DIGITAL TWIN - e-university.tu-sofia.bg
Transcript of DIGITAL TWIN - e-university.tu-sofia.bg
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Jivka OvtcharovaKarlsruhe Institute of Technology (KIT) I Karlsruhe I Germany
© Jivka Ovtcharova I 1
Seamless Engineering in the Industry 4.0 Era
DIGITAL TWIN
XXX International Scientific Conference ELECTRONICS - ET2021 I September 15, 2021 I Sozopol, Bulgaria
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Jivka OvtcharovaKarlsruhe Institute of Technology (KIT) I Karlsruhe I Germany
© Jivka Ovtcharova I 2
Seamless Engineering in the Industry 4.0 Era
DIGITAL TWIN
XXX International Scientific Conference ELECTRONICS - ET2021 I September 15, 2021 I Sozopol, Bulgaria
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© Jivka Ovtcharova I 3
Our competences, our visions
ABOUT US
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Karlsruhe Institute of Technology
© Jivka Ovtcharova I 4Source: own representation
The Research University in the Helmholtz Association.
2009Karlsruhe Institute of Technology
1825Karlsruhe University
1956Research Center
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Institute for Information Management
Knowledge Screening
(Big) Data Analytics
(Engineering)Data Acquisition
Human-MaschineInteraction
FeedbackManagement
Data Modeling and Simulation
Practical Implementation
Virtual & Experimental
Validation
Lifecycle Engineering
Virtual Environments
© Jivka Ovtcharova I 5Source: Ovtcharova 2021
Make analytics come alive with Digital Twin Ecosystem.
View of the whole, at any moment!Deep Analytics
EDUCATION RESEARCH INNOVATION
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Industrie 4.0 Collaboration Lab
Opening24 September 2014
Hannover Fair14 April 2015
Award19 February 2016
Nordschwarzwald
© Jivka Ovtcharova I 6
Innovation Event Hangzhou 21 July 2017
…
„Sandbox“ for experiments in run-time environment. .Source: Industrie 4.0 Collaboration Lab (KIT)
ENSAM Institute Image 5 October 2017
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Virtual Environments LabCAVE VR system
Mixed Reality LabDriving Simulation,, HTC, HoloLens,
haptic Interaction
Communication LabCo-Working-and-Sharing-Space
International Cooperation LabChina, France, Bulgaria, etc.
Value Creation LabIndustrial Case Studies and
Implementation
Experience LabDigital Twin Solutions
Content Creation LabDevelopment and Training with CAx/PLM
Tea LabCreativity-Think-Tank
Source: Ovtcharova 2018 © Jivka Ovtcharova I 7
Lifecycle Engineering Solutions Center
innovate
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Why, What, How?
DIGITAL TWIN
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Why, What, How?
DIGITAL TWIN
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The Beginning of Industry 4.0
Computers and automation come together in a new way.
Dream team: Prof. Kagermann, acatech Prof. Wahlster, DFKI Prof. Lukas, BMBF
at the Hannover Fair in 2011
Source: acatech © Jivka Ovtcharova I 10
Smart manufacturing in focus: System interoperability I Internet of things Information transparency I Cloud computing Technical assistance I Cognitive manufacturing Decentralized decisions I Cyber-physical systems
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Causes and Consequences
End of the 18th century Beginning of the 20th century Beginning of the 70's Today
De
gre
e o
f In
no
vati
on
Time
Industrie 1.0
Mass production
Mechanizationhydro- and steam
power
Industrie 2.0
Mass distribution
Electrificationelectrical power and
vehicle mobility
Industrie 3.0
World economy
Automationcomputer and information
technology
Cyberizationsmart devices and humans, real time interconnections
Industry 4.0
Smart factory?
Industrie 4.0
Real-time economy!
© Jivka Ovtcharova I 11Source: Ovtcharova 2021
5G
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Real-time Economy
North America Latin America Europe Asia Africa
INTERNET-MAP 2003
North America Latin America Europe Asia
25 billion devices and 5 billion people on-line.
INTERNET-MAP 2015
Source: Gartner, Pictures: Festo / blog.kaspersky.com © Jivka Ovtcharova I 12
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The World is „All-in-One“
Pictures: Chess Wise BV, LESC (KIT), Arku GmbH
Real and artificial objects co-exist in real time and in space.
© Jivka Ovtcharova I 13
MERGING OF MATERIAL AND VIRTUAL (COMPUTER GENERATED
WALK-IN) REALITIES
PERCEPTION AND COMMUNICATION IN REAL
TIME AND IN SPACE
INTUITIVE HUMAN-COMPUTER INTERACTION (LOGICAL,
COMPREHENSIBLE, INTUITIVE) IN RUNTIME ENVIRONMENT
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Digital Twin: Status Quo
Mature and widespread implementation is missing.
© Jivka Ovtcharova I 14Pictures: Dassault Systèmes, IBM Watson IoT, GE
MODEL SEMANTICS IS MOSTLY GEOMETRY DRIVEN
ANALYTICS IS ALIGNED AND NOT EMBEDDED
SIMULATION AND USER INTERACTION ARE OFFLINE
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Why, What, How?
DIGITAL TWIN
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Definition
Digital representation of real units and processes interacting and synchronized with a certain accuracy and frequency:
• is system-of-systems,
• uses real-time and historical data,
• represents the past and present,
• simulates the future in a predictive way,
• is implemented in IT/OT systems.
Source: https://www.digitaltwinconsortium.org/glossary/ index.htm#digital-twin © Jivka Ovtcharova I 16
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Core Statement
The existence of a powerful infrastructure based on open, international standards is a prerequisite to:
• support human-twin interaction,
• meet non-functional requirements such as data sovereignty, privacy, and data usage control,
• ensure interoperability and synchronization.
© Jivka Ovtcharova I 17Source: https://www.digitaltwinconsortium.org/glossary/ index.htm#digital-twin
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Cybernetic model 60s
Bidirectional connectivity, at any moment!.
© Jivka Ovtcharova I 18Source: Norbert Wiener, MIT, Cybernetic model 60s, according to S. Böckl, 2005
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Technical capabilities that differentiate 5G
Source: Report ITU-R M.2410-0 (11/2017) Minimum requirements related to technical performance for IMT-202 radio interface(s)
Catalyst for economic growth is connectivity enabled by 5G.
© Jivka Ovtcharova I 19
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Challenges
5G leads to new frontiers of productivity and innovation.
© Jivka Ovtcharova I 20Pictures: IMI/KIT, Herrenknecht AG, LESC (IMI) Citation: adopted by Albert Einstein (1879 – 1955)
MODEL SEMANTICS IS USAGE DRIVEN AND ADAPTIVE
ANALYTICS IS INTERACTIVE AND EMBEDDED IN RUNTIME
IMPLEMENTATION GOES ALONG WITH EXPERIMENTS AND EXPERIENCES
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Why, What, How?
DIGITAL TWIN
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Three fundamentals
© Jivka Ovtcharova I 22Source: own presentation
Setting new norms, hands-on practices and skills.
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© Jivka Ovtcharova I 23
Reference Architectural Model Industry 4.0 (RAMI 4.0)
FUNDAMENTAL #1
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Overview
Image: Platform Industry 4.0
Derive rules for Industry 4.0 implementations.
© Jivka Ovtcharova I 24
Reference Architecture Model Industry 4.0 (RAMI 4.0) VDI, VDE and ZVE ensures that all participants involved in Industry 4.0 discussions understand each other.
LIFECYCLE FUNCTIONS
ARCHITECTURE
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Asset Administration Shell
Source: visit, 2018
Stores all data and I4.0 interfaces about assets.
© Jivka Ovtcharova I 25
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Industry 4.0 Component
Image: Platform Industry 4.0
Contain physical assets with their administration shells.
© Jivka Ovtcharova I 26
Communication capability of cyber-physical systems is described by real objects, which are networked with virtual objects and processes.
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Digital Twin
Image: Platform Industry 4.0
Bi-directional connectivity of Industry 4.0 components.
Real-time-capable handling of material and service systems in different versions over the entire life cycle.
Digital Twin
© Jivka Ovtcharova I 27
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Digital Twin
Image: Platform Industry 4.0
Bi-directional connectivity of Industry 4.0 components.
Digital Twin
© Jivka Ovtcharova I 28
Real-time-capable handling of material and service systems in different versions over the entire life cycle.
CHARACTERISTICS MEANING
Universality Generation, editing, distribution and playback
Availability Accessibility in different formats and data carriers from everywhere
Usability Multiple and multi-sided use, small space requirement
Portability Automatic processing, low transmission errors
Intelligence Quick search, evaluation, analysis and learning ability, mapping of decision and action sequences (algorithmization).
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Hands-on Practice
FUNDAMENTAL #2
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The „German Mittelstand“ is a Trademark
99,6 % of all companies
German thoroughness is no longer enough.
Source: BMWi/Eriksson, 10.04.2017, Pictures: Volksbank Münster © Jivka Ovtcharova I 30
58,5 % of all workplaces
81,8 % of all trainees
35,3 % of total sales
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15.2%
19.6%
32.6%
6.5%
8.7%
15.2%0 - 9
10-49
50 - 249
250 - 499
500 - 999
1000 und mehr
Example: Industry 4.0 for SMEs
Company profile • 46 Participants
• 50 % deal with VR
• above-average Interest
• Industrial sectors:
– Mechanical Engineering and Plants (26%)
– Information Technology (17%)
– Civil Engineering & Architecture (12%)
– Services (12%)
– Automotive (7%)
– Electronics (7%)
– others (19%)
Number of employees
Source: Analyse der Wirtschaftlichkeit der Virtual-Reality-Technologie im Kontext von Industrie 4.0, Masterarbeit J. Dücker, KIT, 2015 © Jivka Ovtcharova I 31
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Example: Industry 4.0 for SMEs
Identified hurdles• Insufficient knowledge about the topic
• Enormous time effort
• High investment risk
• Low acceptance among employees
• Low acceptance also among customers and suppliers
• No experiences in integration into business processes
• Lack of human resources and capacity
• Lack of appropriate software solutions
• Lack of practical experiences
• Missing professional skills and qualification
• Missing data preparation and analysis
• No meaningful applications
• others
Analysis of the results
© Jivka Ovtcharova I 32Source: Analyse der Wirtschaftlichkeit der Virtual-Reality-Technologie im Kontext von Industrie 4.0, Masterarbeit J. Dücker, KIT, 2015
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New practice for Industry 4.0
Traditional implementation Required implementation
Source: own representation © Jivka Ovtcharova I 33
Investment
Deployment
Added value?
Deployment
Added value!
Investment
„A virtual depot - what to practice“ is necessary.
VIRTUAL DEPOT
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„Sandbox“ Implementation
New skills for today's competition!
Pictures: Trumpf GmbH, Elabo GmbH, Siemens AG © Jivka Ovtcharova I 34
• Put real problems "in the sandbox“ of business units
• Think, try out, create “All-in-One“
• Apply emerging technologies playfully and quickly
• Test new solutions in runtime to gain experiences fast
• Transform knowledge into actions and skills
• Establish “Deep Digital Twin Engineering“ as a trademark
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© Jivka Ovtcharova I 35
New skills
FUNDAMENTAL #3
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Lifecycle Engineering
© Jivka Ovtcharova I 36Source: Ovtcharova 2021
Complete data acquisition, end-to-end process simulation.
Model-based Systems Engineering
Building Information Modeling
Product Lifecycle Management
Computer-Aided Design
Cyber Physical Systems
Applications
Processes
Real-time Tooling and Execution Digital Factory
Service Engineering
Customer Feedback Management
Smart Energy
Smart City
Digital Twin
Smart Mobility
Tools
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Deep Analytics
© Jivka Ovtcharova I 37Source: Ovtcharova 2021
Self learning algorithms, Knowledge-based Engineering.
Fast Knowledge Extraction
Semantic Data Structuring
Various (Big) Data Collection
Machine Learning
Self Learning Analysis
Applications
Processes
Human-Machine-Interface Brain-Computer -Interface
Social Networks
e-Governance
Service Robotics
Predictive Maintenance
Condition Monitoring
IoT Platforms
Tools
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Virtual Environments
© Jivka Ovtcharova I 38Source: Ovtcharova 2021
Merge of virtual and physical realities.
Real-time Simulation
Real-time Rendering
3D-Scanning and -Modelling
Scene Management
Virtual Process Modeling
Applications
Processes
Virtual Reality Engine „PolyVR“ Dynamic and Scalable SW/HW
Heritage
Serious Games
Medicine
Service Prototyping
Virtual Factory
Architecture
Tools
PolyVR
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© Jivka Ovtcharova I 39
Drive actions and deliver value
DIGITAL TWIN
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Human-centred engineering methods
© Jivka Ovtcharova I 40Pictures left: Forschungsunion, right: IMI/KIT/bechtle AG
Real-time networking of data, assets, services and people.
BACK-ENDDATA, INFRASTRUCTURE, TECHNOLOGY
FRONT-ENDEXPERIENCE, COGNITION, KNOWLEDGE
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Example IMI I KIT
Product and process simulation in real time.
© Jivka Ovtcharova I 41Videos: Industrie 4.0 Collaboration Lab (KIT)
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Commissioning with Digital Twin
• RAMS (Reliability, Availability, Maintainability, Safety) live
• Validation of machines and entire production lines
• Data homogenization and quality check
• Virtual testing of machine code
• Reduction of complexity and production errors
• Adaptation and reduction of interfaces
• Increasing transparency for end customers
• Increasing visibility and competitiveness
Do it right the first time!
© Jivka Ovtcharova I 42Pictures: Industry 4.0 Collaboration Lab (IMI/KIT)
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• Holistic training during and after development
• Early generation of technical documentation
• Shortening the time to real use
• Improving user-friendliness for different groups:
Developers, Engineers, Operators, Administrators,
Suppliers, Managers
• Optimization of condition monitoring and
predictive maintenance scenarios
Qualifying with Digital Twin
Learn it right the first time!
Pictures: Industry 4.0 Collaboration Lab (IMI/KIT), Video: IMI/KIT with Siemens AG – Power Generation Services Division / Siemens Power Academy, Karlsruhe © Jivka Ovtcharova I 43
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• For required 20 year service life
Installation costs = repair costs (1 Mio. €/MW)
• The operation costs: dramatically high
Crane 10.000 € / day, ship off-shore 100.000 € / day
• Damage costs due to failure: immense
• Simulation instead of putting „hands-on“
Transfer measurement data and simulate real processes
Monitoring with Digital Twin
Act in real-time!
Pictures: Industry 4.0 Collaboration Lab (KIT) © Jivka Ovtcharova I 44
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Information Management in Engineering at KIT
© Jivka Ovtcharova I 45
Jivka OvtcharovaInstitut für Informationsmanagement im Ingenieurwesen, Karlsruher Institut für
Technologie
The Future is now
First Choice Partner!