COGNITIVE PLANTS THROUGH PROACTIVE SELF-LEARNING HYBRID DIGITAL TWINS

Informazioni relative al progetto

COGNITWIN

ID dell’accordo di sovvenzione: 870130

DOI

10.3030/870130

Progetto chiuso

Data della firma CE 22 Agosto 2019

Data di avvio 1 Settembre 2019

Data di completamento 28 Febbraio 2023

Finanziato da

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing

Costo totale

€ 8 614 343,21

Contributo UE

€ 6 982 431,38

Coordinato da

SINTEF AS
Norway

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (20)

Short Interim Management Report - 3

Short Interim Management Report 3

Short Interim Management Report - 4
IA Coordination and Performance Indicators Measurement
Risk Assessment and Management Action Plan
T0 baseline measurement of the KPIs
Final report and outreach and dissemination activities
Risk Assessment and Management Action Plan - 2
Short Interim Management Report - 2
Short Interim Management Reports
IA Coordination and Performance Indicators Definition
A report on existing level of digitalisation and describing challenges for Steel pilots, incl. identification of novel sensors
IA Coordination and Performance Indicators Measurement - 2
Baseline Hybrid AI and Cogntive Twin Toolbox
Data Management Plan
Documentation providing input to relevant research and education programmes
A report on existing level of digitalization, describing challenges for Engineering pilot, incl. identification of novel sensors and collected information for cognitive modelling
Intermediate report on dissemination activities
Baseline Platform, Sensor and Data Interoperability Toolbox
Dissemination and communication plan and tools
A report on existing level of digitalisation and describing challenges for Non-ferrous pilots, incl. identification of novel sensors

Demonstrators, pilots, prototypes (9)

Updated Platform, Sensor and Data Interoperability Toolbox
A complete Cognitive Twin for Engineering pilot
Initial Platform, Sensor and Data Interoperability Toolbox
Final Hybrid AI and Cogntive Twin Toolbox
Updated Hybrid AI and Cogntive Twin Toolbox
A complete digital twin enabled with cognitive elements for the Steel pilots
A complete digital twin enabled with cognitive elements for the Non-ferrous pilots
Initial Hybrid AI and Cogntive Twin Toolbox
Final Platform, Sensor and Data Interoperability Toolbox

Websites, patent fillings, videos etc. (1)

Website portal

Other (1)

Material prepared for the workshops and final conclusions

Pubblicazioni

Peer reviewed articles (10)

Digital Twin and Internet of Things—Current Standards Landscape

Autori: Michael Jacoby, Thomas Usländer
Pubblicato in: Applied Sciences, Numero 10/18, 2020, Pagina/e 6519, ISSN 2076-3417
Editore: MDPI
DOI: 10.3390/app10186519

Estimating Fuel Characteristics from Simulated Circulating Fluidized Bed Furnace Data

Autori: Neuvonen, M. (Markus); Selek, I. (Istvan); Ikonen, E. (Enso)
Pubblicato in: 2021 9th International Conference on Systems and Control (ICSC), Numero 23790067, 2021, Pagina/e 107-112, ISSN 2379-0067
Editore: IEEE
DOI: 10.1109/icsc50472.2021.9666596

Methodology and Tools for Digital Twin Management—The FA3ST Approach

Autori: Ljiljana Stojanovic, Thomas Usländer, Friedrich Volz, Christian Weißenbacher, Jens Müller, Michael Jacoby, Tino Bischoff
Pubblicato in: IoT, Numero 2, 2021, Pagina/e 717-740, ISSN 2624-831X
Editore: MDPI
DOI: 10.3390/iot2040036

Neuroscope: An Explainable AI Toolbox for Semantic Segmentation and Image Classification of Convolutional Neural Nets

Autori: Christian Schorr; Payman Goodarzi; Fei Chen; Tim Dahmen
Pubblicato in: Applied Sciences, Numero 20763417, 2021, Pagina/e 2199(1-16), ISSN 2076-3417
Editore: MDPI
DOI: 10.3390/app11052199

Impact on Inference Model Performance for ML Tasks Using Real-Life Training Data and Synthetic Training Data from GANs

Autori: Ulrike Faltings; Tobias Bettinger; Swen Barth; Michael Schäfer
Pubblicato in: Information, Numero 20782489, 2021, Pagina/e 9(1-15), ISSN 2078-2489
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/info13010009

A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data

Autori: Sahan Yoruç Selçuk,Perin Ünal, Özlem Albayrak, Moez Jomâa
Pubblicato in: Information, Numero 12, 2021, Pagina/e 386(1-14), ISSN 2078-2489
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/info12100386

Transfer Learning Enabled Bearing Fault Detection Methods Based on Image Representations of Single-Dimensional Signals

Autori: Bilgin Umut Deveci, Mert Çeltikoglu, Özlem Albayrak, Perin Ünal, Pınar Kırcı
Pubblicato in: Information Systems Frontiers, 2023, ISSN 1572-9419
Editore: Springer Nature
DOI: 10.1007/s10796-023-10371-z

An Approach for Realizing Hybrid Digital Twins Using Asset Administration Shells and Apache StreamPipes

Autori: Michael Jacoby, Branislav Jovicic, Ljiljana Stojanovic, Nenad Stojanović
Pubblicato in: Information, Numero 12/6, 2021, Pagina/e 217, ISSN 2078-2489
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/info12060217

Fusing Physical Process Models with Measurement Data Using FIR Calibration

Autori: Enso Ikonen, Istvan Selek
Pubblicato in: Journal of Control Engineering and Applied Informatics, Numero Vol 23, No 2, 2021, Pagina/e 67-76, ISSN 1454-8658
Editore: Romanian Society of Control Engineering and Technical Informatics

Hybrid and Cognitive Digital Twins for the Process Industry

Autori: Stein Tore Johansen, Perin Unal, Özlem Albayrak, Enso Ikonen, Kasper J. Linnestad, Sudi Jawahery, Akhilesh K. Srivastava, Bjørn Tore Løvfall
Pubblicato in: Open Engineering, Numero 13(1), 2023, Pagina/e 20220418, ISSN 2391-5439
Editore: Walter de Gruyter GmbH & Co. KG
DOI: 10.1515/eng-2022-0418

Book chapters (3)

Smart Steel Pipe Production Plant via Cognitive Digital Twins: A Case Study on Digitalization of Spiral Welded Pipe Machinery

Autori: Özlem Albayrak, Perin Ünal
Pubblicato in: Impact and Opportunities of Artificial Intelligence Techniques in the Steel Industry - Ongoing Applications, Perspectives and Future Trends, Numero 1338, 2021, Pagina/e 132-143, ISBN 978-3-030-69366-4
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-69367-1_11

Smart Services in the Physical World: Digital Twins

Autori: Ljiljana Stojanovic, Sebastian R. Bader
Pubblicato in: Smart Service Management - Design Guidelines and Best Practices, 2020, Pagina/e 137-147, ISBN 978-3-030-58181-7
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-58182-4_12

Data-Driven Artificial Intelligence and Predictive Analytics for the Maintenance of Industrial Machinery with Hybrid and Cognitive Digital Twins

Autori: Perin Unal, Özlem Albayrak, Moez Jomâa, Arne J. Berre
Pubblicato in: Technologies and Applications for Big Data Value, 2022, Pagina/e 299-320, ISBN 978-3-030-78306-8
Editore: Springer, Cham
DOI: 10.1007/978-3-030-78307-5

Conference proceedings (12)

Simultaneous Prediction of Remaining-Useful-Life and Failure-Likelihood with GRU-based Deep Networks for Predictive Maintenance Analysis

Autori: Ali Yuce Kaleli; Aras Firat Unal; Sedat Ozer
Pubblicato in: 2021 44th International Conference on Telecommunications and Signal Processing (TSP), 2021, Pagina/e 301-304, ISBN 978-1-6654-2933-7
Editore: IEEE
DOI: 10.1109/tsp52935.2021.9522592

Control System Design and Implementation Based on Big Data and Ontology

Autori: Seyithan Temel, Emre Ummak, Abdülkadir Tokgöz, Furkan Işık, Özlem Albayrak, Perin Ünal, Murat Özbayoğlu
Pubblicato in: 2022 IEEE International Conference on Big Data (Big Data), 2022, Pagina/e 6048-6056, ISBN 978-1-6654-8045-1
Editore: IEEE
DOI: 10.1109/bigdata55660.2022.10020589

Digitalization of a Steel Pipe Production Factory: STEEL4.0- A Family of Products Developed on Routes from Industry 3.0 to Industry 4.0

Autori: Özlem ALBAYRAK, Perin ÜNAL*
Pubblicato in: Fifth International Iron & Steel Symposium, Data Science in Process Engineering, 2021, ISBN 978-605-9554-57-2
Editore: Karabük University Publishing

Cognitive Digital Twins for the Process Industry

Autori: Abburu, Sailesh; Berre, Arne J.; Jacoby, Michael; Roman, Dumitru; Stojanovic, Ljiljana; Stojanovic, Nenad
Pubblicato in: International Conference on Advanced Cognitive Technologies and Applications, 2020, ISBN 978-1-61208-780-1
Editore: International Conference on Advanced Cognitive Technologies and Applications

COGNITWIN – Hybrid and Cognitive Digital Twins for the Process Industry

Autori: Sailesh Abburu, Arne J. Berre, Michael Jacoby, Dumitru Roman, Ljiljana Stojanovic, Nenad Stojanovic
Pubblicato in: 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 2020, Pagina/e 1-8, ISBN 978-1-7281-7037-4
Editore: IEEE
DOI: 10.1109/ice/itmc49519.2020.9198403

On-line estimation of circulating fluidized bed boiler fuel composition

Autori: Enso Ikonen; Markus Neuvonen; Istvan Selek; Mikko Salo; Mika Liukkonen
Pubblicato in: 2022 UKACC 13th International Conference on Control (CONTROL), 2022, Pagina/e 136-141, ISBN 978-1-6654-5201-4
Editore: IEEE
DOI: 10.1109/control55989.2022.9781460

A Comprehensive Comparison of State-of-Art Machine Learning Algorithms on Fault Indication and Remaining Useful Life Determination by Telemetry Data

Autori: Aras Ünal, Ali Kaleli, Emre Ummak, Özlem Albayrak
Pubblicato in: The 8th International Conference on Future Internet of Things and Cloud, 2021, Pagina/e 79-85, ISBN 978-1-6654-2575-9
Editore: IEEE
DOI: 10.1109/ficloud49777.2021.00019

A Comparison of Deep Transfer Learning Methods on Bearing Fault Detection

Autori: Bilgin Umut Deveci; Mert Celtikoglu; Tilbe Alp; Ozlem Albayrak; Perin Ünal; Pinar Kirci
Pubblicato in: 2021 8th International Conference on Future Internet of Things and Cloud (FiCloud), Numero 1, 2021, Pagina/e 285-292, ISBN 978-1-6654-2574-2
Editore: IEEE
DOI: 10.1109/ficloud49777.2021.00048

Heat exchanger fouling estimation for combustion–thermal power plants including load level dynamics

Autori: Markus Neuvonen; Istvan Selek; Enso Ikonen; Lauri Aho
Pubblicato in: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2022, Pagina/e 2987-2992, ISBN 978-1-6654-0782-3
Editore: IEEE
DOI: 10.1109/smc53654.2022.9945541

Asset Administration Shell Generation and Usage for Digital Twins: A Case Study for Non-destructive Testing.

Autori: Fatih Yallıç, Özlem Albayrak, Perin Ünal
Pubblicato in: 3rd International Conference on Innovative Intelligent Industrial Production and Logistics, ETCIIM 2022, 2022, ISBN 978-989-758-612-5
Editore: SCITEPRESS - Science and Technology Publications, Lda.
DOI: 10.5220/0011561400003329

A Hybrid Digital Twin for Optimal Si-Production

Autori: Kasper Linnestad, Kjetil Hildal, Lars K. Jakobsson, Sølve Eidnes, Vemund Tjessem, Erlend L. Bjørnstad, Stein Wasbø
Pubblicato in: Proceedings of the Silicon for the Chemical & Solar Industry XVI, 2022, Pagina/e 1-16, ISBN 978-82-692919-0-2
Editore: SSRN
DOI: 10.2139/ssrn.4121131

Calibration of Physical Models with Process Data using FIR Filtering

Autori: Enso Ikonen, Istvan Selek
Pubblicato in: 2020 Australian and New Zealand Control Conference (ANZCC), 2020, Pagina/e 143-148, ISBN 978-1-7281-9992-4
Editore: IEEE
DOI: 10.1109/anzcc50923.2020.9318340