Fraunhofer-Institute for Optronics System Fraunhofer - Q-DAS

Transcription

Fraunhofer Institute for Optronics,
Fraunhofer-Institute
Optronics System
Technology and Image Exploitation IOSB
Industry 4.0 – a new paradigm in German manufacturing
Olaf Sauer
Kosmonosy, September 14, 2012
Karlsruhe
Seite 1
© Fraunhofer IOSB
Ettlingen
Ilmenau
Lemgo
Fraunhofer IOSB-overview
CEO
CEOs:
Prof. Dr.-Ing. Jürgen Beyerer
Prof. Dr. Maurus Tacke
Presentation Industry 4.0 Q-DA
P
AS
Core competencies:
Optronics
System technology
Vi i ttechnology
Vision
h l
Business units:
Automation
Energy, water, environment
Automated Visual Inspection
Defence
Security
Cooperation with:
Seite 2
 Fraunhofer IOSB, BU Automation, 2012
Key figures:
Budget 2012
Total staff
Scientists and engineers
41 Mio. €
405
267
Students
130
Faculty for computer science, Institute for anthropomatics,
Chair for interactive realtime systems
P
AS
Realtime
IT for
complex manufacturing processes
Das Geschäftsfeld
Automatisierung
Seite 3
Service offering of the Business Unit “Automation”
Production monitoring and MES
Adaptive information technology
Process and condition monitoring
Autonomous robots
MES-level
Vertical
i t
integration
ti
Information
model
Horizontal
integration
Industrial communication
P
AS
Industrial Smart Grids
Field device-level
Qualification and training for experts and executives
Seite 4
Life cycle
Karlsruher Leit- und Automatisierungstechnische Akademie
1. Starting point for our work in information technology: monitoring &
control system for Daimler in press, body, paint, trim shop
C t l control
Central
t l room in
i the
th B
Bremen plant
l t
The integrated monitoring & reporting system for Daimler
consists of
® for monitoring
- ProVis.Agent
g
g & control,,
- ProVis.Visu® for real-time visualization,
- ProVis.Paula® for web based reporting.
P
Process
iimage off an assembly
bl liline
In the Bremen plant ProVis.Agent monitors app. 450 PLCs of
app. 2.000 machines/facilities in body, paint and trim shop
In the Woeth plant (commercial vehicles) we have delivered
ProVis.Agent incl. online body tracking, central shift calender,
integration of EMOS (Durr-monitoring system, paint shop)
Presentation Q-DAS 14092012
P
Example for ProVis.PAULA-GUI
The web based reporting system for manufacturing and
machine data based on content management
g
system
y
WebGenesis®, data amount Daimler Bremen:
1 TByte raw data/35d, 2.000 facilities, app. 1.600 users
Page 5
Source: Getty im
magaes
SSource: Gozarian.ccom
2. What does “Industry 4.0” mean?
First mechanical
spinning frame,
1764
First PLC: Modicon 084
1968
FORD‘s assembly line
1913
Source: WIKIPEDIA;
Wateerframe.jpg
Source: Photosearch.de
4th industrial revolution:
based on cyber physical
systems
3rd industrial revolution:
numerical/programmable
p g
controllers, automation
2nd industrial revolution:
assembly line, era of
mass production
P
1st industrial revolution:
mechanisation of the
t til industry
textile
i d t
end of 18th century
Page 6
20th century
1970ies
today
2. Industry 4.0 and the future factory
Functions (examples):
- communication, negotiation
- interpretation, configuration
- visualization, simulation
- capacity balancing
- APP-store for MES-functions
Specifications,
p
delivery dates,
amounts
Customers
CPS manufacturing cloud
Part suppliers
D li
Delivery
dates
d t
Product specification,
p
geometry, kinematics,
BOM, work plan
P
Product developer
Product specifications,
work p
plans,,
BOM,
orders, deadlines,
Material availability ,
long
g term capacities
p
Manufacturing
operators
Page 7
Material, capacities,
delivery dates,
amounts
Manufacturing equipment and
self description,
geometry, kinematics, logic
Machine and
equipment suppliers
3.1 Aspects of Industry 4.0: Interoperability in information technology for
manufacturing
 software
f
embedded
b dd d in ffield
ld d
devices, which
h h are connected
db
by the
h field
f ld bus,
b
e.g. in sensors, actuators, drives, valves, etc.;
 th
the control
t l software
ft
off machinery
hi
and
d equipment,
i
t e. g. programmable
bl
logic controllers (PLCs);
 the software managing the equipment
equipment, e.
e g.
g SCADA,
SCADA manufacturing
execution systems – MES, etc.
P
GOAL: standard interface (USB-mechanisms) for the factory
Page 8
New
e facility
ac ty identified!
de t ed
3.1 Required components for plug-and-work methodology
MES 1
MES 2
MES m
Decoder
Decoder
Decoder
Plug-and-produce
Plug
and produce middleware
Encoder
Encoder
Encoder
Facility1
Facility2
Facilityn
Digital factory
P
Encoder
Page 11
3.1 Developed and patented methodology
Producer
or
MES
MESsupplier
MES-systems
Decoder: allows specific
access/navigation to the
data model
Machine
supplier
Encoder („driver“):
interprets incoming data
to CAEX-data model
various
description formats
Self description
p
of a single
g
facility/machine
P
specific
filter
Page 12
Data from
‚Digital factory‘
Plug-and-work
middleware:
XML-based
Data model
(here CAEX) as
global name
space of an OPCUA-server
Material flow data,, layouts,
y
,
shift model, etc.
3.1 Example for plug-and-work benefits
Potential for savings at MES-/Monotoring-systems or
HMI; example ProVis.Agent®
Assumptions:
P
 total= app. 25%
Page 13
Invest monitoring system:
500.000 €
Monitored PLCs per system: 250
Efforts per PLC for Image-,
IO and
IOd ffacility
ilit engineering
i
i
=> Total engineering efforts
Cost per day engineering:
total cost engineering:
2-5
2
5 days
d
app. 500 days
500 €
250.000 €
Potential for savings by
plug-and-work: app. 80%
200.000 €
3.1 Example for plug-and-work effects
Example of a
demonstrator:
- TS1: test station
- DT1: turn table
bl
- TB1: transport belt 1
- TB2: transport belt 2
+ various variables and
values
P
completely! generated
f
from
self
lf description
d
i i
off
facilities including
topology information from
layout planning
Next step:
- test with real facility at
D i l Woerth
Daimler
W
h
Page 14
Transportieren
Name: TB2
Process: Transportation
Status: active
Transportieren
Prüfen
Drehen-umsetzen
Type: engine block-XYZ
ID: m3867115
3.2 Aspects of Industry 4.0: Gesture interaction
 Technology: gesture
recognition and man
manmachine-interaction
instead of keyboard,
mouse,, touch-screen
 Multi-user/multi display
interaction
P
 Benefits: time saving,
for gestures can be
recognized directly on
the object, e.g. quality
inspection
Page 15
3.3 Aspects of Industry 4.0: machine builders of the future
Development of machine sales in Germany and
China (Source: VDMA: Maschinenbau in Zahl und Bild 2012)
Examples for product services for today's customers
(Source: Fraunhofer ISI, Modernisierung der Produktion: Nutzen statt
Produkte kaufen)
[Bio. €]
600
563
500
400
Optimization contracts
during
g operation
China
200
215 209
221
4%
7%
2%
Currently in use
Pay-on-production 3% 1%
Pilot project
154
LCC guaranty 3% 1%
77
2003
2007
P
0
12%
Germany
300
100
Availability guaranty
Page 16
2011
0
5
10
15
20 %
Average share of components/competencies in today’s machines
(Source: VDMA – Forum IT@Automation)
80
70
73
60
70
50
2008
40
2012
30
20
10
0
18
9
10
Software
P
20
IT Hardware/
IT-Hardware/
Electronics
Mechanics
13% of machine builders: „Products consist less than 50% of hardware”
Page 17
 IT-based services lead to new business models
P
 For machine builders also software will become a product
Page 18
4 Conclusions
 Internet and mobile devices from the office are also used on the shop floor
 iPads, smart phones, Ethernet factory wide;
Security and availability are required
 Degree of software in conventional mechanical products increase
 organizational structure and process organization will change towards
software development, tests, etc.; opportunities for new business models
 The separate disciplines industrial engineering, automation and IT merge
 increasing demands concerning interdisciplinary cooperation;
new degree programs, lifelong qualification, new ways of cooperation
 Supplier structure / different software vendors do not support integrated use of IT
 interoperability and standards are overdue
P
 Risk of data-, information- and functional ‘overkill‘
 assistant functions, role based access, new GUIs, semantic search, etc., required
 ‚automation of automation‘
 configuration and parameterization instead of programming
Page 19
For further information please join us:
19 and
19.
d 20
20. S
September
t b 2012
Testing platform – Industrial IT Lab
•
R&D-platform „IT-based automation“
•
All IT-processes from the sensor up to
the control room
•
Multi-vendor equipment
P
Supported by:
Page 21
Imprint
Dr. Olaf Sauer
olaf.sauer@iosb.fraunhofer.de
www.mes.fraunhofer.de
www.klkblog.de
P
Tel.: +49-721-6091-477
Page 22

Fraunhofer-Institute for Optronics System Fraunhofer - Q-DAS

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