Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration

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Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration

Environmental sustainability


Specifics for Project DISRUPT | Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration

Manufacturing the products of the future


Specifics for Project DISRUPT | Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration

Title Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration
Description Industry 4.0 is the next developmental stage in the organisation of the manufacturing value chain.
Organisation THE UNIVERSITY OF MANCHESTER
Comments to detect complex events, and at the higher level to monitor the behaviour of processes and products.
 D2.4: Validation and Improvement of KPIs for the DISRUPT environment Result title D2.4: Validation and Improvement of KPIs for the DISRUPT environment
 Periodic Reporting for period 1 - DISRUPT (Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration) Result description To exploit big data technologies and modern cloud-based architectures to increase the efficiency of ICT tools and services in future smart manufacturing applications.
 R&I Objective 1.4: Artificial intelligence for productive, excellent, robust and agile manufacturing chains - Predictive manufacturing capabilities & logistics of the future Taxon title R&I Objective 1.4: Artificial intelligence for productive, excellent, robust and agile manufacturing chains - Predictive manufacturing capabilities & logistics of the future
 Material efficiency Taxon description   Making a usable item out of thinner stock than a prior version increases the material efficiency of the manufacturing process.
 Data analytics Comments to detect complex events, and at the higher level to monitor the behaviour of processes and products.