Opendata, web and dolomites

FUDIPO SIGNED

Future Directions of Production Planning and Optimized Energy- and Process Industries

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "FUDIPO" data sheet

The following table provides information about the project.

Coordinator
MAELARDALENS HOEGSKOLA 

Organization address
address: HOGSKOLEPLAN 1
city: VASTERAS
postcode: 721 23
website: www.mdh.se

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Sweden [SE]
 Project website http://www.fudipo.eu
 Total cost 5˙740˙676 €
 EC max contribution 5˙740˙676 € (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  2020-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MAELARDALENS HOEGSKOLA SE (VASTERAS) coordinator 1˙135˙158.00
2    TIETO AUSTRIA GMBH AT (WIEN) participant 680˙072.00
3    ABB POWER GRIDS SWEDEN AB SE (VASTERAS) participant 661˙521.00
4    BESTWOOD AB SE (SUNDBYBERG) participant 591˙077.00
5    FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. DE (MUNCHEN) participant 433˙520.00
6    Turkiye Petrol Rafinerileri Anonim Sirketi TR (Kocaeli) participant 428˙890.00
7    RISE RESEARCH INSTITUTES OF SWEDEN AB SE (BORAS) participant 373˙393.00
8    RISE SICS VASTERAS AB SE (VASTERAS) participant 356˙615.00
9    MALARENERGI AB SE (VASTERAS) participant 304˙070.00
10    MICRO TURBINE TECHNOLOGY BV NL (BREDA) participant 303˙375.00
11    OPTIMIZACION ORIENTADA A LA SOSTENIBILIDAD SL ES (SEVILLA) participant 250˙720.00
12    BILLERUDKORSNAS AKTIEBOLAG (PUBL) SE (SOLNA) participant 222˙262.00

Map

 Project objective

Machine learning have revolutionized the way we use computers and is a key technology in the analysis of large data sets. The FUDIPO project will integrate machine learning functions on a wide scale into several critical process industries, showcasing radical improvements in energy and resource efficiency and increasing the competitiveness of European industry. The project will develop three larger site-wide system demonstrators as well as two small-scale technology demonstrators. For this aim, FUDIPO brings together five end-user industries within the pulp and paper, refinery and power production sectors, one automation industry (LE), two research institutes and one university. A direct output is a set of tools for diagnostics, data reconciliation, and decision support, production planning and process optimization including model-based control. The approach is to construct physical process models, which then are continuously adapted using “good data” while “bad data” is used for fault diagnostics. After learning, classification of data can be automated. Further, statistical models are built from measurements with several new types of sensors combined with standard process sensors. Operators and process engineers are interacting with the system to both learn and to improve the system performance. There are three new sensors included (TOM, FOM and RF) and new functionality of one (NIR). The platform will have an open platform as the base functionality, as well as more advanced functions as add-ons. The base platform can be linked to major automation platforms and data bases. The model library also is used to evaluate impact of process modifications. By using well proven simulation models with new components and connect to the process optimization system developed we can get a good picture of the actual operations of the modified plant, and hereby get concurrent engineering – process design together with development of process automation.

 Deliverables

List of deliverables.
Project website with content for public consumption Documents, reports 2020-01-24 15:00:06

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

 Publications

year authors and title journal last update
List of publications.
2019 Dahlquist, E., Nordlander, E., Thorin, E., Wallin, C., Avelin, A
Control of wastewater treatment combined with irrigation
published pages: , ISSN: , DOI:
11th International Conference of Applied Energy and 60th SIMS, Vasteras 12-16 August 2019. 2020-03-06
2018 Anbalagan, Anbarasan
A passage to wastewater nutrient recovery units: Microalgal-Bacterial bioreactors.
published pages: , ISSN: , DOI:
2020-03-06
2017 Mahsa Daraei, master thesis ””, Mälardalen University press, 2017.
Evaluation and prediction of wood properties in pulp and paper production
published pages: , ISSN: , DOI:
Malardalen University press 2020-01-24
2017 Al Hamrani, Emad och Gibrael, Nemir,
Fast determination of fuel/feedstock material properties and composition: By Near infrared (NIR) spectroscopy
published pages: , ISSN: , DOI:
Mälardalen University press 2020-01-24
2017 Mahsa Darei,
rediction of pulp yield and Kappa number using NIR-regression models: Acase study Within BillerudKorsnäs, Gävle in Sweden
published pages: , ISSN: , DOI:
ICNIR2017 i Danmark, 2017 2020-01-24
2018 Aslanidou, I., Zaccaria, V., Rahman, M., Oostveen, M., Olsson, T., Kyprianidis, K.G.,
Towards an Integrated Approach for Micro Gas Turbine Fleet Monitoring, Control, and Diagnostics
published pages: , ISSN: , DOI:
Global Power and Propulsion Society Forum, GPPF 2018, Zurich, Switzerland January 2018 2020-01-24
2018 Zaccaria, V., Stenfelt, M., Aslanidou, I., Kyprianidis, K.G., 2018,“ ”, accepted for presentation at
Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines
published pages: , ISSN: , DOI:
ASME Turbo Expo, Oslo, Norway, June 2018 2020-01-24
2018 Moksadur Rahman, Anders Avelin, Konstantinos Kyprianidis, Johan Jansson,  Erik Dahlquist
Model based Control and Diagnostics strategies for a Continuous Pulp Digester
published pages: , ISSN: , DOI:
PaperCon 2018 2020-01-24
2018 Christian Wallin and Jesús Zambrano
MIMO System Identification of an Activated Sludge Process – BSM1 as case study. Abstract accepted, full paper submitted May 15 2018.
published pages: , ISSN: , DOI:
59th International Conference of Scandinavian Simulation Society, SIMS 2018, in Oslo, Norway. September 26-28, 2018. 2020-01-24

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "FUDIPO" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "FUDIPO" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.2.1.5.3.)

IMPRESS (2019)

Integration of efficient downstreaM PRocessEs for Sugars and Sugar alcohols

Read More  

HyperCOG (2019)

Hyperconnected Architecture for High Cognitive Production Plants

Read More  

PERFORM (2019)

PowerPlatform: Establishment of platform infrastructure for highly selective electrochemical conversions

Read More