Data-Driven Collaborative Intelligence in SM and Robotics (Workshop 2.2)

SESSION OBJECTIVES

Autonomous Factory is one of the three 2025 scenarios identified by the 2017-2018 Discussion Paper “Big Data challenges in Smart Manufacturing” recently issued by the BDVA subgroup “Smart Manufacturing Industry” and validated by the Factories of the Future Connected Factories project . In such a scenario, IoT connected machinery, [mobile] robots and internal logistics equipment (so called Cyber Physical Production Systems CPPS in Industry 4.0) are able to take critical decisions in real time and autonomy, thanks to advanced AI-based embedded technologies. However, as indicated by the above mentioned paper, in an Autonomous Factory scenario, Industrial IoT, Robotics, Logistics and Artificial Intelligence technologies are fed and coordinated by data-driven architectures responding to the five main technological challenges of the BDVA Strategic Research and Innovation Agenda: namely i) Data lifecycle Management, ii) Data Security and Protection, iii) Data Processing architectures and tools, iv) Data Analytics and Forecasting, v) Data Visualisation and Interaction. Data is absolutely the oil for this 2025 scenario as well, enabling intelligent behaviours by CPPS which could amplify, extend and embody human capabilities. But, what is the role of Humans in such an intelligent, cognitive and autonomous scenario? Shall humans disappear from the Autonomous Factory or shall they just radically change their roles, jobs and competencies?

The objective of this session is to discuss and delineate new forms of Human-Machine collaboration, such as for instance VR/AR environments, collaborative robots, wearable devices and to identify where new professions and skills are needed by humans in order to train, explain and sustain manufacturing autonomous decisions and behaviours. We call this human-driven viewpoint of the Autonomous Factory scenario “Data-driven Collaborative Intelligence”.

AGENDA

• Organisers-Moderators:
  • Davide Dalle Carbonare & Sergio Gusmeroli ENGINEERING Ingegneria Informatica
• Experts:
  • Big Data: Óscar Lázaro (INNOVALIA) coordinator of the BDVA BOOST 4.0 Lighthouse project for Smart Manufacturing Industry
  • Robotics: Reinhard Lafrenz (TUM) secretary general of euROBOTICS Association
  • Discrete Manufacturing: Chris Decubber (EFFRA) technical director of European Factories of the Future Research Association
  • Process Industry: Ingo Gräf (SPIRE)
  • Artificial Intelligence: Philippe Mouttou (THALESgroup) coordinator of AI4EU Innovation Action
  • Industrial IoT: Thomas Walloschke (FUJITSU) leader of AIOTI (Alliance for the Internet of Things Innovation) WG11 Smart Manufacturing and Chair of the AIOTI Steering Board.

EXPECTED OUTCOMES

The expected outcomes of the session is a consensus report to be attached to the 2018-2019 issue of the “Big Data challenges in Smart Manufacturing” discussion paper, which will firstly analyse the role of Robotics and AI technologies in the implementation of the 2025 Autonomous Factory, and afterwards will depict required hard and soft skills for 2025 humans (and blue collar workers in particular) to implement the “Data-driven Collaborative Intelligence” scenario.

TARGET AUDIENCE

The session is specifically addressing practitioners in the domain of “Big Data for Manufacturing Industry”, but it is closely related to EFFRA Factories of the Future, Industrial IoT, Artificial Intelligence and Robotics industrial and research experts. Dissemination of the event will be implemented inside the Factories of the Future H2020 cPPP, the EU Robotics association, the AIOTI movement and the AI communities, in order to have a multi-disciplinary and multi-domain discussion audience. It is expected an audience between 30-50 participants, which could animate working groups and find consensus on a predefined set of key questions.