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Energy-aware Factory Analytics for Process Industries

Project description

DEENESFRITPL

A twin take on factory analytics

Digital twins are a virtual simulation of real-world objects. One of the main expectations of the use of digital twins is to provide the capability to observe and monitor the behaviour of their respective physical twins. The EU-funded FACTLOG project will develop a real-time processing layer where observations, knowledge and experience interoperate to understand the control behaviour of a complex system (cognition). It will enable the realisation of the cognitive factory as an ensemble of independent but intertwined European Credit Transfer (ETC) systems that can self-learn and detect and react to anomalies and disruptions. The 20-member consortium will bring related knowledge and innovation, organising different pipelines of machine learning and analytical tools.

Objective

It becomes apparent particularly in process industries that cognition can improve the behaviour of a complex process system. One of the main expectations of the use of digital twins is to give us the capability to observe and monitor the behaviour of their respective physical twins. In order to make it happen, we need to combine digital twins, which are driven by domain models (i.e. knowledge), with the models derived from data (i.e. experience). In order to realize it, we need a real-time processing layer where observations (i.e. events), knowledge and experience interoperate to understand and control the behaviour of a complex system (i.e. cognition). FACTLOG offers such a layer and aims at deploying and adjusting it to several process industries.
By incorporating different pipelines of machine learning and analytical tools at different levels (from machines to process steps and from processes to the whole production plant), FACTLOG enables the realization of the Cognitive Factory as an ensemble of independent but intertwined ECTs, that are (i) able to self-learn, and thus to effectively detect and react to anomalies and disruptions but also to opportunities that may arise, (ii) enjoy a local or global view of operations and (iii) are capable for short-, mid- and long-term reasoning and optimization.
FACTLOG is driven by several specific, yet indicative, business cases in the process industry and focuses its innovation regarding analytics, AI and optimization on the deployment and assessment of coherent Enhanced Cognitive Twins for the specific sectors represented in FACTLOG and even for the plants in which it will be pilot tested and evaluated.
It will be implemented by a just right consortium of twenty partners, five of which are manufacturers and a further three represent manufacturing clusters. Technology and scientific contributors from leading academic institute and focused ICT vendors (mostly SMEs) bring in all necessary knowledge and innovation.

Fields of science

Programme(s)

Topic(s)

Call for proposal

H2020-NMBP-ST-IND-2018-2020

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Sub call

H2020-NMBP-SPIRE-2019

Funding Scheme

IA - Innovation action

Coordinator

MAGGIOLI SPA
Net EU contribution
€ 977 812,50
Address
Via del carpino 8
47822 Santarcangelo di romagna
Italy

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Region
Nord-Est Emilia-Romagna Rimini
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Other funding
€ 419 062,50

Participants (20)

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EC signature date 14 November 2019
Last update: 22 January 2023

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Permalink: https://cordis.europa.eu/project/id/869951

European Union, 2023