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MONSOON SIGNED

MOdel based coNtrol framework for Site-wide OptmizatiON of data-intensive processes

Total Cost €

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EC-Contrib. €

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Partnership

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Project "MONSOON" data sheet

The following table provides information about the project.

Coordinator
ISTITUTO SUPERIORE MARIO BOELLA SULLE TECNOLOGIE DELL'INFORMAZIONE E DELLE TELECOMUNICAZIONI ASSOCIAZIONE 

There are not information about this coordinator. Please contact Fabio for more information, thanks.

 Coordinator Country Italy [IT]
 Project website https://www.spire2030.eu/monsoon
 Total cost 5˙497˙190 €
 EC max contribution 5˙497˙190 € (100%)
 Programme 1. H2020-EU.2.1.5.3. (Sustainable, resource-efficient and low-carbon technologies in energy-intensive process industries)
 Code Call H2020-SPIRE-2016
 Funding Scheme RIA
 Starting year 2016
 Duration (year-month-day) from 2016-10-01   to  2019-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    FONDAZIONE LINKS - LEADING INNOVATION & KNOWLEDGE FOR SOCIETY IT (TORINO) coordinator 869˙743.00
2    ISTITUTO SUPERIORE MARIO BOELLA SULLE TECNOLOGIE DELL'INFORMAZIONE E DELLE TELECOMUNICAZIONI ASSOCIAZIONE IT (TORINO) coordinator 0.00
3    CAPGEMINI TECHNOLOGY SERVICES FR (SURESNES) participant 815˙776.00
4    FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. DE (MUNCHEN) participant 773˙611.00
5    ALUMINIUM PECHINEY FR (VOREPPE) participant 725˙292.00
6    KUNSTSTOFF-INSTITUT FUR MITTELSTANDISCHE WIRTSCHAFT NRW GMBH (KIMW NRWGMBH) DE (LUDENSCHEID) participant 492˙812.00
7    TECHNICKA UNIVERZITA V KOSICIACH SK (KOSICE) participant 472˙875.00
8    ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS EL (THERMI THESSALONIKI) participant 472˙812.00
9    PROBAYES SAS FR (MONTBONNOT SAINT-MARTIN) participant 320˙000.00
10    GLNPLAST SA PT (MACEIRA) participant 258˙015.00
11    LIFE CYCLE ENGINEERING SRL IT (CASTELLAMONTE) participant 215˙000.00
12    ASOCIACION ESPANOLA DE NORMALIZACION ES (MADRID) participant 81˙250.00

Map

 Project objective

The MONSOON vision is to provide Process Industries with dependable tools to help achieving improvements in the efficient use and re-use of raw resources and energy. MONSOON aims at establishing a data-driven methodology supporting the exploitation of optimization potentials by applying multi-scale model based predictive controls in production processes. MONSOON features harmonized site-wide dynamic models and builds upon the concept of the cross-sectorial data lab, a collaborative environment where high amounts of data from multiple sites are collected and processed in a scalable way. The data lab enables multidisciplinary collaboration of experts allowing teams to jointly model, develop and evaluate distributed controls in rapid and cost-effective way. Hybrid simulation and seamless integration techniques are adopted for rapid prototyping and deployment in real conditions. MONSOON will be developed and evaluated in two sites from the aluminium and plastics domains. The aluminium scenario will be focused on predictive monitoring of potlines, targeting early detection of anomalies and identification of potential optimization gains. Aluminium cases will be implemented in the plant with the highest primary aluminium production in the EU-28, namely the AP Dunkerque smelter, France. The plastics scenario will focus on fusing data from data-intensive in-mould sensors with information from higher SCADA levels, enabling early and precise identification of potential issues. This use case will be implemented in the GLN plant in Maceira-Leiria. MONSOON addresses the SPIRE vision, providing advantages for the European industry competitiveness and sustainability through the realization of an overarching monitoring and control infrastructure. MONSOON aims at creating synergies within and between the process industry sectors, boosting European industry in the worldwide race for competitiveness and sustainability.

 Deliverables

List of deliverables.
Final Requirements and Architecture Specifications Documents, reports 2020-03-17 14:12:18
Final Project Advertising Materials and Results Websites, patent fillings, videos etc. 2020-03-17 14:12:18
Updated Report on the standardization landscape and applicable standards Documents, reports 2020-03-17 14:12:18
Report on the contributions to standardization Documents, reports 2020-03-17 14:12:18
Final Multi-scale Model based Development Environment Other 2020-03-17 14:12:18
Final Demonstrators in the Aluminium and Plastics domain Documents, reports 2020-03-17 14:12:18
Final Online and Deep Machine Learning Functions Other 2020-03-17 14:12:18
Final Lifecycle Management plugin Other 2020-03-17 14:12:18
Final Virtual Process industries Resources Adaptation Other 2020-03-17 14:12:18
Final Big Data Storage and Analytics Platform Other 2020-03-17 14:12:18
Final Cross-sectorial Domain Model Documents, reports 2020-03-17 14:12:18
Initial Demonstrators Evaluation and Impact Report Documents, reports 2020-03-17 14:12:18
Final Semantic framework for dynamic multi-scale industry modelling Other 2020-03-17 14:12:18
Initial Project Advertising Materials and Results Websites, patent fillings, videos etc. 2020-03-17 14:12:18
Initial Demonstrators in the Aluminium and Plastics domain Documents, reports 2020-03-17 14:12:18
Final Trend Analysis Functions Other 2020-03-17 14:12:18
Initial Deployment and Maintenance Report Documents, reports 2020-03-17 14:12:18
Initial Lifecycle Management plugin Other 2020-03-17 14:12:17
Updated Real time Communications Framework Other 2020-03-17 14:12:17
Updated Big Data Storage and Analytics Platform Other 2020-03-17 14:12:17
Updated Virtual Process industries Resources Adaptation Other 2020-03-17 14:12:17
Initial Process Industry Domain Analysis and Use Cases Documents, reports 2020-03-17 14:12:17
Test and Integration Plan Documents, reports 2020-03-17 14:12:17
Initial Runtime Container Other 2020-03-17 14:12:17
Project Website Websites, patent fillings, videos etc. 2020-03-17 14:12:17
Initial Virtual Process industries Resources Adaptation Other 2020-03-17 14:12:17
Initial Trend Analysis Functions Other 2020-03-17 14:12:17
Initial Requirements and Architecture Specifications Documents, reports 2020-03-17 14:12:17
Initial Big Data Storage and Analytics Platform Other 2020-03-17 14:12:17
Initial Multi-scale Model based Development Environment Other 2020-03-17 14:12:17
Initial Cross-sectorial Domain Model Documents, reports 2020-03-17 14:12:17
Initial Semantic framework for dynamic multi-scale industry modelling Other 2020-03-17 14:12:17
MONSOON platform usage scenarios Documents, reports 2020-03-17 14:12:17
Initial Real time Communications Framework Other 2020-03-17 14:12:17
Report on the standardization landscape and applicable standards Documents, reports 2020-03-17 14:12:17
Initial Online and Deep Machine Learning Functions Other 2020-03-17 14:12:17
Communication and Dissemination Strategy Documents, reports 2020-03-17 14:12:17
Initial Integrated MONSOON Platform Other 2020-03-17 14:12:16
Initial Evaluation Framework Documents, reports 2020-03-17 14:12:17
Initial Integrated Resource Optimization Toolkit, Decision Support Other 2020-03-17 14:12:16
Updated Process Industry Domain Analysis and Use Cases Documents, reports 2020-03-17 14:12:16

Take a look to the deliverables list in detail:  detailed list of MONSOON deliverables.

 Publications

year authors and title journal last update
List of publications.
2017 Martin Sarnovsky, Peter Bednar (TUK)
MONSOON project – design of big data analysis plaform in process industries (in Slovak)
published pages: 93 - 97, ISSN: , DOI:
Data a znalosti 2020-03-17
2019 Claudio Pastrone
The efficiency of production processes
published pages: , ISSN: , DOI:
Platinum 2020-03-17
2019 Nikolaos Kolokas, Thanasis Vafeiadis, Dimosthenis Ioannidis, Dimitrios Tzovaras
Anomaly detection in aluminum production with unsupervised machine learning classifiers
published pages: , ISSN: , DOI:
International Symposium on INnovations in Intelligent SysTems and Applications 2020-03-17
2019 Achilleas Pasias, Thanasis Vafeiadis, Dimosthenis Ioannidis, Dimitrios Tzovaras
Forecasting bath and metal height features in electrolysis process
published pages: , ISSN: , DOI:
International Workshop on IoT Applications and Industry 4.0 2020-03-17
2019 Bilal Azennoud, Ameline Bernard, Vincent Bonnivard, Hervé Pedroli
Anode Quality Monitoring Using Advanced Data Analytics
published pages: , ISSN: , DOI:
Light Metals 2019: Electrode Technology for Aluminium Production 2020-03-17
2019 Martin Sarnovsky, Peter Bednar, Miroslav Smatana
Cross-Sectorial Semantic Model for Support of Data Analytics in Process Industries
published pages: , ISSN: 2227-9717, DOI:
\"Processes Journal, Special Issue: \"\"Big Data Analysis in the Process Industry\"\"\" 2020-03-17
2018 Nikolaos Kolokas, Thanasis Vafeiadis, Dimosthenis Ioannidis, Dimitrios Tzovaras (CERTH)
Forecasting faults of industrial equipment using machine and deep learning classifiers
published pages: , ISSN: , DOI:
IEEE International Conference on Innovations in Intelligent Systems and Applications 2020-03-17
2018 Jose Antonio Jimenez (UNE)
Optimizing industrial processes through MONSOON
published pages: 24 - 25, ISSN: 2605-0013, DOI:
Revista UNE 2020-03-17
2018 Peter Bednar, Martin Sarnovsky, Miroslav Smatana (TUK)
Big Data Processing and Analytics Platform Architecture for Process Industry Factories
published pages: , ISSN: 2504-2289, DOI:
Big Data and Cognitive Computing Journal 2020-03-17

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