ESI symposium 2019

Intelligence, the next challenge in system complexity?

Date: April 9, 2019: 09h00-18h00
Venue: Auditorium TU/e Eindhoven University of Technology, Eindhoven NL route and address
Costs: free of charge
Registration: register

High-tech systems are integrating more and more intelligence, which increases engineering complexity. At the 2019 ESI Symposium we will discuss the challenges this presents and initial directions for managing, and coping with, the growing complexity.

We would like to invite you to join the symposium. The event features a varied program with interactive sessions inspired by contributions from industrial and academic speakers. Moreover, there will be plenty of networking opportunities on the innovation market. Please register now.

We look forward to seeing you.

Wouter Leibbrandt and Frans Beenker

ESI symposium 2019

link to movie


Programme

09h00 Registration open

09h30
Opening 
Wouter Leibbrandt and Frans Beenker, ESI
09h50 Keynote academy: Professor Edward E. Lee, UC Berkeley
10h45 Break at the innovation market
11h15 Parallel sessions S1 Digital Twinning S2 Learning systems S3 Architecting intelligent systems
Chair and introduction Hans Duetz, Philips
Gregor Pavlin, Thales TRT
Ronald Fabel, Océ Technologies
Lecture Jacques Verriet, ESI Michael Borth, ESI Wouter Tabingh Suermondt, ESI
Lecture Louis Stroucken, Philips Innovation Services John van den Dobbelsteen, TU Delft Mike Nicolai, Siemens Industry Software
Facilitator Teun Hendriks, ESI
Bas Huijbrechts, ESI Richard Doornbos, ESI
12h30 Lunch at the innovation market
13h30 Parallel sessions S4 Diagnostic reasoning S5 Acceptable AI S6 Future system engineers
Chair and introduction Hans Onvlee, ASML Robert-Jan de Pauw, Philips Arjen Klomp,Thermo Fisher Scientific
Lecture Jeroen Voeten, ESI Michael Siegel, Offis Ton Peijnenburg, VDL-ETG

Lecture

Ton van Velzen, IBM Marc Steen, TNO Nicole Hutchison, SERC
Facilitator Emile van Gerwen, ESI Michael Borth, ESI Joris van den Aker, ESI
14h45 Break, networking at the innovation market
15h15 Keynote industry: Dr. Henk van Houten, Royal Philips
16h15 Closure Wouter Leibbrandt and Frans Beenker, ESI
16h30 Drinks, networking, innovation market
18h00 End


Keynotes

Keynote speaker (academy): Edward A. Lee, Professor in Electrical Engineering and Computer Sciences, EECS Department, University of California, Berkeley
Title: Intelligence and Computation

Edward E Lee picture by Jessica Lifland

While compelling, the analogy that many people draw between human intelligence and software is problematic. Recent dramatic advances in machine learning seem to have strengthened the analogy, but this could be misleading. Are we fundamentally the same as computer programs, just running on different hardware? In this talk, I will examine a number of points where the analogy breaks down. First, human cognition may be firmly rooted in our embodiment, stemming from the interaction between the brain, the body, and the environment, rather than emerging from the brain processes alone. Moreover, some properties of cognition appear to not be representable digitally and may require fundamentally first-person interaction rather than Turing-Church computation.

Fundamentally, the digital and algorithmic nature of software is a limitation not shared by the hardware of human brains and bodies, and it is quite possible that digital technology will evolve more in complementary rather than competitive ways.

Keynote speaker (industry): Henk van Houten, CTO and Head of Research for Royal Philips
Title: Digitalization and AI in support of Value Based Care

Healthcare costs are exploding, medical staff are overburdened, and patients live longer with (multiple) chronic conditions. These are just a few of the many challenges healthcare systems across the globe are facing. Philips has adopted the quadruple aim as its yardstick for innovations which seek to alleviate these challenges. This approach ensures that we measure our innovation in termsHenk_van_houten of the impact on improving clinical outcomes, reducing cost, and enhancing the patient and staff experience.

Digitalization is a key enabler for solutions addressing the quadruple aim. Adoption of (hybrid) Cloud platforms and the Internet of Things is unlocking data at an unprecedented scale. Making sense of all this data calls for smart algorithms, and tailored deployment platforms embedded in the workflow of the healthcare professionals. Artificial Intelligence has the potential to play an important role in this. Philips positions AI as Adaptive Intelligence – technology that adapts to people in their daily context and augments their capabilities. Combining data-based adaptation with anatomical and biological science captured in models of organs, like the heart, is a powerful way to support precision diagnosis and image guided therapy. Such models can also be used to connect the dots across the health continuum, ultimately evolving into a digital twin of the patient. This we believe will be a powerful complement of electronic medical records, and a key ingredient in seamless delivery of collaborative care.

Parallel sessions

  1. Digital Twinning
    How can digital twinning drive design and engineering innovation?

    A digital twin is a virtual representation of a physical entity or system. A digital twin is much more than a picture, blueprint or schematic: It is a dynamic, simulated view of a physical product that is continuously updated throughout the design, build and operation lifecycle, and exists in parallel to its corresponding physical object. Digital twins can provide customer and equipment insights, improve quality and reliability, monitor performance, and mitigate downtime and increase availability. This session looks at the potential of digital twins to drive innovation, ways to introducing digital twinning as a way-of-working in the high tech industry, and its impact on an R&D organization.

    - Chair and introduction:Hans Duetz, Philips
    - Jacques Verriet, ESI (TNO)
    - Louis Stroucken, Philips Innovation Services (PINS)
    - ESI facilitator: Teun Hendriks

  2. Learning systems
    How to exploit system data for operational excellence?

    Emerging operational data, a direct consequence of systems increasingly being equipped with sensors and software, could help industry to deal with the key challenges in industry’s shift towards complex digitised, connected, intelligent solutions. How to make these systems resilient to change, capable to autonomously self-adapt their operations upon unforeseen conditions? Will augmenting systems with introspective and machine-learning capabilities be the next step in supporting evolvability? What is needed to make self-learning systems genuine artificial intelligent? These and many other questions are being discussed in this session, with a focus on pursuing operational excellence by means of self-learning behavior.

    - Chair and introduction: Gregor Pavlin, Thales TRT
    - Michael Borth, ESI (TNO)
    - John van den Dobbelsteen, TU Delft
    - ESI facilitator: Bas Huijbrechts

  3. Architecting intelligent systems
    Is a paradigm shift needed in architecting intelligent systems?

    The examples of artificial intelligent systems, such as self-driving cars, autonomous drones or autonomous weapons, are all well-known, hyped may be. From architecting perspective, does it make a difference to call them artificial intelligent and does that influence the way architects have to do their job? Is a paradigm shift needed to architect these systems? Can architects delegate their work to smart digital assistants? These and many other questions are being discussed in this session, with a focus on the impact of AI on systems architecting.

    - Chair and introduction: Ronald Fabel, Océ Technologies
    - Wouter Tabingh Suermondt, ESI (TNO)
    - Mike Nicolai, Siemens Industry Software
    - ESI facilitator: Richard Doornbos

  4. Diagnostic reasoning
    Model based reasoning to support diagnostics in complex systems

    As systems become increasingly complex, diagnosing system failures and performance issues becomes a true challenge for engineers. Too often, solving problems requires extensive involvement of multiple R&D experts. Diagnostic reasoning gives engineers the tools they need to make decisions about system behaviour and performance without having to know all the intrinsic system details. In addition to presenting a state-of-the-art overview and a look into the future, this session presents industrial cases in which data, modelling, and reasoning are brought together to solve diagnostic challenges.

    - Chair and introduction: Hans Onvlee, ASML
    - Jeroen Voeten, ESI (TNO)
    - Ton van Velzen, IBM
    - ESI facilitator: Emile van Gerwen

  5. Acceptable AI
    How to obtain trust in systems with AI components?

    Next to the technical complexity of integrating AI into high-tech systems, we have to address the complex task of making the resulting system acceptable by its end-users. This track discusses the possible routes and roadblocks of getting AI explained and accepted. The presentations are based on industrial use cases, including healthcare applications and automotive applications.

    - Chair and introduction: Robert-Jan de Pauw, Philips
    - Michael Siegel, Offis
    - Marc Steen, TNO
    - ESI facilitator: Michael Borth

  6. Future system engineers
    What does future systems engineering look like? Will the rise of intelligent systems threaten or augment SE practices?

    The introduction of AI techniques promises to automate many engineering activities, while at the same time it further increases the complexity of systems. This requires an increasing emphasis on SE competencies such as systems thinking, holistic lifecycle view, etc. How does this impact systems engineering organizations, and SE competency models? How can industry prepare, and what are universities doing in this area?

    - Chair and introduction: Arjen Klomp,Thermo Fisher Scientific
    - Ton Peijnenburg, VDL-ETG
    - Nicole Hutchison, SERC
    - ESI facilitator: Joris van den Aker


Innovation market

  • Altran
  • Artemis
  • ASML / ESI
  • Delft University of Technology
  • Eindhoven University of Technology High Tech Systems Center
  • ESI - diagnostics
  • ESI - digital twin / ENABLE S3
  • ESI - competence development
  • Fraunhofer IESE
  • High Tech NL
  • Itea
  • Lely
  • Obeo
  • One of a Kind Technologies
  • Radboud University
  • SERC
  • Siemens ISW
  • Twente University
  • Unit 040

High Tech NLESI

See: previous ESI symposia