COALA AMBASSADOR PODCAST SERIES
December, 5 2022
In this occasion COALA meets FACTLOG
Guest of this Episode is Paolo Perillo, Products Director at Holonix, as moderator.
Artificial Intelligence and Manufacturing
The COALA Ambassador Podcast series is an initiative aimed at sharing our COALA EU project progress and findings with AI and Manufacturing Communities who want to know more more about Digital Voice Assistants for the industry and its developments in the fields of Artificial Intelligence and Manufacturing
COALA – COgnitive Assisted agile manufacturing for a LAbor force supported by trustworthy Artificial Intelligence – is an EU Horizon 2020 funded project, which aims to develop a trustworthy voice-enabled Digital Intelligent Assistant for the manufacturing industry.
COALA will provide a solution for cognitive assistance that consists of a composition of trustworthy AI components with a voice-enabled digital intelligent assistant as an interface. The solution will support workers that need to use analytics tools and new workers that perform on-the-job training. Complementary to the technology, an education and training concept that focuses on building blue-collar worker competencies in human-AI collaboration will be developed. The COALA solution will transform how workers perform their jobs and it allows companies to maintain or increase the quality of their production processes and their products.
COALA collaborates in the AI-MAN Cluster with other eight projects that are funded under the EU H2020 ICT-38 call – Artificial intelligence for manufacturing, aiming to develop trustworthy human-centred AI in manufacturing.
It becomes apparent particularly in process industries that cognition can improve the behaviour of a complex process system. The capability to observe and monitor the behaviour is crucial, it’s necessary to combine digital twins which are driven by domain models, with the models derived from data. In order to realize it, we need a real-time processing layer. FACTLOG offers such a layer and aims at deploying and adjusting it to several process industries