Industry Forum on Industrial Applications of Artificial Intelligence

IEEE INDIN 2019 will be hosting an industry forum with a focus on Industrial Applications of Artificial Intelligence (AI). The forum will be composed of 3 sessions, details of which can be found below

Authors intending to present a talk at the industry forum sessions are requested to send a abstract of the talk to the respective session chairs, the contacts of which can be found in the respective session details below.

Session 1 - Artificial Intelligence in manufacturing and supply chain

Chaired by: Lasse Eriksson, Kalmar Global, Finland;

This Industry Forum session addresses the key opportunities and challenges related to applying artificial intelligence in manufacturing and supply chain. The session will provide the participants with a state-of-the-art view to how industry is applying artificial intelligence to create new business models, improve manufacturing performance and enhance supply chain predictability, transparency and efficiency.

In this session, the speakers are encouraged to submit presentations tackling with AI within manufacturing and supply chain.

Topics under this session include (but not limited to):

  • Industrial applications and real-world examples of AI
  • Industrial research and development results related to AI
  • Data ownership, privacy and ethics within industrial application of AI
  • AI-enabled business models and earning logics
  • Humanized artificial intelligence: AI-human interaction
  • How AI empowers humans (e.g. factory workers, planners, support organizations)
  • AI based performance optimization
  • AI driven services
  • AI as an engine for maintenance process optimization and predictive and condition based maintenance

Submit your talk proposal

If you are interested in presenting a talk at this session, please send a abstract of your talk to session chair Lasse Eriksson ( lasse.eriksson@kalmarglobal.com) .

Session 2 - Artificial Intelligence for autonomous systems

Chaired by: Zhibo Pang, ABB Corporate Research, Sweden, and Royal Institute of Technology (KTH), Sweden;

As an emerging trend, industrial systems are transforming from automated to autonomous. The systems that, without manual intervention, can change their behavior in response to unanticipated events during operation are called “autonomous”. In the recent years, we have seen many explorations in both academia and industries on such systems, ranging from driverless cars, unmanned aviation vehicles (UAV), automated guided vehicles (AGV), autonomous robots, autonomous ships, unmanned mining equipment, unmanned warehouses and distribution centers, unmanned groceries and shops, unmanned hotels and restaurants, and even autonomous power grids. Compared with traditional automatic control, the AI or machine learning techniques will play essential roles in such systems to enable the autonomous execution of complex tasks in more dynamic and unstructured environments with unpredictable changes.

In this session, the invited speakers will address state-of-the-art, research challenges, and business cases of the autonomous industrial systems.

Topics under this session include (but not limited to):

  • Applications and business cases in transportation, logistics, healthcare, mining, energy, and manufacturing
  • New learning frameworks and AI models for industrial specific solutions
  • Communications infrastructure e.g. OPC UA TSN, 5G
  • Computing architecture e.g. local accelerator, edge/fog/cloud offloading
  • Key building blocks e.g. machine vision, sensors fusion and perception, SLAM
  • Cross-disciplinary design for determinism, latency, debuggability, traceability, and safety

Submit your talk proposal

If you are interested in presenting a talk at this session, please send a abstract of your talk to session chair Zhibo Pang ( pang.zhibo@se.abb.com) .

Session 3 - Artificial Intelligence and Informatics Systems

Chaired by: Michael Condry, IEEE, USA;

In industrial electronics systems activity happens at the edge with sensors, camera, etc. that detect information and with actuators, control, and other services that act. Many activities are well understood, and detect and act can be managed at the edge. However, many of these activities require advanced AI systems, rule based or neural networks typically in the cloud , that need history and current information to make complex decisions such as “replace this factory element”, “reroute the transport vehicle”, or “check with the doctor.” The informatics here require much more computing power and storage than typically is available at the edge system. There are many challenges such as sending the “right” amount of information to the cloud to make proper decisions without overloading the network or the cloud; also, doing so in a timely manner that the control decision can be made in suitable time. Design here depends on the application, and these kinds of systems are found in many applications including factory control and automation, transportation, medicine and agriculture, just to name a few. This Industry Forum session looks at the challenges and solutions to this problem space found in application systems today and in the near future.

In this session, the speakers are encouraged to submit presentations tackling with AI within Industrial Informatics.

Topics under this session include (but not limited to):

  • Industrial applications and real-world examples of AI
  • Solutions to optimize computation between the edge and cloud for selected applications, considering the computation power of the edge, communication speed and real-time requirements of the applications
  • Use of AI as an engine for maintenance process optimization and predictive and condition based maintenance
  • Any suitable industrial applications with particular focus on:
    • Control
    • Manufacturing
    • Transportation
  • Security and Reliability matters with cloud computing that result in decision making

Submit your talk proposal

If you are interested in presenting a talk at this session, please send a abstract of your talk to session chair Michael Condry ( condry@ieee.org) .