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Human-AI Teaming Platform for Maintaining and Evolving AI Systems in M...

TEAMING.AI - Human-AI Teaming Platform for Maintaining and Evolving AI Systems in Manufacturing

Smart Manufacturing is believed to play a critical role in maintaining the competitiveness of organisations, by supporting them at different levels such as process optimisation, resource efficiency, predictive maintenance and quality control. Nevertheless, AI technologies which are currently and rapidly penetrating industrial sectors at those levels remain essentially narrow AI systems. This is due to the lack of self-adaptiveness in the AIs capability to assimilate and interpret new information outside of its predefined programmed parameters. This mean that AI systems are tailored for solving specific tasks on a specific predefined setting and changes in the underlying setting usually requires system adaption ranging from fine-grained parameter adaptations to fully-fledged re-design and re-development of AI systems.

TEAMING_AI project aims at a human AI teaming framework that integrates the strengths of both, the flexibility of human intelligence and scale-up capability of machine intelligence. Human AI teaming is equally motivated to meet the increased need for flexibility in the maintenance and further evolution of AI systems, driven by the increasing personalization of products and service, as well as tackling the barriers of user acceptance and ethical challenges involved in the collaborative environments where artificial intelligence will be used, in order AI can be considered as 'teammate' rather than as a threat.

The TEAMING.AI project will be run over 36 months with a work plan divided into 9 Work Packages. Work Packages from 1 to 5 are devoted to the development of new technology to enhance the interaction between human and machine. Furthermore, Work Packages 6 and 7 wrap the development of 3 use case scenarios. Finally, two final Work Packages (8 and 9) will work respectively on the dissemination, exploitation of results and coordination of the project in a transversally way to the above mentioned WPs.

Resources

Demonstrators, pilots, prototypes
Industrial pilot or use case
Use Case 1: Transfer learning based robust quality inspection (for plastic injection sector) (FARPLAS)
Use Case 2: Machine diagnostics for plastic injection sector to improve quality and reduce waste (IAL)
Use Case 3: Ergonomics and risk prevention in large part manufacturing (GOIMEK)
Key documentation on demonstrators, pilots, prototypes
Recording of the TEAMING. AI FINAL CONFERENCE
Exploitable result(s)
Key exploitable technology-approach
Exploitable Result 1: Advanced Method for Building and Curating Industrial Updatable Graphs (WUW)
Exploitable Result 2: Advanced Machine Learning Algorithms for Defect Prediction (ITU)
Exploitable Result 3: Dynamic Knowledge Graph Engine
Exploitable Result 4: Process Knowledge Graph Extractor
Exploitable Result 5: TEAMING.AI engine software platform
Exploitable Result 6: Software solution for machine parameter optimisation based on root cause analysis
Exploitable Result 7: Software solution for machine data extraction
Exploitable Result 8:Software solution for ergonomic risk assessment using vision-based posture analysis
Key documentation on exploitable results
Recording of the TEAMING. AI FINAL CONFERENCE

Call Topic

ICT-38-2020