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Day One

08.15 – 09.00

REGISTRATION

09.00 – 09.10

WELCOME & CHAIRPERSON’S OPENING REMARKS FOR DAY ONE

Marc De Samber, Research Fellow and Senior Director, Signify (formerly known as Philips Lighting)

09.10 – 09.45

Digital Transformation and Digital Factories at Signify

  • Digital transformation of the lighting industry
  • Digital Factories and factories of the future
  • Automation in quality control, for End-of-Line and for process execution
  • Future of work, Operator guidance
  • Computer Vision, Machine Learning, image classification, for Product assembly processes

Marc De Samber, Research Fellow and Senior Director, Signify (formerly known as Philips Lighting)

09.45 – 10.20

Fashioning the future: Machine learning, Artificial intelligence in retail – supply chain

  • Artificial intelligence – Machine learning in an Enterprise
  • case study
  • Enabling ML in use cases with Data governance
  • Blockchain: to use or not to use? Hype vs. reality
  • An infrastructure to Data science through 2030

Kshitij Kumar, Chief Data Officer, Farfetch

10.20 – 11.10

COFFEE BREAK & MEETINGS

11.10 – 11.45

Data-driven transformation manufacturing & supply chain through artificial intelligence

  • Description of Digital Operations Ecosystem & End-to-end Supply Chain
  • Role of Data & Analytics for data-driven transformation of Supply Chain & Manufacturing
  • AI areas with significant impact on Digital Operations
  • Deep-dive real world examples of Operations Excellence through leveraging AI

Martin Whyte, Director, Digital Operations Analytics, PwC

11.50 – 12.50
One to One Meetings

  • Industry 4.0
  • Machine Learning
  • Deep Learning
  • Collaborative Robots (Cobots)
  • Autonomous Automation
  • Robotic Process Automation (RPA)
  • Smart Sensors
  • Data Analytics
  • Algorithms (Smart/Flexible)
  • Blockchain
  • Industrial connectivity
  • Supply Chain Software
  • S&OP / Integrated Business Planning
  • Inventory Planning / Demand Planning
  • Transport Management
  • Procure2Pay / eCommerce
  • Supply Chain Finance / Risk Management
  • Workforce Development and Leadership
  • Regional Distribution Hubs / Localised Networks
  • Supplier Relationship Management
  • Cyber Security / Third Party Risk Assessment

11.50 – 12.20
Operations steering in a digital world

  • Present and describe state of the art principles to manage and steer operations globally – with Digital and AI features and opportunities
  • What’s possible, what’s next with AI, especially for industrial companies – the art of the impossible
  • Advantages and possible effects for companies and clients in B2B Segment – opportunity from complexity
  • Outlook 2025 – how AI will be an essential part of operations
  • Exchange, discuss the most relevant key factors for future success (in plenum)

12.20 – 12.50
New practical AI automation solutions for industrial & enterprise processes and machines

  • How to automate more and tackle real-world challenges
  • What is System 2 AI, model-based reinforcement learning, Neural MPC
  • New practical applications and cases in real-world systems and processes, such as industrial and enterprise process automation, sales and operations planning
  • Possibilities and impact

12.50 – 13.40

NETWORKING LUNCH

Data Analytics

13.40 – 14.15
Powering Knowledge-Based systems with I4.0 semantics standards

  • The sad reality of corporate, engineering and field-level data
  • Knowledge-Based AI reborn: WebOntology, GraphDBs
  • Ingesting AutomationML, eCl@ss and OPC-UA
  • Applications in Manufacturing

Paulo Zanini, Head of IoT and Digitalization – Systems Architect, Weiss GmbH

Intelligent Automation & RPA

13.40 – 14.15
Driving digital transformation – Intelligent automation to the next level in Novo Nordisk manufacturing and supply chain

  • Considerations for a global roll out and scaling of intelligent automation using a combination of RPA, OCR and BPM technologies
  • Key challenges and considerations for an effective operations model for intelligent automation

Carsten Lutzhoft, Director of Process Digitalisation, Novo Nordisk

14.20 – 14.55
Predictive Analytics using AI

  • Identifying the real problem
  • Getting the right data for predictive maintenance
  • Knowing when to use AI
  • Operationalization is the key

Patrick Volkmann, Group Lead, Verticals & Analytics driven Portfolio, Siemens AG

14.20 – 14.55
Quality 4.0 – Redesigning Quality Management

  • How to start the digitalization journey?
  • Our digitalization journey – what prerequisites are important?
  • Insights on my digitalization road map and implementation strategy
  • What is RPA? Examples of Quality processes we programmed in RPA
  • Lessons Learned

Christophe Dohr, Site Quality Head, Acino

15.00 – 15.35
The challenges of computer vision in industry

  • Why Computer Vision?
  • The challenges we face today
  • Leveraging existing knowledge from open-source tools
  • What are the key lessons learned from our journey?

Victor Caldas, Sr. Data Scientist, Cargill

15.00 – 15.35
Deep Learning in Mobile and Industrial Robots

  • An overview of several state-of-the art deep learning applications to mobile and industrial robots
  • Learning powerful deep models is easy, but needs significant expertise for successful handling and deployment
  • An overview of common issues and solutions (importance of datasets, metrics, generalization, dataset engineering)

Alessandro Giusti, Senior Researcher, Dalle Molle Institute for Artificial Intelligence (IDSIA)

15.35 – 16.25

COFFEE BREAK & MEETINGS

16.25 – 17.25
One to One Meetings

  • Industry 4.0
  • Machine Learning
  • Deep Learning
  • Collaborative Robots (Cobots)
  • Autonomous Automation
  • Robotic Process Automation (RPA)
  • Smart Sensors
  • Data Analytics
  • Algorithms (Smart/Flexible)
  • Blockchain
  • Industrial connectivity
  • Supply Chain Software
  • S&OP / Integrated Business Planning
  • Inventory Planning / Demand Planning
  • Transport Management
  • Procure2Pay / eCommerce
  • Supply Chain Finance / Risk Management
  • Workforce Development and Leadership
  • Regional Distribution Hubs / Localised Networks
  • Supplier Relationship Management
  • Cyber Security / Third Party Risk Assessment

16.25 – 16.55
AI and Data Fusion in three implementations

  • What’s the added value of AI in forecasting and decision support system
  • How data fusion makes AI smarter
  • Use cases:
    • Short term forecasting and monitoring for fashion retail business intelligence
    • Supply chain management
    • Health, Safety and Environment Risk Management

16.55 – 17.25
Intelligent process optimization as Industry 4.0 evolves

  • AI in Industry is evolving from predictive maintenance to process optimization
  • Challenges as AI moves to core operations
  • The case for intelligent process optimization
  • Experience from implementations

17.30 – 18.10

Open Panel Discussion

RPA & AI Vision: A real game-changer. Examples of deployment and lessons learnt

Intelligent RPA using Artificial Intelligence can be seen as the next game changer for many industries, but what is intelligent automation and to which processes is it most applicable for?

This open panel discussion will look at:

  • What can Robots do now and how will AI impact RPA in future?
  • The AI Strategy and readiness
  • Possibilities and limitations of current – AI enabled RPA compared to traditional automation
  • Examples of AI & RPA programs – lessons learnt from experience

Chair:
Marc De Samber
, Research Fellow and Senior Director, Signify

Panellists:
Carsten Lutzhoft
, Director of Process Digitalisation, Novo Nordisk
Christophe Dohr, Site Quality Head, Acino
Alessandro Giusti, Senior Researcher, Dalle Molle Institute for Artificial Intelligence (IDSIA)

18.10

CHAIRPERSON’S CLOSING REMARKS AND END OF DAY ONE

18.15

NETWORKING DRINKS

Day Two

09.00 – 09.10

CHAIRPERSON’S OPENING REMARKS FOR DAY TWO AND SUMMARY OF DAY ONE

09.10 – 09.45

How can we empower our Manufacturing Workforce for the Digital Era

  • Defining Industry 4.0 for ourselves. Is it the same for everyone?
  • How will Smart manufacturing change the future requirements of work qualifications and skills?
  • Digital transformation journey – Where do you start and how?
  • Manufacturing workforce – enabling the workforce for the digital era
  • How can we measure the success of a digital workplace transformation?

Richard Allbert, Head of Digital Innovation, Pirelli

09.45 – 10.20

We don’t need Deep Learning in Manufacturing

  • High level discussion of data analytics techniques in manufacturing
  • Where are the reasons to use deep neural networks?
  • What are promising areas of applications? – And what not!
  • What techniques are successful in Manufacturing – How should gaps be filled?
  • Possible future applications

Dr. Rolf Roth, Head of Data Science Performance Materials and Group Functions, Digital Organization, Merck KGaA

10.20 – 10.55

Collaborative AI in Mobility – Handling Complexity in the Interplay of Humans and Machines

  • What is Industrial AI?
  • What are major challenges in current train-based mobility?
  • How can AI help us in solving these challenges?
  • What are future implications for holistic mobility processes?
  • What are best practices for organizational setups to realize Industrial AI systems?

Thomas Thiele, Program Manager House of AI, Deutsche Bahn AG

10.55 – 11.25

COFFEE BREAK & MEETINGS

11.25 – 12.15

Roundtable Discussions:

For 4 to 8 participants to discuss and debate on one of the selected topics:

  1. Smart Manufacturing
  2. Digital Supply Chain
  3. Digital Transformation
  4. Machine Learning Platforms
  5. Robotic Process Automation
  6. Predictive Maintenance
  7. Workforce Developement

12.15 – 13.05

NETWORKING LUNCH

13.05 – 13.40

Data Analytics for a smart factory – real use cases

  • IT infrastructure for data analytics
  • Quality improvement by data analytics
  • Machine utilization – Digital Value Stream Analysis
  • Predictive Maintenance
  • Supplier Collaboration supported by tool management

Dr. Jochen Boenig, Head of Strategic Digitalization, Siemens AG

13.40 – 14.15

Knowledge Graphs in Conversational AI Platforms

  • Machine Learning backs conversational AI with advanced natural language understading
  • The Mushroom Effect
  • Knowledge Graphs to bring domain expertise and explainability
  • The SPEAKER Platform

Mikhail Galkin, Senior Research Scientist, Fraunhofer IAIS

14.15 – 14.50

An age-old textbook model can make your business cost efficient
While artificial intelligence is important to move ahead, the first step towards it is the willingness to accept a data driven approach. If you know your business, and are willing to change things, even a simple 100 year old formula can make a big difference in your business

  • What is this age-old textbook method?
  • Why is it not already being applied in the industry?
  • What does it take to make it a reality?
  • Some examples from a real world application

Stuti Argawal, Data Scientist, Merck KGaA

14.50 – 15.10

COFFEE BREAK

15.10 – 15.45

Open Panel Discussion
The case for Artificial Intelligence – How can we build a strong business case from buy-in and deployment to building a corporate culture around data?

AI can be a daunting prospect for many C-level decision makers. And yet according to 313 executives recently surveyed by Forbes Insights—63% of whom were in the C-Suite—almost all (95%) believe that AI will play an important role in their responsibilities in the near-future.

This open panel discussion will look at:

  • How to build the business around achievable goals that consider the positive impact on human work
  • Where to start? Start small or start big? Picking the right problem
  • The human touch – How to build a data driven culture with a shared vision to keep AI moving ahead
  • Scaling up – Defining the AI Infrastructure through new cloud based technologies
  • Closing the skill gap though workforce development

15.45

CHAIPERSON’S CLOSING REMARKS

15.50

CLOSE