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Secure Management Platform for Shared Process Resources (SHAREBOX)
Date du début: 1 sept. 2015, Date de fin: 31 août 2019 PROJET  TERMINÉ 

To pave the way forward for IS as a solution for more efficient processing and energy systems for the process industry, we will develop a secure ICT platform (SHAREBOX) for the flexible management of shared process resources that will provide plant operations and production managers with the robust and reliable information that they need in real-time in order to effectively and confidently share resources (plant, energy, water, residues, and recycled materials) with other companies in a symbiotic eco-system. A suite of new analysis and optimisation tools for flexible energy use and material flow integration will be developed for optimising symbiosis among companies. These tools will be based on input-output (IO) modelling for resource (waste and energy) supply-demand matching and process efficiency analysis (to understand physical and technological conditions), game theoretical (GT) approach for integrating company behaviour in cost-, benefit-, and resource-sharing (to understand economic conditions), and agent-based modelling (ABM) for designing the (economic, environmental, and social) optimal symbiotic network (to have the holistic optimum). The outputs from the SHAREBOX controller will provide plant and operations managers with commands for actions to be taken and/or recommendations for decision support. It will be ensured that all commands and recommendations a) fulfil plant operations requirements, b) are within the constraints of any contractual obligations, c) are in compliance with all regulatory thresholds, and d) deliver optimal impacts in terms of cost/savings and ecological footprints. The historical data that is generated by the SHAREBOX platform will be processed by data mining tools that will provide the production/process BIG DATA for symbiotic shared resources optimisation. The platform will be co-created, implemented and tested at 4 demo locations in EU, using realistic industrial streams and process conditions.

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