that Dave just made--

873
00:45:00,960 --> 00:45:05,820
is that there is an evolution
of manufacturing process control

874
00:45:05,820 --> 00:45:07,920
many industries
had gone through.

875
00:45:07,920 --> 00:45:10,710
And you will often
see a trajectory

876
00:45:10,710 --> 00:45:15,570
where an industry may actually
start with a process that

877
00:45:15,570 --> 00:45:18,270
is not all that stable,
and they essentially

878
00:45:18,270 --> 00:45:21,390
have to inspect every
single part that comes out--

879
00:45:21,390 --> 00:45:25,950
100% inspection may have
relatively high scrap rates--

880
00:45:25,950 --> 00:45:28,860
even a few percent,
for example--

881
00:45:28,860 --> 00:45:35,330
with low throughput, and
correspondingly high cost.

882
00:45:35,330 --> 00:45:38,300
So this might be thought
to be a characteristic

883
00:45:38,300 --> 00:45:43,430
of immature processes,
but it's also

884
00:45:43,430 --> 00:45:48,200
a characteristic of
incredibly complex processes.

885
00:45:48,200 --> 00:45:50,810
So you would really
like to avoid that.

886
00:45:50,810 --> 00:45:53,510
Quick question for-- well, some
of the guys from semiconductor

887
00:45:53,510 --> 00:45:54,590
know this.

888
00:45:54,590 --> 00:45:59,060
Do we have 100% inspection
of semiconductor chips today?

889
00:46:02,830 --> 00:46:04,412
What do you think?

890
00:46:04,412 --> 00:46:05,870
Do you think every
single chip that

891
00:46:05,870 --> 00:46:09,140
comes off the line gets
inspected, measured,

892
00:46:09,140 --> 00:46:10,910
verified that it produces?

893
00:46:10,910 --> 00:46:13,910
Do we have high costs or--

894
00:46:16,990 --> 00:46:20,060
somebody who knows the answer--

895
00:46:20,060 --> 00:46:23,800
well, I think perhaps it
depends on what the chip is.

896
00:46:23,800 --> 00:46:25,690
You think every
single microprocessor

897
00:46:25,690 --> 00:46:30,940
chip gets inspected before it
gets packaged and put in a PC?

898
00:46:30,940 --> 00:46:32,470
You bet.

899
00:46:32,470 --> 00:46:34,930
You bet.

900
00:46:34,930 --> 00:46:36,925
On the other hand--

901
00:46:36,925 --> 00:46:37,800
AUDIENCE: [INAUDIBLE]

902
00:46:37,800 --> 00:46:39,425
DUANE BONING: Oh, absolutely.

903
00:46:46,322 --> 00:46:49,310
A microprocessor chip might sell
for a couple hundred dollars,

904
00:46:49,310 --> 00:46:50,550
so it's worth it.

905
00:46:50,550 --> 00:46:53,720
Now, if you're talking about
a semiconductor chip that

906
00:46:53,720 --> 00:46:57,770
is a discrete diode
worth probably

907
00:46:57,770 --> 00:47:01,160
a fraction of a penny in
terms of the manufacturing

908
00:47:01,160 --> 00:47:03,380
cost, yeah, you--

909
00:47:03,380 --> 00:47:06,560
it's a much more simple
and less complex thing,

910
00:47:06,560 --> 00:47:09,740
and you probably don't
need 100% inspection there.

911
00:47:09,740 --> 00:47:14,330
But most integrated circuits,
at the end of the day,

912
00:47:14,330 --> 00:47:16,630
still need inspection
at the end.

913
00:47:16,630 --> 00:47:17,436
Yeah, Hayden?

914
00:47:17,936 --> 00:47:19,686
HAYDEN TAYLOR: I thought
it might be worth

915
00:47:19,686 --> 00:47:21,465
remarking that I think--

916
00:47:21,465 --> 00:47:22,590
DUANE BONING: Speak loudly.

917
00:47:22,590 --> 00:47:25,610
AUDIENCE: Can everyone
hear me in Singapore?

918
00:47:25,610 --> 00:47:27,233
No.

919
00:47:27,233 --> 00:47:28,275
DUANE BONING: Just shout.

920
00:47:28,775 --> 00:47:29,610
HAYDEN TAYLOR: OK.

921
00:47:29,610 --> 00:47:33,060
I think Intel, when
they test their chips,

922
00:47:33,060 --> 00:47:36,480
they determine what
the maximum operating

923
00:47:36,480 --> 00:47:39,570
frequency of any given
chip is, and they sort them

924
00:47:39,570 --> 00:47:42,460
so the chips that happen to
operate at the faster end

925
00:47:42,460 --> 00:47:44,820
are put in more
expensive machines,

926
00:47:44,820 --> 00:47:47,580
and those that are slower
go in the cheaper machines.

927
00:47:47,580 --> 00:47:50,160
So they actually get
some extra benefit

928
00:47:50,160 --> 00:47:53,077
from the testing process.

929
00:47:53,077 --> 00:47:53,910
DUANE BONING: Right.

930
00:47:53,910 --> 00:47:56,340
So based on the quality
or the performance,

931
00:47:56,340 --> 00:48:01,000
they can bin the chips and
get differential pricing.

932
00:48:01,000 --> 00:48:05,370
Of course, they would be most
beneficial if all of the chips

933
00:48:05,370 --> 00:48:07,200
operated at the high end.

934
00:48:07,200 --> 00:48:12,240
And so in some sense,
that's both a limitation

935
00:48:12,240 --> 00:48:14,040
and an advantage.

936
00:48:14,040 --> 00:48:17,970
You can get a premium for
the highest performing.

937
00:48:17,970 --> 00:48:22,560
But it's a great example
of the range of variation

938
00:48:22,560 --> 00:48:25,320
and the effective, ultimately,
on the end performance.

939
00:48:29,380 --> 00:48:32,140
A next step typically
in some of the evolution

940
00:48:32,140 --> 00:48:35,590
of these manufacturing
processes involve--

941
00:48:35,590 --> 00:48:40,900
whoops-- involve rework,
both at the end of the line,

942
00:48:40,900 --> 00:48:44,110
but more often pushing
down to unit processes--

943
00:48:44,110 --> 00:48:46,810
where, if you could
do a inspection,

944
00:48:46,810 --> 00:48:48,610
you still have limited
control perhaps

945
00:48:48,610 --> 00:48:50,500
over the individual
unit process,

946
00:48:50,500 --> 00:48:53,140
but you can inspect it,
determine something went wrong.

947
00:48:53,140 --> 00:48:56,170
And if there is a possibility
of fixing it then and there,

948
00:48:56,170 --> 00:48:59,710
now you've got a big advantage.

949
00:48:59,710 --> 00:49:03,460
We already talked about also
high durability at changeover,

950
00:49:03,460 --> 00:49:06,055
and that's an example
we already talked about,

951
00:49:06,055 --> 00:49:10,180
about how cost rate and
flexibility are linked.

952
00:49:10,180 --> 00:49:14,440
Of course, all of these--
if you can get quality up,

953
00:49:14,440 --> 00:49:17,020
get to higher and higher yield--

954
00:49:17,020 --> 00:49:20,620
that has a dramatic effect,
perhaps the strongest effect

955
00:49:20,620 --> 00:49:25,720
on overall throughput
and the optimal output

956
00:49:25,720 --> 00:49:27,520
from your manufacturing plant--

957
00:49:27,520 --> 00:49:30,580
especially in those industries
where yields may not

958
00:49:30,580 --> 00:49:33,700
be all that high.

959
00:49:33,700 --> 00:49:36,940
For example, in many of the
semiconductor processes,

960
00:49:36,940 --> 00:49:41,500
if you have 90% yield on a
very complex microprocessor,

961
00:49:41,500 --> 00:49:43,080
you're doing pretty well.

962
00:49:43,080 --> 00:49:44,930
That's not great, is it?

963
00:49:44,930 --> 00:49:50,950
Can you imagine 90% output of--

964
00:49:50,950 --> 00:49:56,580
90% functioning output
of syringe needles

965
00:49:56,580 --> 00:50:00,270
that we saw, where 10% of them
were defective in some way?

966
00:50:00,270 --> 00:50:02,400
That wouldn't be very
satisfying, I think.

967
00:50:04,930 --> 00:50:08,000
OK, so one of the
things that we're

968
00:50:08,000 --> 00:50:11,420
going to do a little bit in
the next couple of lectures--

969
00:50:11,420 --> 00:50:13,910
and I'm going to talk about
a little bit generically

970
00:50:13,910 --> 00:50:17,240
to set the stage for that last
10 minutes or so of class--

971
00:50:17,240 --> 00:50:22,550
is characteristics of
manufacturing processes--

972
00:50:22,550 --> 00:50:25,520
in fact, something of
a taxonomy that Dave

973
00:50:25,520 --> 00:50:30,590
will cover on
Thursday based on some

974
00:50:30,590 --> 00:50:34,850
of the inherent characteristics
of the physical action

975
00:50:34,850 --> 00:50:37,460
of manufacturing processes.

976
00:50:37,460 --> 00:50:39,110
And we've already
chatted a little bit,

977
00:50:39,110 --> 00:50:42,680
and we'll see more as we
dive into those processes

978
00:50:42,680 --> 00:50:46,500
about why they don't
always work correctly.

979
00:50:46,500 --> 00:50:49,760
So here I'm going to try to get
a little bit of the terminology

980
00:50:49,760 --> 00:50:53,330
out and give you a little bit
of a framework for thinking

981
00:50:53,330 --> 00:50:56,240
about the processes,
and then some reflection

982
00:50:56,240 --> 00:50:59,720
on the different
segments of the subject

983
00:50:59,720 --> 00:51:03,290
that we mentioned are
coming up, and how

984
00:51:03,290 --> 00:51:08,910
they relate to a very-high level
generic view of the process.

985
00:51:08,910 --> 00:51:10,860
So the key idea in a
process, of course,

986
00:51:10,860 --> 00:51:15,830
is that we have some part that
we want to produce at the end.

987
00:51:15,830 --> 00:51:18,680
We do that by working
on a work piece.

988
00:51:18,680 --> 00:51:22,970
There is some physical material
that we are transforming

989
00:51:22,970 --> 00:51:25,100
in some important way.

990
00:51:25,100 --> 00:51:26,930
We are changing the geometry.

991
00:51:26,930 --> 00:51:30,950
We are changing the material
properties of that part.

992
00:51:30,950 --> 00:51:32,250
How do we do that?

993
00:51:32,250 --> 00:51:35,520
Well, we have to
subjected to some process,

994
00:51:35,520 --> 00:51:42,040
and we do that through
equipment, and in some cases,

995
00:51:42,040 --> 00:51:43,600
parts of the
equipment-- things like

996
00:51:43,600 --> 00:51:48,310
tooling that come in
contact with the part.

997
00:51:48,310 --> 00:51:53,170
So some examples of broadly,
equipment-- and here,

998
00:51:53,170 --> 00:51:55,960
equipment we may even
rise a little bit

999
00:51:55,960 --> 00:52:01,990
as both the physical machinery
and the process environment

1000
00:52:01,990 --> 00:52:05,620
that that machinery generates
around the work piece.

1001
00:52:05,620 --> 00:52:08,810
So examples might
be an an etch bath.

1002
00:52:08,810 --> 00:52:13,460
So that is a liquid
chemical environment

1003
00:52:13,460 --> 00:52:15,080
that might be done
under the control

1004
00:52:15,080 --> 00:52:18,870
of a piece of equipment.

1005
00:52:18,870 --> 00:52:21,930
Other equipment that many of you
may have come in contact with--

1006
00:52:21,930 --> 00:52:26,490
things like injection molders,
lathes, drop presses--

1007
00:52:26,490 --> 00:52:30,060
and the whole goal of those
are to act on some workpiece.

1008
00:52:30,060 --> 00:52:33,300
So we may have silicon with
certain layers already coded

1009
00:52:33,300 --> 00:52:34,020
on them.

1010
00:52:34,020 --> 00:52:36,990
We may have feedstock,
things like plastic pellets

1011
00:52:36,990 --> 00:52:39,120
or [INAUDIBLE], that come in.

1012
00:52:39,120 --> 00:52:40,260
We may have sheet metal.

1013
00:52:40,260 --> 00:52:41,970
Sheet metal already
may have gone

1014
00:52:41,970 --> 00:52:44,040
through an awful
lot of processing,

1015
00:52:44,040 --> 00:52:46,080
and we're looking at
a unit step that's

1016
00:52:46,080 --> 00:52:49,810
doing some additional
processing on that.

1017
00:52:49,810 --> 00:52:55,560
And then the output can
either be a finished part

1018
00:52:55,560 --> 00:53:00,090
direct for use or a part that is
in some intermediate stage that

1019
00:53:00,090 --> 00:53:03,630
will, again, go and be used
in some larger manufacturing

1020
00:53:03,630 --> 00:53:04,540
process.

1021
00:53:04,540 --> 00:53:06,420
So it might be a shaft
or a hood or something

1022
00:53:06,420 --> 00:53:08,940
like that that's going
to be further assembled,

1023
00:53:08,940 --> 00:53:10,440
or an IC chip--

1024
00:53:10,440 --> 00:53:12,750
which, from the
semiconductor fab,

1025
00:53:12,750 --> 00:53:14,400
that's the finished product.

1026
00:53:14,400 --> 00:53:17,130
But from somebody-- can't
remember who said they worked

1027
00:53:17,130 --> 00:53:19,080
at Dell--

1028
00:53:19,080 --> 00:53:22,470
the IC chip-- that's
not a finished product.

1029
00:53:22,470 --> 00:53:25,680
The PC and the assembly--

1030
00:53:25,680 --> 00:53:28,390
the packaging and assembly
onto boards and the assembly

1031
00:53:28,390 --> 00:53:31,920
of boards into the
[? back plane ?] and so on

1032
00:53:31,920 --> 00:53:35,980
are an important
manufacturing process.

1033
00:53:35,980 --> 00:53:40,560
So by definition, we're thinking
of a manufacturing process

1034
00:53:40,560 --> 00:53:45,240
as a change or the sequence
of changes in some work piece

1035
00:53:45,240 --> 00:53:46,510
material.

1036
00:53:46,510 --> 00:53:48,390
The easiest way to
conceptualize this

1037
00:53:48,390 --> 00:53:51,180
is that it's going to
be a change in geometry.

1038
00:53:51,180 --> 00:53:53,610
We're building up some part.

1039
00:53:53,610 --> 00:53:56,790
But equally
important is a change

1040
00:53:56,790 --> 00:54:00,810
in some material properties,
some constitutive properties

1041
00:54:00,810 --> 00:54:02,410
of that structure.

1042
00:54:02,410 --> 00:54:04,410
We'll see lots of
examples of that

1043
00:54:04,410 --> 00:54:06,540
in semiconductor fabrication.

1044
00:54:06,540 --> 00:54:09,750
Here I want to give you a
kind of a generic conceptual

1045
00:54:09,750 --> 00:54:11,580
semiconductor process model.

1046
00:54:11,580 --> 00:54:13,710
And actually, I want to
mention a little bit--

1047
00:54:13,710 --> 00:54:17,520
this ties into the history of
the evolution of this subject.

1048
00:54:17,520 --> 00:54:21,420
Back-- oh, God-- it's getting
to be 18 years ago already--

1049
00:54:24,060 --> 00:54:27,540
when we were starting to look
at ways to formalize discussion

1050
00:54:27,540 --> 00:54:31,200
of semiconductor processing,
we came up with--

1051
00:54:31,200 --> 00:54:34,140
myself and some other
co-workers here at MIT

1052
00:54:34,140 --> 00:54:37,080
came up with some terminology
for this conceptual

1053
00:54:37,080 --> 00:54:39,000
semiconductor process model.

1054
00:54:39,000 --> 00:54:41,280
And we talked about
it in terms of states

1055
00:54:41,280 --> 00:54:43,830
and transformations of
states, these states

1056
00:54:43,830 --> 00:54:47,610
being the geometric state and
the constitutive properties

1057
00:54:47,610 --> 00:54:51,300
of the work piece In
semiconductor fabrication,

1058
00:54:51,300 --> 00:54:53,760
that's typically the wafer.

1059
00:54:53,760 --> 00:54:56,010
And around that,
one is generating

1060
00:54:56,010 --> 00:54:59,040
a process or some
environment around the wafer.

1061
00:54:59,040 --> 00:55:03,060
That may be gases,
temperature environment,

1062
00:55:03,060 --> 00:55:09,300
other kinds of ways of
generating and directing

1063
00:55:09,300 --> 00:55:13,750
energy and material at
the surface of the wafer.

1064
00:55:13,750 --> 00:55:17,500
The machine itself is a key
controlling parameter for how

1065
00:55:17,500 --> 00:55:20,920
one generates that environment,
and the rest of the facility

1066
00:55:20,920 --> 00:55:25,390
also impacts that environment--
the feed material coming in,

1067
00:55:25,390 --> 00:55:29,560
the very, very high purity
chemicals, for example.

1068
00:55:29,560 --> 00:55:31,480
Now, what's important
about the machine

1069
00:55:31,480 --> 00:55:35,980
is that the operator
only has limited access.

1070
00:55:35,980 --> 00:55:39,700
The operator, which may be human
or may be an automation system,

1071
00:55:39,700 --> 00:55:44,860
has only limited access to
that equipment and the facility

1072
00:55:44,860 --> 00:55:48,860
through some settings-- some
knob settings, if you will,

1073
00:55:48,860 --> 00:55:51,370
that you can perform
on the equipment.

1074
00:55:51,370 --> 00:55:56,080
But you also have other
directional sensing capability.

1075
00:55:56,080 --> 00:55:59,650
You have some number of readings
that are telling you indirectly

1076
00:55:59,650 --> 00:56:01,930
things about the machine--

1077
00:56:01,930 --> 00:56:05,440
machine states, sensor
states, thermocouple states,

1078
00:56:05,440 --> 00:56:08,260
which are telling you things
about the wafer environment--

1079
00:56:08,260 --> 00:56:11,110
and then, indirectly--
if you're lucky, directly

1080
00:56:11,110 --> 00:56:12,985
things about the
state of the work

1081
00:56:12,985 --> 00:56:18,190
piece itself, telling you things
like the thickness of the film

1082
00:56:18,190 --> 00:56:20,230
being grown on the wafer.

1083
00:56:20,230 --> 00:56:24,220
And then we had a term,
which is really kind

1084
00:56:24,220 --> 00:56:28,120
generic to semiconductor
processing, of a recipe that

1085
00:56:28,120 --> 00:56:32,980
basically defined the settings,
and perhaps even could

1086
00:56:32,980 --> 00:56:35,203
be generalized to a
control algorithm,

1087
00:56:35,203 --> 00:56:37,120
if you will-- which might
be a little bit more

1088
00:56:37,120 --> 00:56:40,570
of a generic
terminology-- for dealing

1089
00:56:40,570 --> 00:56:42,880
with responses to the readings.

1090
00:56:42,880 --> 00:56:46,180
So now you can think about
things like real-time control--

1091
00:56:46,180 --> 00:56:48,940
or run by run control, which
we'll talk about later--

1092
00:56:48,940 --> 00:56:52,390
that looks at how one determines
what the settings should

1093
00:56:52,390 --> 00:56:55,180
be on the equipment.

1094
00:56:55,180 --> 00:56:59,050
Now, we came up with a
slightly simplified version

1095
00:56:59,050 --> 00:57:01,930
of the semiconductor
process model just focused

1096
00:57:01,930 --> 00:57:05,590
on the wafer, the
process, and the settings.

1097
00:57:05,590 --> 00:57:10,352
And I want to give you a
real quick example of this.

1098
00:57:10,352 --> 00:57:12,310
Actually, I'll probably
skip this and come back

1099
00:57:12,310 --> 00:57:13,880
to this next time.

1100
00:57:13,880 --> 00:57:18,700
This is looking at examples for
one particular process dealing

1101
00:57:18,700 --> 00:57:20,420
with oxidation.

1102
00:57:20,420 --> 00:57:22,360
Now, what was
interesting is we came up

1103
00:57:22,360 --> 00:57:24,110
with this generic process model.

1104
00:57:24,110 --> 00:57:26,350
This was early '90s.

1105
00:57:26,350 --> 00:57:28,390
When I came back to
MIT, I started teaching

1106
00:57:28,390 --> 00:57:31,330
a subject on
semiconductor process

1107
00:57:31,330 --> 00:57:34,420
control dealing with
statistical process modeling,

1108
00:57:34,420 --> 00:57:37,810
yield, design of
experiments, and so on.

1109
00:57:37,810 --> 00:57:39,640
And then I got involved
in some research

1110
00:57:39,640 --> 00:57:42,370
that overlapped with Dave
Hardt and some others.

1111
00:57:42,370 --> 00:57:45,610
And he had a course, and--

1112
00:57:45,610 --> 00:57:47,890
on manufacturing
process control,

1113
00:57:47,890 --> 00:57:52,990
and he had a process model
for control circa 1995.

1114
00:57:52,990 --> 00:57:55,780
Maybe you had come up
with it even earlier.

1115
00:57:55,780 --> 00:57:59,470
And one of the readings that you
need to grab off of the website

1116
00:57:59,470 --> 00:58:03,580
is an overview of
manufacturing processes that

1117
00:58:03,580 --> 00:58:08,020
is circa 1995, '96, where
the terminology is almost

1118
00:58:08,020 --> 00:58:10,430
exactly the same.

1119
00:58:10,430 --> 00:58:14,290
And in fact, the
overlap was astonishing.

1120
00:58:14,290 --> 00:58:16,810
The tools and techniques
that I was teaching

1121
00:58:16,810 --> 00:58:19,600
in my separate subject and Dave
was teaching in his subject

1122
00:58:19,600 --> 00:58:23,350
was about 80% the same, and
then just the process details

1123
00:58:23,350 --> 00:58:24,670
kind of changed.

1124
00:58:24,670 --> 00:58:26,950
So in fact, we
merged the subject,

1125
00:58:26,950 --> 00:58:30,520
and that's how this
subject came about.

1126
00:58:30,520 --> 00:58:34,120
And again, the key ideas
here are there are controls.

1127
00:58:34,120 --> 00:58:36,130
There is the operator,
and some settings,

1128
00:58:36,130 --> 00:58:38,320
and the equipment, material--

1129
00:58:38,320 --> 00:58:41,170
that we're all about changing
the geometry and property

1130
00:58:41,170 --> 00:58:44,680
through the action of
the process environment,

1131
00:58:44,680 --> 00:58:46,457
or these energy states.

1132
00:58:46,457 --> 00:58:48,040
Now, in this class,
we're really going

1133
00:58:48,040 --> 00:58:50,770
to be focused a lot
on the overall process

1134
00:58:50,770 --> 00:58:53,500
outputs [INAUDIBLE]
processes, and in some cases,

1135
00:58:53,500 --> 00:58:55,790
the aggregation of those.

1136
00:58:55,790 --> 00:58:58,240
And just to get a little
bit of terminology

1137
00:58:58,240 --> 00:59:03,700
as a prelude for both
Thursday and next Tuesday,

1138
00:59:03,700 --> 00:59:07,570
one can think about a
vector y of characteristics

1139
00:59:07,570 --> 00:59:10,000
of the product that
are important--

1140
00:59:10,000 --> 00:59:13,000
shape parameters,
particular thicknesses,

1141
00:59:13,000 --> 00:59:16,150
perhaps material properties--
like index of refraction

1142
00:59:16,150 --> 00:59:17,710
of thin films--

1143
00:59:17,710 --> 00:59:22,630
the conductivity of particular
layers, as well as transistor

1144
00:59:22,630 --> 00:59:24,920
characteristics, for example.

1145
00:59:24,920 --> 00:59:28,900
And that is a function of
the process parameters,

1146
00:59:28,900 --> 00:59:31,840
both controls that
one can change

1147
00:59:31,840 --> 00:59:37,040
and other parameters that may be
fixed and set for the process.

1148
00:59:37,040 --> 00:59:39,610
So a key question is,
what are these alphas?

1149
00:59:39,610 --> 00:59:41,350
What are these
process parameters?

1150
00:59:44,990 --> 00:59:46,880
And how do we go about
controlling those?

1151
00:59:46,880 --> 00:59:51,660
So we'll touch on this picture
a little bit more next time,

1152
00:59:51,660 --> 00:59:56,990
but what I want to
skip to here is a--

1153
00:59:56,990 --> 01:00:01,550
we'll hear about these different
characterizations or taxonomy

1154
01:00:01,550 --> 01:00:02,810
of the process next time.

1155
01:00:05,570 --> 01:00:08,900
I want to give you
one last description

1156
01:00:08,900 --> 01:00:15,590
building on this very simplified
mathematical terminology

1157
01:00:15,590 --> 01:00:23,510
at least for the process,
which is we can go in and--

1158
01:00:23,510 --> 01:00:24,750
here we go.

1159
01:00:24,750 --> 01:00:25,580
Here we go.

1160
01:00:25,580 --> 01:00:28,970
We can split out some of
those process parameters

1161
01:00:28,970 --> 01:00:32,420
as those things that
we have control over

1162
01:00:32,420 --> 01:00:34,940
as inputs to the process.

1163
01:00:34,940 --> 01:00:39,560
And now, if we do just a very,
very simple first-order Taylor

1164
01:00:39,560 --> 01:00:43,230
expansion, we get
some nice insight

1165
01:00:43,230 --> 01:00:47,650
into where variation comes
in a typical process.

1166
01:00:47,650 --> 01:00:52,070
So this is the very
simple variation equation

1167
01:00:52,070 --> 01:00:53,600
that, in some sense,
helps structure

1168
01:00:53,600 --> 01:00:56,270
what we're going to be doing
through the rest of the term.

1169
01:00:56,270 --> 01:01:00,320
One can think about
deviations in the output

1170
01:01:00,320 --> 01:01:03,950
deltas in those
characteristics, and we

1171
01:01:03,950 --> 01:01:07,100
can expand that in terms of
some of the alpha parameters

1172
01:01:07,100 --> 01:01:11,300
and some of the
controllable parameters.

1173
01:01:11,300 --> 01:01:18,670
So this dy d alpha-- that's
sensitivity to delta a alphas.

1174
01:01:18,670 --> 01:01:19,600
What's delta alphas?

1175
01:01:19,600 --> 01:01:23,780
Those are disturbances that you
would prefer were not there.

1176
01:01:23,780 --> 01:01:26,320
They're not things that you
intentionally are changing.

1177
01:01:26,320 --> 01:01:30,320
Those are inherent
disturbances in the process.

1178
01:01:30,320 --> 01:01:34,300
So there's one component
that deals with disturbances.

1179
01:01:34,300 --> 01:01:36,670
And then there's also
intentional changes

1180
01:01:36,670 --> 01:01:41,020
we might have, when we want to
or intentionally make a change

1181
01:01:41,020 --> 01:01:43,190
to the control inputs.

1182
01:01:43,190 --> 01:01:47,030
And so what's interesting is
the strategies that we might use

1183
01:01:47,030 --> 01:01:51,070
for minimizing this delta y.

1184
01:01:51,070 --> 01:01:54,280
And in some sense--

1185
01:01:54,280 --> 01:01:57,470
let's see.

1186
01:01:57,470 --> 01:02:00,470
Let me get to a
nice summary here.

1187
01:02:00,470 --> 01:02:01,730
Here we go.

1188
01:02:01,730 --> 01:02:06,350
In some sense, the goal of
the first third of the class--

1189
01:02:06,350 --> 01:02:09,170
the techniques we'll be talking
about our statistical process

1190
01:02:09,170 --> 01:02:12,530
control, which is
all about detecting

1191
01:02:12,530 --> 01:02:15,920
these inherent deviations,
these disturbances,

1192
01:02:15,920 --> 01:02:18,770
and seeking to minimize them.

1193
01:02:18,770 --> 01:02:21,410
Then we can talk about
process optimization,

1194
01:02:21,410 --> 01:02:23,510
things like design
of experiments,

1195
01:02:23,510 --> 01:02:26,810
where we're basically trying
to build a model for y--

1196
01:02:26,810 --> 01:02:29,240
the output-- as a
function of process

1197
01:02:29,240 --> 01:02:33,560
parameters, and seek to
minimize the sensitivity

1198
01:02:33,560 --> 01:02:37,610
to those disturbances, to
have as robust a process as

1199
01:02:37,610 --> 01:02:39,020
possible.

1200
01:02:39,020 --> 01:02:41,180
And then finally,
we can also think

1201
01:02:41,180 --> 01:02:45,590
about active modes of process
control, where you actually

1202
01:02:45,590 --> 01:02:48,500
manipulate some of the
control parameters,

1203
01:02:48,500 --> 01:02:51,830
perhaps in response to
observed deviations,

1204
01:02:51,830 --> 01:02:55,280
to ultimately minimize
or counteract,

1205
01:02:55,280 --> 01:02:59,600
through feedback control, the
effects of those disturbances.

1206
01:02:59,600 --> 01:03:03,560
So that in the
nutshell is the map

1207
01:03:03,560 --> 01:03:06,740
for what we're going to be doing
through the rest of the term.

1208
01:03:06,740 --> 01:03:09,920
We're going to be dealing, first
off, with statistical process

1209
01:03:09,920 --> 01:03:12,380
control and the statistical
background for that.

1210
01:03:12,380 --> 01:03:14,270
We're then going to be
modeling the process,

1211
01:03:14,270 --> 01:03:17,270
building up design of
experiments, response surface

1212
01:03:17,270 --> 01:03:20,420
modeling technologies
for modeling

1213
01:03:20,420 --> 01:03:22,580
and optimizing the
process, and then

1214
01:03:22,580 --> 01:03:25,460
thirdly, we'll talk about
some basic strategies

1215
01:03:25,460 --> 01:03:28,970
for feedback control
to compensate

1216
01:03:28,970 --> 01:03:31,370
for some of these processes.

1217
01:03:31,370 --> 01:03:34,060
So with that, we'll leave you.

1218
01:03:34,060 --> 01:03:37,030
Folks in Singapore, we'll
see you again next week.

1219
01:03:37,030 --> 01:03:44,570
Again, do catch the videotape
of Thursday's lecture.

1220
01:03:44,570 --> 01:03:46,790
Please go to the website.

1221
01:03:46,790 --> 01:03:50,840
This lecture is on there,
but also there are two--

1222
01:03:50,840 --> 01:03:54,020
well, there's one reading
that you should grab

1223
01:03:54,020 --> 01:03:55,670
right away, which is about a--

1224
01:03:55,670 --> 01:03:59,150
was is it-- six or seven
pages process overview

1225
01:03:59,150 --> 01:04:03,500
which defines some of this
terminology in written form

1226
01:04:03,500 --> 01:04:05,180
that we've talked about here.

1227
01:04:05,180 --> 01:04:07,940
And I will also post what
the reading assignment

1228
01:04:07,940 --> 01:04:10,330
is that you can get started on.

1229
01:04:10,330 --> 01:04:12,290
I don't think it's
posted up there yet,

1230
01:04:12,290 --> 01:04:14,300
but go out and try
to get these books,

1231
01:04:14,300 --> 01:04:17,870
because there will be-- the
reading assignment is basically

1232
01:04:17,870 --> 01:04:21,380
start on the first two chapters,
which are very talkative

1233
01:04:21,380 --> 01:04:24,900
overview of
manufacturing processes.

1234
01:04:24,900 --> 01:04:26,840
So we'll get you
started on those.

1235
01:04:26,840 --> 01:04:28,340
One quick question, Dave--

1236
01:04:28,340 --> 01:04:30,020
is there any information on--

1237
01:04:30,020 --> 01:04:33,088
is there a pro seminar
when that starts up,

1238
01:04:33,088 --> 01:04:34,130
that you want to mention?

1239
01:04:34,130 --> 01:04:34,880
DAVID HARDT: Yeah.

1240
01:04:34,880 --> 01:04:37,130
2.888 is already-- there's
a Stellar site on it.

1241
01:04:37,130 --> 01:04:40,616
I think I've sent most of the
preregistered students notes

1242
01:04:40,616 --> 01:04:44,712
on this, but it starts
a week [INAUDIBLE]..

1243
01:04:44,712 --> 01:04:45,420
DUANE BONING: OK.

1244
01:04:45,420 --> 01:04:47,310
So we'll have more
information on that.

1245
01:04:47,310 --> 01:04:52,680
Many of you, like those enrolled
in the mechanical engineering,

1246
01:04:52,680 --> 01:04:54,850
MEng program, will know
about this already,

1247
01:04:54,850 --> 01:04:58,680
but this series of seminars from
folks from industry and so on

1248
01:04:58,680 --> 01:05:02,930
will quite likely be of interest
to other people in the class.

1249
01:05:02,930 --> 01:05:06,720
So we'll start alerting you
about those evening seminars

1250
01:05:06,720 --> 01:05:09,130
here as well.

1251
01:05:09,130 --> 01:05:13,310
So welcome to the class, and
we'll see you on Thursday.