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PROFESSOR: So as
people are gathering,

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00:00:03,110 --> 00:00:06,020
you might begin to
notice some common themes

3
00:00:06,020 --> 00:00:08,119
across different industries.

4
00:00:08,119 --> 00:00:11,090
We have unique
identifiers called--

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what did we call it in
the aircraft industry?

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So it's not just RFID.

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DIMITRI KYRITSIS: Smart labels.

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00:00:16,130 --> 00:00:17,720
PROFESSOR: Oh, smart labels.

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Right.

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00:00:18,830 --> 00:00:21,530
We've heard how
identification schemes

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are incorporated in airplanes.

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00:00:24,500 --> 00:00:28,130
And now, we're going to
listen to our colleagues

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00:00:28,130 --> 00:00:33,200
from the automotive industry
and how RFID is enabling

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00:00:33,200 --> 00:00:36,230
changes in that industry.

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And we're fortunate to have
a member of the conference

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00:00:39,290 --> 00:00:43,380
committee, Dimitri
Kyritsis, who's

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00:00:43,380 --> 00:00:47,690
the associate director of the
Lab of Informatics for Design

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00:00:47,690 --> 00:00:49,432
at the University of--

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00:00:49,432 --> 00:00:51,140
DIMITRI KYRITSIS:
Swiss Federal Institute

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00:00:51,140 --> 00:00:52,447
of Technology in Lausanne.

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PROFESSOR: OK.

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[LAUGHTER]

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It didn't fit.

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Thank you.

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00:00:57,173 --> 00:00:58,340
DIMITRI KYRITSIS: Thank you.

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00:00:58,340 --> 00:00:59,990
Or if you prefer
it in French, it's

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Ecole Polytechnique
Federal de Lausanne.

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Good afternoon,
ladies and gentlemen.

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So we will continue
somehow same concept,

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but in the automotive sector.

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We will cover two things,
two aspects today.

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So the product lifecycle
management and logistics

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or external logistics.

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I suppose you know
that there are

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other applications
in automotive sector

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like the reusable and active
tag in assembly lines.

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Or there are other initiatives
in wireless manufacturing.

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But we will not talk
about that today.

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00:01:38,390 --> 00:01:40,520
It's my great
pleasure to present

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00:01:40,520 --> 00:01:44,240
you this project,
Promise, about the PLAM

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00:01:44,240 --> 00:01:47,550
and information tracking
using smart-embedded devices.

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00:01:47,550 --> 00:01:49,670
You don't see RFID in the title.

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00:01:49,670 --> 00:01:50,840
I will explain to you why.

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00:01:50,840 --> 00:01:54,440
So my colleague here from
Research Center Fiat,

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00:01:54,440 --> 00:02:00,440
Julien Mascolo, will present
you a concept of a demonstrator.

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00:02:00,440 --> 00:02:04,520
And Professor
Scholz-Reiter will give you

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00:02:04,520 --> 00:02:07,910
an overview of another
project in logistics.

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So as you see here, you see
two logos in the back left.

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00:02:11,040 --> 00:02:13,040
It's the sixth framework
program of the European

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00:02:13,040 --> 00:02:14,365
Union and the IMS.

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IMS is the Intelligent
Manufacturing System program

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00:02:19,160 --> 00:02:22,905
that promotes research at
the international level.

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I will start with
presenting you little bit

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briefly the partners.

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So in European-- in Europe,
together with Switzerland,

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we are 22, including end users.

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You may recognize them.

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Fiat, Caterpillar,
[INAUDIBLE],, and producers

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of white and brown goods
in Italy, well-known.

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00:02:45,430 --> 00:02:46,920
[INAUDIBLE] do machine tools.

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00:02:46,920 --> 00:02:50,190
[INAUDIBLE] do telecom
equipment in Greece.

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Bombadier in Switzerland.

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They're well known for not only
for airplanes, but railway.

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Locomotives.

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And this division is with us.

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In solution providers, we
have ACP, a world leader

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in ERP solutions
[INAUDIBLE],, producing tags

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and other embedded devices.

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And the other that you see
here are small companies

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that they provide the
services in this field,

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and a number of number of
universities from Europe,

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including Cambridge
University who is also

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a member of this community.

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[INAUDIBLE]
international program.

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So we have partners
in Japan, a consortium

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which is led by Toyota
Motors and including

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00:03:38,850 --> 00:03:42,840
University of Tokyo, Wasede
University, and CHO University.

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In the United States, we
work with the Intelligence

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Maintenance System, the National
Science Foundation Center,

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00:03:49,230 --> 00:03:53,075
which runs University
of Cincinnati

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00:03:53,075 --> 00:03:54,450
now because
Professor [INAUDIBLE]

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00:03:54,450 --> 00:03:57,810
moved to Cincinnati, Stanford,
and University of Michigan.

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00:03:57,810 --> 00:04:01,450
And in Australia, also, there's
a small consortium with IRIS.

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00:04:01,450 --> 00:04:05,460
IRIS is a Research Institute
in the Swinburne University,

85
00:04:05,460 --> 00:04:09,040
and they do work in
end of life management.

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00:04:09,040 --> 00:04:13,330
So our ultimate goal is
to realize closed loop

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00:04:13,330 --> 00:04:17,130
PLM for this kind of products.

88
00:04:17,130 --> 00:04:18,130
What do we mean by that?

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00:04:18,130 --> 00:04:24,900
So if you take the phases of
a product system lifecycle--

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00:04:24,900 --> 00:04:27,463
let's take these four runs.

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00:04:27,463 --> 00:04:29,880
Two of them, the first two of
them, design and production,

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00:04:29,880 --> 00:04:32,330
are part of the beginning
of life of product.

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00:04:32,330 --> 00:04:34,080
The use and service
is the middle of life,

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00:04:34,080 --> 00:04:36,720
and the end of use
is the end of life.

95
00:04:36,720 --> 00:04:39,430
And you see the
activities that are

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00:04:39,430 --> 00:04:41,400
on a regular basis within them.

97
00:04:41,400 --> 00:04:44,670
And then if you take the
flows, the information flows,

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00:04:44,670 --> 00:04:48,270
you see that as the process
level where designs, design is

99
00:04:48,270 --> 00:04:52,500
concerned, you have now
some concurrent activities

100
00:04:52,500 --> 00:04:55,800
or some feedback, particularly
between design and production

101
00:04:55,800 --> 00:04:57,450
with tools like
concurrent engineering,

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00:04:57,450 --> 00:05:00,000
design for manufacturing
and assembly, et cetera.

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00:05:00,000 --> 00:05:02,260
You have good tools there.

104
00:05:02,260 --> 00:05:04,620
But if you go farther
to the lifecycle,

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00:05:04,620 --> 00:05:06,838
there is not a lot of
feedback of information.

106
00:05:06,838 --> 00:05:08,880
At the product level, you
have the documentation.

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You have design documents, user
guides, manuals, et cetera.

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00:05:13,920 --> 00:05:18,630
And if you take the material
look then after the end of use,

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there is no track
of information.

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Or in some sectors,
there is, but usually,

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00:05:24,360 --> 00:05:26,280
in most of the products,
you don't have a lot

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00:05:26,280 --> 00:05:27,750
of information coming back.

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So our goal is to
provide the system that

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00:05:30,420 --> 00:05:34,380
allows closing the information
loop so field data, experience

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00:05:34,380 --> 00:05:37,140
gathered in the field from
various factors involved,

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00:05:37,140 --> 00:05:41,820
goes back to design and helps
improve quality of products

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00:05:41,820 --> 00:05:43,840
and new generation of products.

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So the concept is to use some
product embedded information

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00:05:47,430 --> 00:05:51,150
devices, as we call
them, including RFID.

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We'll see in another
slide the way

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we use this system that
will allow to realize

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00:05:56,260 --> 00:05:57,630
on ideas like this one.

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00:05:57,630 --> 00:06:00,600
So when a product is delivered,
a locomotive, for example,

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00:06:00,600 --> 00:06:02,070
there is some
initial information

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that is written in
this product, Let's say

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00:06:06,045 --> 00:06:07,440
in an embedded device.

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Then during life, you
have various active agents

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which are certified agents.

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00:06:12,450 --> 00:06:14,220
And they have the
right to conduct,

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00:06:14,220 --> 00:06:17,730
to communicate with the
product and talk to it

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00:06:17,730 --> 00:06:21,570
and retrieve information,
take decisions,

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or be able to
retrieve information

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specific to that product
through the internet

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and take decisions and
update information locally

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00:06:30,240 --> 00:06:35,400
if it is necessary, and
also back to the producers.

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So we are going to use various
identification technologies.

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00:06:39,750 --> 00:06:43,620
Some of them are here,
and I present them here.

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We have RFID with EPCglobal.

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That [INAUDIBLE] now.

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But we have also
other ID technologies

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00:06:49,320 --> 00:06:51,690
that are referenced, and
you are aware of them.

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00:06:51,690 --> 00:06:53,760
The ID [INAUDIBLE],, which
is something developed

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00:06:53,760 --> 00:06:55,630
by Helsinki University
of Technology,

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is also partner in our project.

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The WWAI is also another.

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00:07:00,300 --> 00:07:04,560
A protocol promoted by Stockway,
a small company in Finland.

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00:07:04,560 --> 00:07:07,350
Finland again by
chance, maybe, which

148
00:07:07,350 --> 00:07:10,180
is also partnered
in our project.

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00:07:10,180 --> 00:07:13,200
And then we have also
some tools like the GPS

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00:07:13,200 --> 00:07:17,910
or the GIS for the
localization issues.

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00:07:17,910 --> 00:07:23,050
So our concept is
as it is shown here.

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So you have exchange
between values.

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00:07:25,420 --> 00:07:28,300
This elements,
the EL system that

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00:07:28,300 --> 00:07:31,450
is used to develop the
product, the product itself,

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and the various services that
are executed by various agents

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00:07:34,900 --> 00:07:36,340
through the life of a product.

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00:07:36,340 --> 00:07:39,490
All this data and
information and knowledge

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00:07:39,490 --> 00:07:41,990
is created, how to
manage all this stuff.

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So this is what we call the
concept of closed loop PLM.

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And in order to
realize it, we think

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00:07:50,670 --> 00:07:53,790
that we need this product
embedded information devices

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00:07:53,790 --> 00:07:57,030
to capture information
within the product.

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00:07:57,030 --> 00:08:00,120
And we think that it has to
be closed in two directions,

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00:08:00,120 --> 00:08:01,748
horizontally and vertically.

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00:08:01,748 --> 00:08:03,540
What do I mean horizontally
and vertically?

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00:08:03,540 --> 00:08:06,850
This is a very generic
model of a product.

167
00:08:06,850 --> 00:08:11,480
So you have the product
lifecycle phase here.

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00:08:11,480 --> 00:08:12,080
Oops.

169
00:08:12,080 --> 00:08:12,680
Yes.

170
00:08:12,680 --> 00:08:15,110
Beginning of life, middle
of life, end of life.

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00:08:15,110 --> 00:08:16,710
And you have the
application layer.

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So layer 1, for
example, the RFID tax

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00:08:19,190 --> 00:08:22,460
or, rather, at the productive
level, at the hardware level.

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Layer 2, for example, maybe
the middle where I will--

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there will be some
more explanation after.

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And we want to
close in vertical.

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In the vertical
direction, that is

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that information goes from the
product to the decision support

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00:08:36,500 --> 00:08:39,320
systems and back to the
product if it is necessary.

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And also along the
lifecycles from beginning

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00:08:42,075 --> 00:08:44,450
of life to end of life and
back to the beginning of life.

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00:08:47,510 --> 00:08:50,090
So pillar modeling
means for us that we

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00:08:50,090 --> 00:08:54,230
have to manage the whole
product lifecycle activities

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00:08:54,230 --> 00:08:56,120
and manage not only
product data, but also

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00:08:56,120 --> 00:09:00,500
associated resources,
including people, and agents,

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00:09:00,500 --> 00:09:02,150
and machines, et cetera.

187
00:09:02,150 --> 00:09:04,640
There is a need to collaborate
among various partners

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00:09:04,640 --> 00:09:05,960
and stakeholders.

189
00:09:05,960 --> 00:09:07,400
And we need to
have an enterprise

190
00:09:07,400 --> 00:09:11,550
ability to analyze
related problems

191
00:09:11,550 --> 00:09:13,650
and take appropriate decisions.

192
00:09:13,650 --> 00:09:19,490
So just to give you, I think,
motivation, if you see in this,

193
00:09:19,490 --> 00:09:23,990
you're right diagram,
the information

194
00:09:23,990 --> 00:09:28,730
associated with the products
goes decreasing with the time.

195
00:09:28,730 --> 00:09:32,090
And what we want to do that
is to invert the situation

196
00:09:32,090 --> 00:09:36,050
and going, let's say, from
one phase to the other.

197
00:09:36,050 --> 00:09:39,740
Augment this information using
available technology that

198
00:09:39,740 --> 00:09:42,210
will help to close the loops.

199
00:09:42,210 --> 00:09:43,500
So what kind of data?

200
00:09:43,500 --> 00:09:47,892
So I saw some in some previous
talks something similar.

201
00:09:47,892 --> 00:09:49,850
They have the contacts
that we want to measure.

202
00:09:49,850 --> 00:09:51,140
For example, a sample of them.

203
00:09:51,140 --> 00:09:52,820
And a kind of metadata.

204
00:09:52,820 --> 00:09:55,040
For example, questions
that the product

205
00:09:55,040 --> 00:09:58,260
should be able to answer.

206
00:09:58,260 --> 00:10:00,660
This is an overview of our
system architecture starting

207
00:10:00,660 --> 00:10:02,910
from the products, where we
have this product embedded

208
00:10:02,910 --> 00:10:05,490
information devices
in various forms,

209
00:10:05,490 --> 00:10:08,410
and then middleware to
communicate with that

210
00:10:08,410 --> 00:10:11,130
and to develop applications
for decision making,

211
00:10:11,130 --> 00:10:14,130
for knowledge management,
and then business

212
00:10:14,130 --> 00:10:16,980
processes applications
from design for [INAUDIBLE]

213
00:10:16,980 --> 00:10:19,570
to recycling to end of life.

214
00:10:19,570 --> 00:10:23,010
This is the architecture of
the component that we have.

215
00:10:23,010 --> 00:10:26,550
What we do here is we
don't use only RFID.

216
00:10:26,550 --> 00:10:30,060
Infineon is developing a
technology called PIDX Access

217
00:10:30,060 --> 00:10:36,030
Container that tries to
modernize information contained

218
00:10:36,030 --> 00:10:39,300
in various tags embedded
with the product.

219
00:10:39,300 --> 00:10:44,700
And then allow the transmission
of this data in good interface

220
00:10:44,700 --> 00:10:49,340
with middleware and
to debugging systems.

221
00:10:49,340 --> 00:10:52,340
For example, a possible
scenario that we

222
00:10:52,340 --> 00:10:56,750
want to analyze with all
of this promise system

223
00:10:56,750 --> 00:11:00,200
is, for example, with
middleware from PAD

224
00:11:00,200 --> 00:11:04,430
to provide data from these
devices to the middleware,

225
00:11:04,430 --> 00:11:07,010
then this data
will be transferred

226
00:11:07,010 --> 00:11:11,360
to data analysis systems and
decision support systems.

227
00:11:11,360 --> 00:11:12,350
There is this analogy.

228
00:11:12,350 --> 00:11:13,810
There is an aggregation of data.

229
00:11:13,810 --> 00:11:17,160
Data synchronization was
the term used before.

230
00:11:17,160 --> 00:11:19,520
And this will help to
generate some knowledge

231
00:11:19,520 --> 00:11:23,990
to be used for
various decisions.

232
00:11:23,990 --> 00:11:25,520
For example, there
will be a request

233
00:11:25,520 --> 00:11:28,070
for an incident happened
sometime in the past,

234
00:11:28,070 --> 00:11:30,320
or there will be some
analysis of this data

235
00:11:30,320 --> 00:11:32,330
and the generation of records.

236
00:11:32,330 --> 00:11:35,510
And this will be
helped to bring back

237
00:11:35,510 --> 00:11:41,360
some information to the
product and concentrate

238
00:11:41,360 --> 00:11:42,600
business processes.

239
00:11:42,600 --> 00:11:45,470
So in promise, we have various
applications [INAUDIBLE]

240
00:11:45,470 --> 00:11:48,770
in these sectors
represented by the partners

241
00:11:48,770 --> 00:11:50,090
from the automotive sector.

242
00:11:50,090 --> 00:11:52,340
We will see an
example right after.

243
00:11:52,340 --> 00:11:56,720
To the refrigerators
machine tools, et cetera.

244
00:11:56,720 --> 00:11:59,660
This is the list of
the demonstrators

245
00:11:59,660 --> 00:12:01,910
that we are going to develop.

246
00:12:01,910 --> 00:12:03,290
We're developing right now.

247
00:12:03,290 --> 00:12:05,780
We're at the beginning,
but they are in process.

248
00:12:05,780 --> 00:12:09,140
And the phase of
lifecycle covered

249
00:12:09,140 --> 00:12:11,270
and the representative partners.

250
00:12:11,270 --> 00:12:13,910
And not all of them will
demonstrated everything,

251
00:12:13,910 --> 00:12:15,592
but in this small
chart, you have

252
00:12:15,592 --> 00:12:17,300
which demonstrated or
contributes to what

253
00:12:17,300 --> 00:12:19,530
part of the [INAUDIBLE].

254
00:12:19,530 --> 00:12:22,370
So if you want to know
more, please visit us

255
00:12:22,370 --> 00:12:24,380
on this website.

256
00:12:24,380 --> 00:12:27,250
Now, you see it is
W. We promise no.

257
00:12:27,250 --> 00:12:28,660
No's for Norway.

258
00:12:28,660 --> 00:12:32,410
But then it will be
replaced by the we promise U

259
00:12:32,410 --> 00:12:33,622
from the United States.

260
00:12:33,622 --> 00:12:35,098
[LAUGHTER]

261
00:12:35,098 --> 00:12:36,082
Thank you very much.

262
00:12:36,082 --> 00:12:39,034
[APPLAUSE]

263
00:12:41,505 --> 00:12:42,380
PROFESSOR: Thank you.

264
00:12:42,380 --> 00:12:46,220
And now we have Julien Mascolo,
who's the international liaison

265
00:12:46,220 --> 00:12:51,020
project coordinator for the
Technologies Division of Centro

266
00:12:51,020 --> 00:12:54,320
Ricerche Fiat, which I
assume means the Research

267
00:12:54,320 --> 00:12:58,420
Center for Fiat, in Milano.

268
00:12:58,420 --> 00:13:01,710
GUEST SPEAKER 1: Well, actually,
it's not really Milano.

269
00:13:01,710 --> 00:13:02,430
But it's OK.

270
00:13:02,430 --> 00:13:05,158
It's just as if you say
Boston and Cambridge.

271
00:13:05,158 --> 00:13:06,700
It's nearly the same
thing, isn't it?

272
00:13:06,700 --> 00:13:09,100
[LAUGHING] OK.

273
00:13:09,100 --> 00:13:15,570
So let's transfer
my presentation.

274
00:13:18,770 --> 00:13:24,370
So my duty now is to make a
short overview of the concepts

275
00:13:24,370 --> 00:13:29,140
that we are developing
in promise in 10 minutes.

276
00:13:29,140 --> 00:13:34,420
So I think there are a lot of
technical and business issues

277
00:13:34,420 --> 00:13:37,520
there that I would not have
time in 10 minutes to address.

278
00:13:37,520 --> 00:13:40,720
So if you have some questions,
you can ask me afterwards.

279
00:13:40,720 --> 00:13:46,690
OK, this is an example of
what we are doing in promise

280
00:13:46,690 --> 00:13:52,570
and how we use the data that
we collected during the life

281
00:13:52,570 --> 00:13:56,590
cycle of the product to
support the dismantling

282
00:13:56,590 --> 00:14:00,160
process and the
reuse of components,

283
00:14:00,160 --> 00:14:03,340
knowing how the vehicle
and the components

284
00:14:03,340 --> 00:14:06,830
have been used during
the life cycle.

285
00:14:06,830 --> 00:14:12,950
So just a 10-second
advertisement of who we are.

286
00:14:12,950 --> 00:14:14,600
We are the Fiat Research Center.

287
00:14:14,600 --> 00:14:18,170
We are working for the different
companies in the Fiat group

288
00:14:18,170 --> 00:14:21,440
which are doing a
lot, a lot of things.

289
00:14:21,440 --> 00:14:24,020
You have companies
which are more well

290
00:14:24,020 --> 00:14:26,540
known on this side of the
Atlantic, for example.

291
00:14:26,540 --> 00:14:30,920
The [INAUDIBLE] new Holland
is part of the Fiat group,

292
00:14:30,920 --> 00:14:32,450
and the Ferrari.

293
00:14:32,450 --> 00:14:39,740
But actually, the-- ah, OK.

294
00:14:39,740 --> 00:14:45,920
What we are applying RFID for
in actually is in production

295
00:14:45,920 --> 00:14:48,980
systems and how to increase--

296
00:14:48,980 --> 00:14:53,450
to optimize the
maintenance process.

297
00:14:53,450 --> 00:14:56,990
For products, trucks,
how to use RFIDs

298
00:14:56,990 --> 00:15:01,280
to optimize the
maintenance coupons.

299
00:15:01,280 --> 00:15:04,520
And this application
that I will present

300
00:15:04,520 --> 00:15:10,220
is on how RFID tags
can be used to optimize

301
00:15:10,220 --> 00:15:13,985
the reuse of components at the
end of life of the vehicle.

302
00:15:16,530 --> 00:15:18,270
Well, what is the context?

303
00:15:18,270 --> 00:15:25,020
On one side, we have a lot of
legislative pressure coming

304
00:15:25,020 --> 00:15:29,580
from the EU on
reusing components.

305
00:15:29,580 --> 00:15:36,420
And reusing in weight and
volume components of our costs.

306
00:15:36,420 --> 00:15:39,000
Then we have also
pressure on the fact

307
00:15:39,000 --> 00:15:44,340
that now, anybody roughly can
make spare parts and send them.

308
00:15:44,340 --> 00:15:51,240
This is not-- now, it's a thing
that can be done by everybody,

309
00:15:51,240 --> 00:15:53,730
not only the OENs.

310
00:15:53,730 --> 00:15:56,790
And then the spare parts
business is one of the most

311
00:15:56,790 --> 00:15:57,360
profitable .

312
00:15:57,360 --> 00:16:01,980
Parts so we do not want
to lose this business.

313
00:16:01,980 --> 00:16:05,490
So roughly, this
demonstration is

314
00:16:05,490 --> 00:16:09,660
how to transform a business,
a legislative pressure,

315
00:16:09,660 --> 00:16:12,420
into a business.

316
00:16:12,420 --> 00:16:14,760
How will we achieve this?

317
00:16:14,760 --> 00:16:17,940
By developing what we
call an onboard diary,

318
00:16:17,940 --> 00:16:23,390
which collects the information
during the lifecycle.

319
00:16:23,390 --> 00:16:28,700
It in some way aggregates
it, and then at the end,

320
00:16:28,700 --> 00:16:32,300
gives the dismantling
some hints on which

321
00:16:32,300 --> 00:16:38,910
are the components that should
be dismantled and reused.

322
00:16:38,910 --> 00:16:46,070
Well, roughly, it's-- the
current situation is that

323
00:16:46,070 --> 00:16:49,920
the history of the components
and the vehicle is very,

324
00:16:49,920 --> 00:16:52,010
very roughly known.

325
00:16:52,010 --> 00:16:56,720
We do not know except when the
car comes back to the garage,

326
00:16:56,720 --> 00:17:00,170
we do not know how
the components are

327
00:17:00,170 --> 00:17:01,700
and how they had been used.

328
00:17:01,700 --> 00:17:05,780
Well, we want to go from
this as a situation,

329
00:17:05,780 --> 00:17:08,480
and it should be a
situation where we exactly

330
00:17:08,480 --> 00:17:12,680
know how the components
have been used during what

331
00:17:12,680 --> 00:17:14,510
we call the middle of life.

332
00:17:14,510 --> 00:17:17,990
The lifecycle of the car.

333
00:17:17,990 --> 00:17:21,200
And analyze this information.

334
00:17:21,200 --> 00:17:24,079
Give it to the
recycler so that he

335
00:17:24,079 --> 00:17:30,360
is able to dismount
the components.

336
00:17:30,360 --> 00:17:32,490
Well, the context.

337
00:17:32,490 --> 00:17:39,420
The context for using these
smart labels is quite harsh.

338
00:17:39,420 --> 00:17:43,200
We have typically a
life cycle of a car,

339
00:17:43,200 --> 00:17:49,150
which is more than 20 years,
maybe 30 years, maybe 40 years.

340
00:17:49,150 --> 00:17:55,320
So are we planning to use the
same RFID tags for this period?

341
00:17:55,320 --> 00:17:57,480
Then the second pressure,
the second constraint

342
00:17:57,480 --> 00:18:02,340
is, well, our cars go
everywhere in the world.

343
00:18:02,340 --> 00:18:05,362
We are not always
connected to them.

344
00:18:05,362 --> 00:18:11,700
So how can we be sure that
the information we need

345
00:18:11,700 --> 00:18:17,160
is still collected while the
car is anywhere in the world

346
00:18:17,160 --> 00:18:21,060
and collected, stored,
into the vehicle

347
00:18:21,060 --> 00:18:26,930
and then passed to the
dismantler at the end of life?

348
00:18:26,930 --> 00:18:30,630
Well, the cost
has to be limited.

349
00:18:30,630 --> 00:18:32,880
We are talking about
components which

350
00:18:32,880 --> 00:18:36,790
are the most expensive
components in the car.

351
00:18:36,790 --> 00:18:42,090
For example, a clutch, a motor,
an engine, starting engine,

352
00:18:42,090 --> 00:18:43,060
et cetera, et cetera.

353
00:18:43,060 --> 00:18:50,460
These are components
which are $500, $1000 up.

354
00:18:50,460 --> 00:18:53,370
But we have a lot of
these components on board

355
00:18:53,370 --> 00:18:57,150
on the vehicle, and we have a
lot of vehicles going around

356
00:18:57,150 --> 00:18:57,780
in the world.

357
00:18:57,780 --> 00:19:01,860
More than two or three
million, and maybe five

358
00:19:01,860 --> 00:19:03,750
to six components per car.

359
00:19:03,750 --> 00:19:06,630
So that makes it a lot of tax.

360
00:19:06,630 --> 00:19:13,130
Then the memory is
limited on this tax.

361
00:19:13,130 --> 00:19:18,950
But the information that
is registered by the ECU,

362
00:19:18,950 --> 00:19:24,420
by the central unit
of the car, is huge.

363
00:19:24,420 --> 00:19:29,690
There is a lot of information
which circulates in the car,

364
00:19:29,690 --> 00:19:35,960
and we want to store this to
aggregate this, to store it

365
00:19:35,960 --> 00:19:38,480
and to pass it to a dismantler.

366
00:19:38,480 --> 00:19:40,340
Then we have a lot
of other issues.

367
00:19:40,340 --> 00:19:45,440
For example, this data that
we register that we store

368
00:19:45,440 --> 00:19:52,190
is about how the user has
been using the products.

369
00:19:52,190 --> 00:19:57,020
So this is-- there is here
a very sensitive issue

370
00:19:57,020 --> 00:20:03,510
of registering how our
clients are using their costs.

371
00:20:03,510 --> 00:20:06,570
And then there are a lot
of physical constraints.

372
00:20:06,570 --> 00:20:11,430
We are talking about
what is going on

373
00:20:11,430 --> 00:20:14,250
under the hood of
the vehicle, where

374
00:20:14,250 --> 00:20:18,270
we have lots of rotating parts.

375
00:20:18,270 --> 00:20:19,350
We have liquids.

376
00:20:19,350 --> 00:20:21,390
We have metals.

377
00:20:21,390 --> 00:20:27,950
So transmitting something
in these conditions

378
00:20:27,950 --> 00:20:34,800
and for this long period of
time is quite a huge task.

379
00:20:34,800 --> 00:20:38,850
Well, we are talking about
product lifecycle management.

380
00:20:38,850 --> 00:20:41,400
We are talking about
components and vehicles.

381
00:20:41,400 --> 00:20:43,210
Let's make an example.

382
00:20:43,210 --> 00:20:47,050
We have here all the
lifecycle of the car.

383
00:20:47,050 --> 00:20:49,680
We have some
information, some events

384
00:20:49,680 --> 00:20:55,500
and some information which is
stored during this lifecycle.

385
00:20:55,500 --> 00:20:58,740
Information related to
the design and production.

386
00:20:58,740 --> 00:21:01,530
For example, which
are the conditions

387
00:21:01,530 --> 00:21:03,120
in which it has been produced?

388
00:21:03,120 --> 00:21:06,540
Which are the
recycling strategies

389
00:21:06,540 --> 00:21:10,950
which should be used at
the end of the lifecycle?

390
00:21:10,950 --> 00:21:14,640
And during the
operation of the car,

391
00:21:14,640 --> 00:21:18,090
we have a lot
information that is

392
00:21:18,090 --> 00:21:21,840
coming through the different
sensors which are already

393
00:21:21,840 --> 00:21:23,410
on board of the vehicle.

394
00:21:23,410 --> 00:21:25,860
A lot of information that
should be aggregated.

395
00:21:25,860 --> 00:21:31,650
This is what we call computing
these summary statistics.

396
00:21:31,650 --> 00:21:33,960
We cannot store all
this information.

397
00:21:33,960 --> 00:21:39,180
We have to use our,
let's say, knowledge

398
00:21:39,180 --> 00:21:43,380
of what is the data, which
is important for assessing

399
00:21:43,380 --> 00:21:46,650
the final residual value
of the year of the car.

400
00:21:46,650 --> 00:21:47,670
OK, I have to speed up.

401
00:21:47,670 --> 00:21:48,600
OK.

402
00:21:48,600 --> 00:21:51,930
And so we have to
aggregate in some way

403
00:21:51,930 --> 00:21:55,710
this information
into what is really

404
00:21:55,710 --> 00:22:00,990
useful for the end of the life.

405
00:22:00,990 --> 00:22:05,490
OK, this online data registered
during the life cycle.

406
00:22:05,490 --> 00:22:11,670
And then offline, we have
to know really what's worth.

407
00:22:11,670 --> 00:22:14,250
What's the business off of it?

408
00:22:14,250 --> 00:22:21,000
And how much could I
sell these spare parts

409
00:22:21,000 --> 00:22:23,590
which have a residual life?

410
00:22:23,590 --> 00:22:29,610
How can I sell these
to my customers?

411
00:22:29,610 --> 00:22:36,570
And then give this online data
and offline data to the DSS

412
00:22:36,570 --> 00:22:39,990
so that we know what to
do with the components.

413
00:22:39,990 --> 00:22:42,420
OK, let's make two
simple examples

414
00:22:42,420 --> 00:22:46,590
of what is happening
during the lifecycle.

415
00:22:46,590 --> 00:22:48,570
One of the components,
the clutch, for example,

416
00:22:48,570 --> 00:22:50,820
is being substituted.

417
00:22:50,820 --> 00:22:56,310
The RFID, which is on
board of the component,

418
00:22:56,310 --> 00:23:02,340
was spotted by the antenna,
the reader, which is

419
00:23:02,340 --> 00:23:06,570
connected to the central ECU.

420
00:23:06,570 --> 00:23:09,870
The ECU recognized
that this clutch

421
00:23:09,870 --> 00:23:17,470
has been substituted and stored
this data in the onboard diary.

422
00:23:17,470 --> 00:23:21,760
At the end of life
of the vehicle,

423
00:23:21,760 --> 00:23:26,550
this information is
passed to the dismantler.

424
00:23:26,550 --> 00:23:30,930
So I recall that it's
dynamic and static data.

425
00:23:30,930 --> 00:23:35,340
Static data is the data
that doesn't change along

426
00:23:35,340 --> 00:23:35,970
the lifecycle.

427
00:23:35,970 --> 00:23:39,940
Dynamic data is what we
call summary statistics.

428
00:23:39,940 --> 00:23:44,070
So these are updated data.

429
00:23:44,070 --> 00:23:47,250
For example, in this
case, the number of engine

430
00:23:47,250 --> 00:23:51,100
startups versus the
outside temperature.

431
00:23:51,100 --> 00:23:57,780
So this data is given
to the dismantler.

432
00:23:57,780 --> 00:24:02,760
Plus the cost
models in the sense

433
00:24:02,760 --> 00:24:08,340
that we have to know if there
is a business behind dismantling

434
00:24:08,340 --> 00:24:11,500
these components.

435
00:24:11,500 --> 00:24:14,590
And the final result
should be a list

436
00:24:14,590 --> 00:24:19,570
of the components inside the
car from the component which

437
00:24:19,570 --> 00:24:23,290
is most interesting
to be dismantled

438
00:24:23,290 --> 00:24:27,050
to the less interesting one.

439
00:24:27,050 --> 00:24:33,690
This information is
passed back to the list,

440
00:24:33,690 --> 00:24:41,360
to the database of spare parts,
and to the components, where

441
00:24:41,360 --> 00:24:45,020
it is printed on the RFID.

442
00:24:45,020 --> 00:24:48,950
So in some way, the
RFID is certified.

443
00:24:48,950 --> 00:24:55,440
We say that the
component is 50% good.

444
00:24:55,440 --> 00:24:59,730
So it has a residual
life of 50%.

445
00:24:59,730 --> 00:25:05,230
This leaves to the
component detachment.

446
00:25:05,230 --> 00:25:11,330
And what are we
doing in this period?

447
00:25:11,330 --> 00:25:15,320
We are testing this approach.

448
00:25:15,320 --> 00:25:18,900
As I said before, there is a
lot of technical constraints

449
00:25:18,900 --> 00:25:21,980
behind this component.

450
00:25:21,980 --> 00:25:23,780
There are a lot of
technical constraints

451
00:25:23,780 --> 00:25:26,390
behind this concept.

452
00:25:26,390 --> 00:25:28,460
So we are currently
doing some tests

453
00:25:28,460 --> 00:25:31,460
on static vehicle
for the time being,

454
00:25:31,460 --> 00:25:36,380
and then on working vehicles.

455
00:25:36,380 --> 00:25:42,450
We have developed
prototypes of the DSS, which

456
00:25:42,450 --> 00:25:45,480
is kind of proof of concept.

457
00:25:45,480 --> 00:25:50,700
Unfortunately, I wanted to
come with this demonstrator

458
00:25:50,700 --> 00:25:56,800
right now, but I think passing
the costumes would be strange,

459
00:25:56,800 --> 00:25:59,920
and components would have
been quite difficult.

460
00:25:59,920 --> 00:26:02,440
So that would be
for another time.

461
00:26:02,440 --> 00:26:09,420
And so we have a lot
of consistency issues

462
00:26:09,420 --> 00:26:16,860
to test with this approach.

463
00:26:16,860 --> 00:26:19,010
OK.

464
00:26:19,010 --> 00:26:23,870
So that's roughly another
view of this demonstrator

465
00:26:23,870 --> 00:26:24,790
that we have.

466
00:26:24,790 --> 00:26:27,170
The best we are
doing in this period

467
00:26:27,170 --> 00:26:31,960
and in the framework of
this European project.

468
00:26:31,960 --> 00:26:36,640
I think we have some,
maybe, four questions.

469
00:26:36,640 --> 00:26:38,390
PROFESSOR: We'll have
the questions again.

470
00:26:38,390 --> 00:26:39,670
GUEST SPEAKER 1: OK.

471
00:26:39,670 --> 00:26:41,086
That's fine.

472
00:26:41,086 --> 00:26:44,467
[APPLAUSE]

473
00:26:47,093 --> 00:26:48,510
PROFESSOR: And so
our next speaker

474
00:26:48,510 --> 00:26:50,910
is Professor Bernd
Scholz-Reiter,

475
00:26:50,910 --> 00:26:52,950
who is the professor
and director of Planning

476
00:26:52,950 --> 00:26:56,100
and Control Production Systems
at the University of Bremen.

477
00:27:11,047 --> 00:27:12,880
And actually, while
you're bringing that up,

478
00:27:12,880 --> 00:27:14,400
I should say that
you had arranged

479
00:27:14,400 --> 00:27:21,720
to have the director of the
Daimler Chrysler RFID effort

480
00:27:21,720 --> 00:27:23,140
here, or that was--

481
00:27:23,140 --> 00:27:23,640
right?

482
00:27:23,640 --> 00:27:26,550
And then at the last minute,
there was a scheduling issue.

483
00:27:26,550 --> 00:27:30,348
But I assume you'll
be talking about that.

484
00:27:30,348 --> 00:27:32,765
BERND SCHOLZ-REITER: A little
bit about that product, yes.

485
00:27:48,350 --> 00:27:50,030
Good afternoon,
ladies and gentlemen.

486
00:27:53,040 --> 00:27:56,850
At the University of Bremen,
we have a so-called CRC,

487
00:27:56,850 --> 00:27:59,550
a Collaborative
Research Center, which

488
00:27:59,550 --> 00:28:02,190
is funded by the German
Science Foundation

489
00:28:02,190 --> 00:28:07,500
and is the long-term research
of about nearly 12 years.

490
00:28:07,500 --> 00:28:10,530
And in this collaborative
research center,

491
00:28:10,530 --> 00:28:16,140
we are now working about 80
researchers of four faculties,

492
00:28:16,140 --> 00:28:17,700
so in different disciplines.

493
00:28:17,700 --> 00:28:23,820
And they try to investigate
how conventional control,

494
00:28:23,820 --> 00:28:29,160
which usually is applied now
in our industry nowadays,

495
00:28:29,160 --> 00:28:33,240
could be transferred
to autonomous control,

496
00:28:33,240 --> 00:28:36,780
which will be able,
in our opinion,

497
00:28:36,780 --> 00:28:41,730
to be applied in a couple of
years when we have the RFIDs

498
00:28:41,730 --> 00:28:47,200
of the future, which means RFIDs
which cannot only store data

499
00:28:47,200 --> 00:28:54,780
but also are able to calculate
information and make their own

500
00:28:54,780 --> 00:29:00,450
decisions and gather data from
their environment and exchange

501
00:29:00,450 --> 00:29:04,875
this data with other intelligent
objects which are also--

502
00:29:08,700 --> 00:29:13,890
which also have these RFID
chips of the future on board.

503
00:29:13,890 --> 00:29:19,980
So our idea is that we can
work on autonomous control

504
00:29:19,980 --> 00:29:24,060
and logistic processes
and figure out

505
00:29:24,060 --> 00:29:27,000
where the limitations
are in our days,

506
00:29:27,000 --> 00:29:30,420
where the limitations are
in different business cases,

507
00:29:30,420 --> 00:29:34,140
and where the limitations
are in different situations

508
00:29:34,140 --> 00:29:37,530
in these specific
business cases.

509
00:29:37,530 --> 00:29:42,300
The main idea is every logistic
item will be intelligent

510
00:29:42,300 --> 00:29:43,830
and future based.

511
00:29:43,830 --> 00:29:56,940
On this basic research, we also
are on the floor of research.

512
00:29:56,940 --> 00:29:59,310
And we work together
with industry

513
00:29:59,310 --> 00:30:03,210
and RFID implementation
projects.

514
00:30:03,210 --> 00:30:06,030
And two of these
RFID implementation

515
00:30:06,030 --> 00:30:08,160
projects we are
involved in I would

516
00:30:08,160 --> 00:30:11,280
like to introduce to you now.

517
00:30:11,280 --> 00:30:17,220
The first one is a
logistics project

518
00:30:17,220 --> 00:30:19,710
in automobile
logistics, which means

519
00:30:19,710 --> 00:30:24,960
that we have an automobile
logistics provider who

520
00:30:24,960 --> 00:30:30,720
transports the finished
cars from the automobile

521
00:30:30,720 --> 00:30:38,250
manufacturer, which is shown
here on the upper-left corner,

522
00:30:38,250 --> 00:30:41,700
to a terminal of the
automobile logistics

523
00:30:41,700 --> 00:30:46,410
provider on the right-hand side,
and from there to automobile

524
00:30:46,410 --> 00:30:50,700
dealers or automobile traders,
which are on the lower

525
00:30:50,700 --> 00:30:52,270
left-hand side.

526
00:30:52,270 --> 00:30:56,760
So the cars leave
the assembly line,

527
00:30:56,760 --> 00:31:00,690
for example, here, and
are stored somewhere

528
00:31:00,690 --> 00:31:05,340
on the plant area.

529
00:31:05,340 --> 00:31:06,240
Sorry for that.

530
00:31:12,800 --> 00:31:17,920
And are stored somewhere on
the plant area of the OAM.

531
00:31:17,920 --> 00:31:22,240
Then the automobile logistics
provider took them up,

532
00:31:22,240 --> 00:31:28,240
take them up, and transport them
to the area of the terminals,

533
00:31:28,240 --> 00:31:33,310
of his own terminal, where
some technical operations will

534
00:31:33,310 --> 00:31:35,080
be done on the cars.

535
00:31:35,080 --> 00:31:44,170
For example, to erase
the bags before the car

536
00:31:44,170 --> 00:31:49,990
will be sold to the
automobile trader.

537
00:31:49,990 --> 00:31:55,330
And also to assemble
additional technical equipment.

538
00:31:55,330 --> 00:31:58,840
For example, s navigation
systems and so on.

539
00:31:58,840 --> 00:32:03,370
And also on this area, of
course, the cars are stored.

540
00:32:03,370 --> 00:32:08,230
And a typical terminal
here has about 10,000 cars

541
00:32:08,230 --> 00:32:09,130
which are stored.

542
00:32:09,130 --> 00:32:13,930
And this is not very easy to
store them and find them back,

543
00:32:13,930 --> 00:32:20,380
and also to do this
in a proper way

544
00:32:20,380 --> 00:32:23,680
with minimal transport
time, and so on.

545
00:32:23,680 --> 00:32:27,970
And afterwards, the cars
leave again on trucks

546
00:32:27,970 --> 00:32:30,820
to, for example, to
the dealers, where

547
00:32:30,820 --> 00:32:38,170
they are stored again until they
are sold to the end consumer.

548
00:32:38,170 --> 00:32:41,320
And the question
now is, how can we

549
00:32:41,320 --> 00:32:48,580
support this process with
another ICT technology

550
00:32:48,580 --> 00:32:55,480
and support this process
also with RFID technology?

551
00:32:55,480 --> 00:32:59,020
Because of our Collaborative
Research Center,

552
00:32:59,020 --> 00:33:03,790
the automobile
logistics provider Hans

553
00:33:03,790 --> 00:33:05,965
asked us to support them.

554
00:33:05,965 --> 00:33:10,330
Hans is an automobile
logistics service

555
00:33:10,330 --> 00:33:13,900
provider for new and used cars.

556
00:33:13,900 --> 00:33:17,140
And it's in the
range of transport

557
00:33:17,140 --> 00:33:20,500
not only but also technical
treatment, storage,

558
00:33:20,500 --> 00:33:22,540
and handling of cars.

559
00:33:22,540 --> 00:33:24,940
It has auto terminals.

560
00:33:24,940 --> 00:33:28,510
Of course, transport
and car shipping.

561
00:33:28,510 --> 00:33:34,190
And its field of action
is all over Europe,

562
00:33:34,190 --> 00:33:40,150
so its the biggest automobile
logistics provider in Europe.

563
00:33:40,150 --> 00:33:44,890
And it transports not only
the cars but trucks also

564
00:33:44,890 --> 00:33:51,170
by vessels, rail,
and inland shipping,

565
00:33:51,170 --> 00:33:57,820
as well as short shipping
along the coast in Europe.

566
00:33:57,820 --> 00:34:02,650
And what we do is we
should investigate

567
00:34:02,650 --> 00:34:06,730
several possible fields of
application of RFID systems

568
00:34:06,730 --> 00:34:09,639
based on the processes.

569
00:34:09,639 --> 00:34:13,630
And the first step,
we limited ourself

570
00:34:13,630 --> 00:34:18,969
to an idealized automobile
turn of the company Hans.

571
00:34:18,969 --> 00:34:21,940
This is the current
state of this process,

572
00:34:21,940 --> 00:34:24,850
and you see the weaknesses here.

573
00:34:24,850 --> 00:34:31,150
We apply at this stage
only barcode labels.

574
00:34:31,150 --> 00:34:34,060
So the documentation
of the vehicle

575
00:34:34,060 --> 00:34:40,270
movements our only via
barcode scanners or keyboards.

576
00:34:40,270 --> 00:34:45,940
The barcode is very weak because
raindrops condensate or snow

577
00:34:45,940 --> 00:34:51,429
on the windscreen make scanning
unreliable or also impossible.

578
00:34:51,429 --> 00:34:54,790
The barcode labels bleach when
exposed to direct sunlight,

579
00:34:54,790 --> 00:34:56,020
for example.

580
00:34:56,020 --> 00:35:01,990
And this can cause incorrect
or incomplete data acquisition.

581
00:35:01,990 --> 00:35:08,590
And, of course, it's also
then we have a result

582
00:35:08,590 --> 00:35:10,690
of high consequential costs.

583
00:35:15,090 --> 00:35:20,080
The solution we figured out
between different alternatives

584
00:35:20,080 --> 00:35:26,190
is now that we have an RFID
label on the windshield,

585
00:35:26,190 --> 00:35:30,000
protection foil integrated
in this windshield protection

586
00:35:30,000 --> 00:35:35,910
foil, which is the
passive RFID label.

587
00:35:35,910 --> 00:35:41,940
And on this automobile
terminal, the handling driver

588
00:35:41,940 --> 00:35:47,190
has a portable data terminal.

589
00:35:47,190 --> 00:35:53,680
And when he approaches
a car, there

590
00:35:53,680 --> 00:35:57,820
is the connection of
communication between the PDT

591
00:35:57,820 --> 00:35:59,950
and the passive transponder.

592
00:36:02,580 --> 00:36:07,650
The PDT can be located via GPS.

593
00:36:07,650 --> 00:36:14,520
So if the connection here exists
and the PDT is moving somewhere

594
00:36:14,520 --> 00:36:19,080
around the terminal, you
know that the car has moved

595
00:36:19,080 --> 00:36:20,340
somewhere around the terminal.

596
00:36:22,940 --> 00:36:29,210
And then you can communicate
the data to the IT systems.

597
00:36:29,210 --> 00:36:34,460
So to the scanning and control
system of the automobile

598
00:36:34,460 --> 00:36:35,960
logistics provider.

599
00:36:35,960 --> 00:36:39,170
That is the solution which
is now under development

600
00:36:39,170 --> 00:36:42,470
to support this
automobile logistics

601
00:36:42,470 --> 00:36:47,780
process and the first step
on the area of the automobile

602
00:36:47,780 --> 00:36:49,340
terminal.

603
00:36:49,340 --> 00:36:54,920
The second case study in
the automotive industry

604
00:36:54,920 --> 00:36:58,550
is tracking and tracing of
returnable transport items

605
00:36:58,550 --> 00:37:02,450
this is a project involving
Siemens Business Services,

606
00:37:02,450 --> 00:37:05,130
Red Ants, and my institute,
the BIBA Institute.

607
00:37:05,130 --> 00:37:07,670
We have two pilot
installations--

608
00:37:07,670 --> 00:37:10,550
Daimler Chrysler
and Lia Corporation

609
00:37:10,550 --> 00:37:15,950
as the seat supplier
of Daimler Chrysler.

610
00:37:15,950 --> 00:37:18,990
The supply chain
looks like this.

611
00:37:18,990 --> 00:37:21,740
We have the supplier
here, the seat supplier,

612
00:37:21,740 --> 00:37:23,450
and the production.

613
00:37:23,450 --> 00:37:29,780
Of course, a lot of the seats on
the returnable transport items.

614
00:37:29,780 --> 00:37:32,480
Afterwards, the
delivery by truck

615
00:37:32,480 --> 00:37:39,290
to an inbound buffer of the
OEM of Daimler Chrysler here.

616
00:37:39,290 --> 00:37:43,310
Then the unload of
the seats and assembly

617
00:37:43,310 --> 00:37:46,160
directly on the assembly line.

618
00:37:46,160 --> 00:37:55,100
Afterwards, empty RTIs go either
to repair or return directly

619
00:37:55,100 --> 00:38:01,160
to transport to the ingoing
buffer of the supplier.

620
00:38:01,160 --> 00:38:04,160
And on different stages
here in this process,

621
00:38:04,160 --> 00:38:07,190
we can implement RFID readers.

622
00:38:07,190 --> 00:38:20,450
And all the RTIs are also
equipped with this RFIDs.

623
00:38:20,450 --> 00:38:24,320
This as a project, goals
here-- improvement of process

624
00:38:24,320 --> 00:38:26,210
reliability, of course.

625
00:38:26,210 --> 00:38:29,690
So delivery of seat
in the right sequence

626
00:38:29,690 --> 00:38:31,190
and also in the right order.

627
00:38:31,190 --> 00:38:34,670
Left or right seat
in the car, which

628
00:38:34,670 --> 00:38:40,430
was a problem in former times.

629
00:38:40,430 --> 00:38:43,790
And the main goal, of
course, is reduction

630
00:38:43,790 --> 00:38:48,410
of cost and complexity
and the reduction

631
00:38:48,410 --> 00:38:51,650
of the circulating
assets or reduction

632
00:38:51,650 --> 00:38:54,170
of the number of RTIs.

633
00:38:54,170 --> 00:38:56,700
The technical solution
looks like this.

634
00:38:56,700 --> 00:39:04,580
We have two passive transponders
or smart labels on the RTIs.

635
00:39:04,580 --> 00:39:09,620
Two because of the reading
distance and the direction

636
00:39:09,620 --> 00:39:16,880
of the RTI to the
reading facilities.

637
00:39:16,880 --> 00:39:21,050
And we have one
removable transponder

638
00:39:21,050 --> 00:39:23,750
at this stage on the seat frame.

639
00:39:23,750 --> 00:39:26,570
The removable
transponder will be--

640
00:39:29,360 --> 00:39:33,380
later on will be integrated
in the frame of the seat

641
00:39:33,380 --> 00:39:38,010
and will be there for
the whole lifetime

642
00:39:38,010 --> 00:39:43,310
so it has then some connections
to the promise project.

643
00:39:43,310 --> 00:39:45,990
That was just a
short introduction

644
00:39:45,990 --> 00:39:53,210
to two implementation projects
with industry we conduct.

645
00:39:53,210 --> 00:39:56,360
But based on the
basic research, I

646
00:39:56,360 --> 00:40:00,080
have also mentioned this
investigation of autonomous

647
00:40:00,080 --> 00:40:03,405
control for logistic processes.

648
00:40:03,405 --> 00:40:05,030
Thank you very much
for your attention.

649
00:40:05,030 --> 00:40:08,006
[APPLAUSE]

650
00:40:11,490 --> 00:40:13,810
PROFESSOR: So any questions
for our panelists?

651
00:40:13,810 --> 00:40:16,738
If we could ask you to
come up to the microphone.

652
00:40:28,050 --> 00:40:28,550
Thank you.

653
00:40:38,860 --> 00:40:41,020
AUDIENCE: It's a long way down.

654
00:40:41,020 --> 00:40:45,460
University of Bremen was
doing some testing projects

655
00:40:45,460 --> 00:40:48,340
with cool chain temperature
monitoring of trucks and things

656
00:40:48,340 --> 00:40:49,630
of that nature.

657
00:40:49,630 --> 00:40:54,840
Is this project associated with
that one at all, do you know?

658
00:40:54,840 --> 00:40:58,330
BERND SCHOLZ-REITER: It's
not associated directly,

659
00:40:58,330 --> 00:41:02,380
but it has also something to
do with some colleagues of mine

660
00:41:02,380 --> 00:41:06,790
were also involved in this
collaborative research center.

661
00:41:06,790 --> 00:41:08,200
AUDIENCE: OK.

662
00:41:08,200 --> 00:41:13,510
So the same autonomous logistics
process and taking everything

663
00:41:13,510 --> 00:41:16,990
from centralized to a
localized control thing

664
00:41:16,990 --> 00:41:19,960
is going to be merged
with the other data.

665
00:41:19,960 --> 00:41:22,060
Are you taking the
two projects together

666
00:41:22,060 --> 00:41:23,560
for the results
at all, or are you

667
00:41:23,560 --> 00:41:26,350
just comparing some different
parts of the projects?

668
00:41:26,350 --> 00:41:28,600
BERND SCHOLZ-REITER: You
mean these two projects here,

669
00:41:28,600 --> 00:41:30,870
what I've introduced to do?

670
00:41:30,870 --> 00:41:31,480
AUDIENCE: Yes.

671
00:41:31,480 --> 00:41:33,980
BERND SCHOLZ-REITER: No, they
are not related to each other.

672
00:41:33,980 --> 00:41:38,770
So the automobile final
product logistic process

673
00:41:38,770 --> 00:41:41,608
is not related to the RTI.

674
00:41:41,608 --> 00:41:42,150
AUDIENCE: OK.

675
00:41:42,150 --> 00:41:44,140
BERND SCHOLZ-REITER:
Because this RTI

676
00:41:44,140 --> 00:41:46,720
is this closed
loop thing and has

677
00:41:46,720 --> 00:41:50,190
nothing to do with the
parts or the products.

678
00:41:50,190 --> 00:41:53,368
It's just the means
of transportation.

679
00:41:53,368 --> 00:41:53,910
AUDIENCE: OK.

680
00:41:53,910 --> 00:41:54,460
Thank you.

681
00:41:54,460 --> 00:41:56,252
BERND SCHOLZ-REITER:
Of parts and assembly.

682
00:42:00,035 --> 00:42:01,520
PROFESSOR: I know,
in the context

683
00:42:01,520 --> 00:42:04,160
that we have people from a
number of different countries

684
00:42:04,160 --> 00:42:06,260
and continents here,
one question that's

685
00:42:06,260 --> 00:42:08,430
come up specific to
the automotive industry

686
00:42:08,430 --> 00:42:11,900
but that may be affecting
many of our other industries

687
00:42:11,900 --> 00:42:15,980
is just whether there's a global
standard for identification

688
00:42:15,980 --> 00:42:20,270
or whether we come out by
continent or by even by company

689
00:42:20,270 --> 00:42:23,180
in some cases with
our own ID systems.

690
00:42:23,180 --> 00:42:25,520
In the context that
you've all described

691
00:42:25,520 --> 00:42:27,530
fairly closed
systems, I wondered

692
00:42:27,530 --> 00:42:32,020
whether you had a comment in
that regard in your industry.

693
00:42:32,020 --> 00:42:35,050
BERND SCHOLZ-REITER:
This is a good question.

694
00:42:35,050 --> 00:42:41,130
I'll give you an example of
an mobile logistic process.

695
00:42:41,130 --> 00:42:44,440
There should be something
like an EPC code.

696
00:42:44,440 --> 00:42:48,390
But on the barcode level,
there is no agreement so far.

697
00:42:48,390 --> 00:42:53,430
So they have, with every OEM,
they have their own bar code.

698
00:42:53,430 --> 00:42:57,300
And also, the logistics provider
have their own bar code.

699
00:42:57,300 --> 00:43:02,200
And the ideas are not
comparable to each other.

700
00:43:02,200 --> 00:43:06,810
So on the other side, we have
in Germany the Association

701
00:43:06,810 --> 00:43:11,460
of the German Automotive OEMs.

702
00:43:11,460 --> 00:43:15,000
And now, for this
RFID purpose, they

703
00:43:15,000 --> 00:43:18,480
are sitting together to
get a common agreement

704
00:43:18,480 --> 00:43:21,900
on the ID, which
should be stored

705
00:43:21,900 --> 00:43:27,870
on this passive
tech, which should

706
00:43:27,870 --> 00:43:31,920
be integrated in this
windshield protection form.

707
00:43:31,920 --> 00:43:38,500
But this is the first
attempt to do it.

708
00:43:38,500 --> 00:43:41,610
It failed in the barcode
area, and now, they

709
00:43:41,610 --> 00:43:46,878
tried to do it now.

710
00:43:46,878 --> 00:43:48,420
PROFESSOR: Well,
thank you very much.

711
00:43:48,420 --> 00:43:50,570
Just so you know,
Nick Ferguson, who's

712
00:43:50,570 --> 00:43:52,880
actually in this room
somewhere, has the charter

713
00:43:52,880 --> 00:43:56,090
to try to help organize the
automotive industry or more

714
00:43:56,090 --> 00:43:59,840
of a global basis to avoid
that fragmentation that

715
00:43:59,840 --> 00:44:01,200
occurred in the bar code.

716
00:44:01,200 --> 00:44:06,920
So he would be the contact
person in the EPCglobal group

717
00:44:06,920 --> 00:44:09,140
that's working on that area.

718
00:44:09,140 --> 00:44:12,140
GUEST SPEAKER 1:
Just another comment

719
00:44:12,140 --> 00:44:19,520
is that just as the aeronautics,
a lot of system providers--

720
00:44:19,520 --> 00:44:22,430
I mean, component makers--

721
00:44:22,430 --> 00:44:26,720
are also working for
different companies.

722
00:44:26,720 --> 00:44:29,270
I have the example
of Manetti Marelli,

723
00:44:29,270 --> 00:44:31,760
which is doing components
on not only for Fiat.

724
00:44:31,760 --> 00:44:36,860
It's also for a Mercedes Benz
or outside Europe as well.

725
00:44:36,860 --> 00:44:42,557
So there is a tendency
to define standards.

726
00:44:42,557 --> 00:44:44,390
PROFESSOR: There's a
reason that the Auto ID

727
00:44:44,390 --> 00:44:46,750
Center was initially
founded by suppliers

728
00:44:46,750 --> 00:44:49,000
who were dealing with
very large customers that

729
00:44:49,000 --> 00:44:52,010
had all their own way
of looking at things.

730
00:44:52,010 --> 00:44:54,730
And so that's true in
your industry as well.

731
00:44:54,730 --> 00:44:56,140
Well, thank you very much.

732
00:44:56,140 --> 00:44:57,990
[APPLAUSE]