Energy-aware Factory Analytics for Process Industries

Informations projet

FACTLOG

N° de convention de subvention: 869951

DOI

10.3030/869951

Projet clôturé

Date de signature de la CE 14 Novembre 2019

Date de début 1 Novembre 2019

Date de fin 30 Avril 2023

Financé au titre de

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

Coût total

€ 9 199 249,50

Contribution de l’UE

€ 7 089 837,00

Coordonné par

MAGGIOLI SPA
Italy

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Documents, reports (24)

Dissemination and Communication Activities Report V2

This deliverable will report on the dissemination and communciation activities during the second year of the project.

Dissemination and Communication Activities Report V1

This deliverable will report on the dissemination and communciation activities during the first year of the project.

Validation and impact assessment (Interim Version)

Validation and impact assessment of FACTLOG from the pilots.

FACTLOG optimization toolkit and service

Experimentation and validation of the algorithmic framework using FACTLOG data and literature instances - a suite for robust optimization ‘as a service’.

Systemic Cognitive Models Prototypes

A methodology enabling the generation and management of multiple systemic model scenarios plus a dynamic simulation mechanism isolating the physical system and its (augmented) digital twin.

Cognitive Transformation Report (Interim Version)

Preliminary report on Cognitive Transformation of the pilots deploying FACTLOG results as well as demonstrations carried out by the project clusters.

Cognitive Factory Framework

The conceptual framework for the development of Cognitive Digital Twins, focused on Cognitive Plants for Process Industries.

Dissemination and Communication Activities Report V3

This deliverable will report on the dissemination and communciation activities during the last period of the project.

FACTLOG Training and Educational Material V2

This report will describe the training and educational materials designed both from industrial and academic partners.

KG-based analytics for process optimization

A methodology for Knowledge Graph based analytics for process and system optimization, implemented as a Knowledge Core add-on module.

Integration guidelines (Final Version)

Integration guidelines for FACTLOG with external systems.

Validation and impact assessment (Final Version)

Validation and impact assessment of FACTLOG from the pilots.

Knowledge Graphs Modelling

Knowledge graphs including all relevant pieces of an industrial system that enables the integration of heterogeneous – and mostly unstructured – data from diverse sources, thus allowing for flexible and smart knowledge or data querying.

Cognitive Transformation Report (Final Version)

Final report on Cognitive Transformation of the pilots deploying FACTLOG results as well as demonstrations carried out by the project clusters.

Standardisation Activities Report V1

This deliverable will report on the standardisation activities during the first year of the project.

Analytics System Requirements and Design Specification

pilot-specific requirements for analytics, together with the existing sources from sensors to data and meta-data.

Data Collection Framework (Interim Version)

Data collection services and adapters for the pilots.

FACTLOG Training and Educational Material V1

This report will describe the training and educational materials designed both from industrial and academic partners.

Standardisation Activities Report V3

This deliverable will report on the standardisation activities during the last period of the project.

Standardisation Activities Report V2

This deliverable will report on the standardisation activities during the second year of the project.

Process Modelling Methodology

The transformation of WP1 output into Process Models using state of the art standards for system modelling and analysis plus the creation of a hierarchical inheritance registry that will provide prototype reconfigurable building blocks.

Integration guidelines (Interim Version)

Integration guidelines for FACTLOG with external systems.

Data Collection Framework (Final Version)

Data collection services and adapters for the pilots.

Reference Scenarios, KPIs and Datasets

Reference scenarios, KPIs and initial datasets from all pilots.

Demonstrators, pilots, prototypes (7)

Analytical Platform for Process Industry

FACTLOG analytics prototype addressing all requirements, data models and pilot data sets.

Factory Knowledge for Cognition

The output of Interpreting factory knowledge base from the cognition point of view and a set of interfaces for accessing that knowledge.

Integrated Package and Platform (Final Version)

Final FACTLOG prototype for the pilot operation.

Robust and energy-aware planning and scheduling

Models and algorithms for robust multi-objective scheduling/resource allocation plus effective re-scheduling problems.

Anomaly Detection System

Services for detecting anomalous events, anomalies based on CEP, risk prediction and root cause analysis.

Real-time re-optimization algorithms

State-of-the-art re-optimization heuristics combined with exact methods.

Integrated Package and Platform (Interim Version)

Initial FACTLOG prototype for the pilot operation.

Open Research Data Pilot (1)

Initial Data Management Plan

This report will describe the research data generated in the project and how they will be published.

Websites, patent fillings, videos etc. (1)

Project Website

This report will describe the design and deployment of the project website, in particular it aims it intends to reach, the targeted audiences, the structure and tools for online activities monitoring.

Publications

Conference proceedings (20)

Cognitive Twins for Supporting Decision-Makings of Internet of Things Systems

Auteurs: Jinzhi Lu, Xiaochen Zheng, Ali Gharaei, Kostas Kalaboukas, Dimitris Kiritsis
Publié dans: Proceedings of 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing - AMP 2020, 2020, Page(s) 105-115, ISBN 978-3-030-46211-6
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-030-46212-3_7

A Knowledge Management Approach Supporting Model-Based Systems Engineering

Auteurs: Pengfei Yang, Jinzhi Lu, Lei Feng, Shouxuan Wu, Guoxin Wang, Dimitris Kiritsis
Publié dans: Trends and Applications in Information Systems and Technologies (WorldCIST 2021), 2021, Page(s) 581-590
Éditeur: Springer
DOI: 10.1007/978-3-030-72651-5_55

Scheduling Jobs on Unrelated Machines with Job Splitting and Setup Resource Constraints for Weaving in Textile Manufacturin

Auteurs: Ioannis Mourtos, Stavros Vatikiotis & Georgios Zois
Publié dans: IFIP International Conference on Advances in Production Management Systems, 2021, Page(s) 424-434
Éditeur: Springer
DOI: 10.1007/978-3-030-85874-2_45

Utilizing an enhanced digital twin to optimize on-specs LPG recovery

Auteurs: Eirinakis P, Arampatzis G, Košmerlj A, Rožanec J, Sarantinoudis N
Publié dans: 31st European Conference on Operational Research (EURO21), 2022, Page(s) 186
Éditeur: EURO 2021

Digital Twins (DTs) as an integral part of manufacturing Digital Transformation (DX)

Auteurs: Timoleon Farmakis, Stavros Lounis, Ioannis Mourtos and Georgios Doukidis
Publié dans: LEADING AND MANAGING IN THE DIGITAL ERA (LMDE 2023), 2023, Page(s) 35-40, ISBN 978-960-9443-21-0
Éditeur: LMDE

Towards Actionable Cognitive Digital Twins for Manufacturing

Auteurs: Jože M. Rožanec, Lu Jinzhi, Aljaž Košmerlj, Klemen Kenda, Kiritsis Dimitris, Viktor Jovanoski, Jan Rupnik, Mario Karlovčec, Blaž Fortuna
Publié dans: European Semantic Web Conference (ESWC2020), 2020
Éditeur: Springer

The role of Digital Twins and Optimisation in facilitating Digital Transformation in manufacturing.

Auteurs: Lounis S, Doukidis G, Mourtos I
Publié dans: 31st European Conference on Operational Research (EURO21), 2022
Éditeur: EURO 2021

Machine-Learning-Based Soft Sensors for Energy Efficient Operation of Crude Distillation Units

Auteurs: J.M. Rožanec, E. Trajkova, M.K. Onat, N. Sarantinoudis, G. Arampatzis, B. Fortuna and D. Mladenić
Publié dans: International Conference on Electrical, Computer and Energy Technologies (ICECET2022), 2022, ISBN 978-1-6654-7087-2
Éditeur: IEEE
DOI: 10.1109/icecet55527.2022.9872983

A Cognitive Approach to Manage the Complexity of Digital Twin Systems

Auteurs: Jinzhi Lu, Xiaochen Zheng, Lukas Schweiger, Dimitris Kiritsis
Publié dans: Smart Services Summit, 2021, Page(s) 105-115
Éditeur: Springer
DOI: 10.1007/978-3-030-72090-2_10

Exact methods for tardiness objectives in production scheduling

Auteurs: Avgerinos I, Mourtos I, Vatikiotis S, Zois G
Publié dans: 10th IFAC Manufacturing Modelling, Management and Control (MIM22), Numéro 55(10), 2022, Page(s) 2487-2492, ISSN 2405-8963
Éditeur: ScienceDirect
DOI: 10.1016/j.ifacol.2022.10.082

Forecasting sensor values in waste-to-fuel plants

Auteurs: Brecelj, B., Šircelj, B., Rožanec, J. M., Fortuna, B., & Mladenić, D.
Publié dans: Conference on Data Mining and Data Warehouses (SiKDD 2022), 2022
Éditeur: AILAB
DOI: 10.48550/arxiv.2209.13957

Combined Production Scheduling and Predictive Maintenance for PCB Manufacturing

Auteurs: Mourtos I, Kasapidis GA, Repoussis P, Eirinakis P
Publié dans: 31st European Conference on Operational Research (EURO21), 2022
Éditeur: EURO 2021

A mathematical programming approach for optimizing on-specs production for industrial processes under input uncertainty

Auteurs: Eirinakis P, Koronakos G
Publié dans: 10th IFAC Manufacturing Modelling, Management and Control (MIM22), Numéro 55(10), 2022, Page(s) 2822-2827, ISSN 2405-8963
Éditeur: ScienceDirect
DOI: 10.1016/j.ifacol.2022.10.158

Enhancing Cognition for Digital Twins

Auteurs: Pavlos Eirinakis, Kostas Kalaboukas, Stavros Lounis, Ioannis Mourtos, Joze M. Rozanec, Nenad Stojanovic, Georgios Zois
Publié dans: 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 2020, Page(s) 1-7, ISBN 978-1-7281-7037-4
Éditeur: IEEE
DOI: 10.1109/ice/itmc49519.2020.9198492

A unified CP-based evolutionary algorithm for solving flexible job shop scheduling problems with resource constraints

Auteurs: Kasapidis G., Paraskevopoulos D, Mourtos I, Repousis P
Publié dans: 36th Conference of the European Chapter on Combinatorial Optimization (ECCO 2023), 2023, Page(s) 37
Éditeur: ECCO

Production scheduling in the steel reinforcement industry

Auteurs: Konstantinos Kaparis, Kyriakos Bitsis, Stavros Lounis
Publié dans: 31st European Conference on Operational Research (EURO21), 2022
Éditeur: EURO 2021

FACTLOG: Energy-Aware Factory Analytics for Process Industries

Auteurs: Stavros Lounis, Yiannis Mourtos
Publié dans: LEADING AND MANAGING IN THE DIGITAL ERA (LMDE 2023, 2023, Page(s) 284-285, ISBN 978-960-9443-21-0
Éditeur: LMDA

Cognitive Manufacturing: The role of process modelling and optimization

Auteurs: Sarantinoudis N, Tsinarakis G, Kalaboukas K, Eirinakis P, Arampatzis G
Publié dans: 31st European Conference on Operational Research (EURO21), 2022, Page(s) 186
Éditeur: EURO 2021

The cognitive retrofit revolution inside industry: how to modernize factories by Cognitive Digital Twins

Auteurs: Calefato C., Vallini M., Fasana S.
Publié dans: XII Congresso Nazionale Società Italiana di Ergonomia e Fattori Umani (SIE2020), 2020
Éditeur: Springer

Systems Engineering Approach to Identify Requirements for Digital Twins Development

Auteurs: Gharaei A., Lu J., Stoll O., Zheng X., West S., Kiritsis D.
Publié dans: IFIP Advances in Information and Communication Technology (IFIPAICT), Numéro 591, 2020
Éditeur: Springer
DOI: 10.1007/978-3-030-57993-7_10

Peer reviewed articles (17)

Cognitive Digital Twins for Resilience in Production: A Conceptual Framework

Auteurs: Pavlos Eirinakis; Stavros Lounis; Stathis Plitsos; George Arampatzis; Kostas Kalaboukas; Klemen Kenda; Jinzhi Lu; Jože M. Rožanec; Nenad Stojanovic
Publié dans: Information, Numéro 13 (1), 2022, Page(s) 33, ISSN 2078-2489
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/info13010033

Reframing demand forecasting: a two-fold approach for lumpy and intermittent demand

Auteurs: Rožanec, J. M., Fortuna, B., & Mladenić, D.
Publié dans: Sustainability, Numéro 14(15), 2022, ISSN 2071-1050
Éditeur: MDPI Open Access Publishing
DOI: 10.3390/su14159295

The emergence of cognitive digital twin: vision, challenges and opportunities

Auteurs: Xiaochen Zheng, Jinzhi Lu, Dimitris Kiritsis
Publié dans: International Journal of Production Research, Numéro 60(24), 2021, Page(s) 7610-7632, ISSN 0020-7543
Éditeur: Taylor & Francis
DOI: 10.1080/00207543.2021.2014591

Cyber-Physical LPG Debutanizer Distillation Columns: Machine-Learning-Based Soft Sensors for Product Quality Monitoring

Auteurs: Rožanec, J.M.; Trajkova, E.; Lu, J.; Sarantinoudis, N.; Arampatzis, G.; Eirinakis, P.; Mourtos, I.; Onat, M.K.; Yilmaz, D.A.; Košmerlj, A.; et al
Publié dans: MDPI Applied Sciences Special Numéro: Smart Resilient Manufacturing, Numéro 11(24), 2021, Page(s) 11790, ISSN 2076-3417
Éditeur: MDPI
DOI: 10.3390/app112411790

Weighted tardiness minimisation for unrelated machines with sequence-dependent and resource-constrained setups

Auteurs: Ioannis Avgerinos, Ioannis Mourtos, Stavros Vatikiotis & Georgios Zois
Publié dans: International Journal of Production Research, Numéro 62, 2023, Page(s) 359-379, ISSN 0020-7543
Éditeur: Taylor & Francis
DOI: 10.1080/00207543.2023.2275634

Model-Based Simulation Framework for Digital Twins in the Process Industry

Auteurs: Nikolaos Sarantinoudis; Georgios Tsinarakis; Panagiotis Dedousis; George Arampatzis
Publié dans: IEEE Access, Numéro 11, 2023, Page(s) 111701-111714, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2023.3322926

Actionable cognitive twins for decision making in manufacturing

Auteurs: Jože M. Rožanec; Jinzhi Lu; Jan Rupnik; Maja Škrjanc; Dunja Mladenic; Blaž Fortuna; Xiaochen Zheng; Dimitris Kiritsis
Publié dans: International Journal of Production Research, Numéro 60 (2), 2022, Page(s) 452-478, ISSN 0020-7543
Éditeur: Taylor & Francis
DOI: 10.1080/00207543.2021.2002967

Active Learning and Novel Model Calibration Measurements in Manufacturing

Auteurs: Rožanec, J. M., Bizjak, L., Trajkova, E., Zajec, P., Keizer, J., Fortuna, B., & Mladenić, D.
Publié dans: Journal of Intelligent Manufacturing, 2022, ISSN 1572-8145
Éditeur: Springer
DOI: 10.1007/s10845-023-02098-0

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Auteurs: Jinzhi Lu, George Tsinarakis, Nikolaos Sarantinoudis, George Arampatzis, Xiaochen Zheng, Dimitris Kiritsis
Publié dans: Computers & Industrial Engineering, Numéro 190, 2024, ISSN 0360-8352
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.cie.2024.110042

Implementation of Cognitive Digital Twins in Connected and Agile Supply Networks - An Operational Model

Auteurs: Kalaboukas, K.; Rožanec, J.; Košmerlj, A.; Kiritsis, D.; Arampatzis, G
Publié dans: Applied Sciences Special Numéro: Smart Resilient ManufacturingApplied Sciences, Numéro 11(9), 2021, Page(s) 4103, ISSN 2076-3417
Éditeur: MDPI
DOI: 10.3390/app11094103

Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

Auteurs: Jinzhi Lu; Dejiu Chen; Guoxin Wang; Dimitris Kiritsis; Martin Törngren
Publié dans: IEEE Transactions on Systems, Man, and Cybernetics: Systems, Numéro 52(4), 2021, ISSN 2168-2232
Éditeur: IEEE
DOI: 10.1109/tsmc.2020.3048821

Soft sensing of LPG processes using deep learning

Auteurs: Nikolaos Sifakis, Nikolaos Sarantinoudis, George Tsinarakis, Christos Politis and George Arampatzis
Publié dans: Sensors, Numéro 23(18), 2023, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s23187858

Scheduling unrelated machines with job splitting, setup resources and sequence dependency

Auteurs: Vatikiotis S.; Avgerinos I.; Mourtos I.; Zois, G
Publié dans: International Journal of Production Research, Numéro 61(16), 2022, Page(s) 5502-5524, ISSN 0020-7543
Éditeur: Taylor & Francis
DOI: 10.1080/00207543.2022.2102948

A Design Theory for Energy and Carbon Management Systems in the Supply Chain

Auteurs: Zampou, Eleni; Mourtos, Ioannis; Pramatari, Katerina; and Seidel, Stefan
Publié dans: Journal of the Association for Information Systems, Numéro 23(1), 2021, Page(s) 329-371, ISSN 1536-9323
Éditeur: Association for Information Systems
DOI: 10.17705/1jais.00725

A Discrete Process Modelling and Simulation Methodology for Industrial Systems within the Concept of Digital Twins

Auteurs: George ARAMPATZIS; Nikolaos Sarantinoudis; George Tsinarakis
Publié dans: Applied Sciences, Numéro 12 (2), 2022, Page(s) 870, ISSN 2076-3417
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/app12020870

Automotive OEM Demand Forecasting: A Comparative Study of Forecasting Algorithms and Strategies

Auteurs: Jože M. Rožanec; Blaž Kažič; Maja Škrjanc; Blaž Fortuna; Dunja Mladenic
Publié dans: Applied Sciences, Numéro 11 (15), 2022, ISSN 2076-3417
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/app11156787

Governance framework for autonomous and cognitive digital twins in agile supply chains

Auteurs: Kostas Kalaboukas, Dimitris Kiritsis, George Arampatzis
Publié dans: Computers in Industry, Numéro 146, 2023, ISSN 0166-3615
Éditeur: Elsevier BV
DOI: 10.1016/j.compind.2023.103857

Book chapters (1)

Cognitive Digital Twins in the Process Industries

Auteurs: Xiaochen Zheng, Jinzhi Lu, Rebeca Arista, Jože Martin Rožanec, Stavros Lounis, Kostas Kalaboukas, Dimitris Kiritsis
Publié dans: Handbook of Digital Twins, Numéro 1st Edition, 2024, Page(s) 15, ISBN 9781003425724
Éditeur: Taylor & Francis
DOI: 10.1201/9781003425724