CIS Digital Twin Days

November 15-16, 2021 at SwissTech Convention Center (STCC) in Lausanne | Hybride
Two heads digital

Digital Twin technologies are gaining momentum in research and applications in health and industry on an international scale. EPFL and its partners are active in the development of related core technologies and their integrations, for instance via the CIS Research Pillars and DIGIPREDICT.

With the EPFL CIS Digital Twin Days 2021, the EPFL Center for Intelligent Systems and its partners will further increase the awareness for Digital Twin technologies, to showcase their applications for society and industry and to foster the dialogue between researchers, industry representatives and stakeholders from politics and the general public.

When 
15-16 November 2021
Doors open 9am – Event starts 9:30am 
Event ends: 5.30pm 

What 
This unique two-day event provides the opportunity to meet and discuss with the EPFL CIS Digital Twin community and renowned international experts.
15 November will be focussing on research done within the universities of EPFL, ETH Zürich, Politecnico di Milano and University of Texas (Austin).
16 November will feature expert presentations from industries featuring presentations by Siemens, Georg Fischer (+GF+), and Akselos.
The entire event will provide ample time for networking, technology showcases through selected posters and will be concluded with a roundtable discussion on day two.

Where 
SwissTech Convention Center in Lausanne, Switzerland
Option to follow online for people who can not attend in person. 

Speakers 

Full program

09:00 – 09:30
Door opening & Welcome
09:30 – 10:30
Prof. Eleni Chatzi,
Chair of Structural Mechanics & Monitoring, ETH Zürich
On the Synergy of data and models for Virtualizing Structures & Infrastructure

Abstract
The monitoring of the condition of engineered systems operating under diverse dynamic loads involves the tasks of simulation (forward engineering), identification (inverse engineering) and maintenance/control actions. The efficient and successful implementation of these tasks is however non-trivial, due to the ever-changing nature of these systems, the variability in their interactive environments, and the polymorphic uncertainties involved. Structural Health Monitoring (SHM) attempts to tackle these challenges by exploiting information stemming from sensor networks in order to deliver a digital representation of the system as-is. SHM comprises a hierarchy across levels of increasing complexity aiming to i) detect damage, ii) localize and iii) quantify damage, and iv) finally offer a prognosis over the system’s residual life. When considering higher levels in this hierarchy, including damage assessment and even performance prognosis, purely data-driven methods are found to be lacking. For higher-level SHM tasks, or for furnishing a virtualization of a monitored system, it is necessary to integrate the knowledge stemming from physics-based representations, relying on the underlying mechanics and dynamics principles. This talk discusses implementation of such a hybrid approach to SHM for tackling the aforementioned challenges with examples across diverse systems including civil structures and transport infrastructure, as well as wind turbine facilities.
10:30 – 11:00
Networking & Poster session
11:00 – 12:00
Prof. Alfio Quarteroni
Professor of Numerical Analysis, Politecnico di Milano and Emeritus Professor, EPFL
Physics-Based and Data-Driven-Based Algorithms for the Simulation of the Heart Function

Abstract
In this talk I will present a mathematical model that is suitable to simulate the cardiac function, thanks to its capability to describe the interaction between electrical, mechanical, and fluid-dynamical processes occurring in the heart. The model comprises a system of nonlinear differential equations (either ordinary and partial) featuring a multi-physics and multi-scale nature. Efficient numerical strategies are devised to allow for the analysis of both heart function and dysfunction.These strategies rely on both classical physics-based numerical discretization methods and machine-learning algorithms, as well as on their interplay.

Acknowledgment: The work presented in this talk is part of the project iHEART that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 740132)
12:00 – 13:30
Lunch on campus
13:30 – 14:30
Prof. Adrian Ionescu, Full Professor and Head of the Nanoelectronic Devices Laboratory (NANOLAB), EPFL
Edge-To-Cloud Digital Twins Aiming At Future Personalized, Preventive and Participatory (P3) Healthcare

Abstract
In this talk we will discuss the challenges and opportunities of building Edge-to-Cloud Digital Twins for P3 healthcare applications. Such Digital Twins will enable an evolution in human model development by leveraging data from omics analyses, medical and imaging data, environmental and life style big data that are continuously updated by a multitude of biosensors at an unprecedented scale. With such complex data sets, first of their kind human avatars will be built that can be personalised and used to prevent and cure each one’s own diseases. We will particularly detail and discuss sensor technology platform needs and evolutions in Edge AI, including wearables, implantables and organs on chips.
14:30 – 15:00
Networking & Poster session
15:00 – 16:00
Prof. Karen E. Willcox
Director, Oden Institute for Computational Engineering and Sciences, University of Texas, Austin
Predictive Digital Twins: From physics-based modeling to scientific machine learning

Abstract
A digital twin is an evolving virtual model that mirrors an individual physical asset throughout its lifecycle. Key to the digital twin concept is the ability to sense, collect, analyze, and learn from the asset’s data. To make digital twins a reality, many elements of the interdisciplinary field of computational science, including physics-based modeling and simulation, inverse problems, uncertainty quantification, and scientific machine learning, have an important role to play.

In this work, we develop a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset-twin system as a set of coupled dynamical systems, evolving over time through their respective state-spaces and interacting via observed data and control inputs. The abstraction is realized computationally as a dynamic decision network. Predictive capabilities are enabled by physics-based reduced-order models. We demonstrate how the approach is instantiated to create, update and deploy a structural digital twin of an unmanned aerial vehicle.
16:00 – 17:15
Apéro & Poster session
09:00 – 09:30
Door opening & Welcome
09:30 – 10:30
Dr. Gunter Beitinger, SVP Manufacturing and Head of Factory Digitalization, SIEMENS AG
Lean Digital Factory- A Closed Loop Manufacturing Approach

Abstract
Our DI factories have to serve as role models for excellence in production and logistics to provide proven value add for our customers and our operational company, based on lean engineering, smart Factory Automation and Digital Enterprise Solutions. To stay ahead of our competition, we launched 2016 the Lean Digital Factory approach, a structured and bottom up approach for our factories to met future challenges and to take advantage of new possibilities dueto digitalization. Since then, The Lean Digital Factory Approach has served several Siemens plants to receive multiple awards. In this presentation, I would like to share our experience and demonstrate “How to bring Closed Loop Manufacturing into your organization based on our own experiences”
10:30 – 11:00
Networking & Poster session
11:00 – 12:00
Dr. Roberto Perez
Head of Innovation Network Technology Office – Operations Digital Business Unit, GF Machining Solutions
A Digital factory twin for continuous improvement in Milling Spindle manufacturing processes

Abstract
Based on the analysis of key performance barriers of GF spindle factory and a digitalization campaign for system component manufacturing and tests, a digital twin has been implemented in order to improve the manufacturing process productivity and the quality of final products.

The solution provides a new framework, defined within the EU project Boost 4.0, involving a dedicated product and process ontology and data warehouse, a digital thread from spindle manufacturing to milling machine assembly as well as real time monitoring and analytics capabilities for predictive quality on the GF cloud environment, enabling full traceability and transparency of the process and new solutions for identifying and anticipating defects across the production chain down to customer shopfloor, and providing a base for a robust predictive maintenance application implementation.
12:00 – 13:30
Lunch on campus
13:30 – 14:30
Thomas Leurent
CEO, Akselos
How digital twins can help us reach the Net Zero 2050 goal

Abstract
This year, the International Energy Agency released an ambitious roadmap for the energy industry to reach the Net Zero 2050 goal. Between life extension of existing O&G assets (as opposed to building new ones) and deploying gigantic offshore wind farms, the energy industry must rewrite its technology playbook. Akselos has built a technology stack, based on EPFL & MIT R&D, that helps the industry protect its most critical assets and design and operate the lean renewable assets of the future. Hear why green and digital together can help crack the energy transition.
14:30 – 15:00
Networking & Poster session
15:00 – 16:00
Panel discussion
With Dr. Gunter Beitinger, Prof. Adrian Ionescu, Thomas Leurent, Dr. Roberto Perez and Prof. Karen E. Willcox
Moderated by Dr. Jan Kerschgens and Prof. Fabio Nobile
16:00 – 17:15
Apéro & Poster session

Aftermovie

Replay and PowerPoint Presentations 

Prof. Eleni Chatzi, Chair of Structural Mechanics & Monitoring, ETH Zürich
On the Synergy of data and models for Virtualizing Structures & Infrastructure
Replay
PDF Presentation

Prof. Alfio Quarteroni, Professor of Numerical Analysis, Politecnico di Milano and Emeritus Professor, EPFL
Physics-Based and Data-Driven-Based Algorithms for the Simulation of the Heart Function
Replay
PDF Presentation

Prof. Adrian Ionescu, Full Professor and Head of the Nanoelectronic Devices Laboratory (NANOLAB), EPFL
Edge-To-Cloud Digital Twins Aiming At Future Personalized, Preventive and Participatory (P3) Healthcare
Replay
PDF Presentation

Prof. Karen E. Willcox,Director, Oden Institute for Computational Engineering and Sciences, University of Texas, Austin
Predictive Digital Twins: From physics-based modeling to scientific machine learning
Replay
PDF Presentation

Dr. Gunter Beitinger, SVP Manufacturing and Head of Factory Digitalization, SIEMENS AG
Lean Digital Factory- A Closed Loop Manufacturing Approach
Replay
PDF Presentation

Dr. Roberto Perez,Head of Innovation Network Technology Office – Operations Digital Business Unit, GF Machining Solutions
A Digital factory twin for continuous improvement in Milling Spindle manufacturing processes
Replay
PDF Presentation

Thomas Leurent, CEO, Akselos
How digital twins can help us reach the Net Zero 2050 goal
Replay
PDF Presentation

Panel discussion
With Dr. Gunter Beitinger, Prof. Adrian Ionescu, Thomas Leurent, Dr. Roberto Perez and Prof. Karen E. Willcox
Moderated by Dr. Jan Kerschgens and Prof. Fabio Nobile
Replay

Contact

If you have any questions or request please contact : [email protected]