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Optimization and performance improving in metal industry by digital technologies

Resultado final

On-line monitoring and predictive control tools developed

Modelbased online monitoring and predictive control tools for liquid steelmaking and rolling processes are developed

Final assessment of the social acceptance of new tools in productive plants

Deliverable will analyze the feedback coming from endusers in a highly confidential manner considering the possibility of better adapt the tools to real daily necessities

Mid requirements & specifications for Use case 2: : Smart sensor and model-based decision support system for ultra clean steel production

As a result of the deep analysis of the status and innovation potential by elevating the overall degree of digitalization in terms of instrumentation equipment, data collection, data analysis and control technology for Use case 2: Smart sensor and model-based decision support system for ultra clean steel production; the requirements and specifications for Use case 2 will be issued in Deliverable D2.3 in M6. This will be a first approach for developing process improvements in terms of energy efficiency, minimizing waste, environmental aspects, product quality and productivity.

Final requirements & specifications for Use case 3: Deployment of digital cognitive architecture in non-ferrous industrial case

Deliverable D2.5 will be updated in M20 to define the final requirements and specifications explaining by what means the requirements will be achieved (installed new control and instrumentation equipment, data collection, data analysis, etc.) for Use case 3: Deployment of digital cognitive architecture in non-ferrous industrial case.

Design principles for data infrastructure

This document will contain set of design principles recommendations and guidelines for data infrastructure based on consolidated set of requirements Document will cover different aspects of data infrastructure design including industry standards cloud concepts and technologies capacity and performance security availability reliability and similar

ZRM basic control system upgrade

This deliverable will give a report on upgrading the basic control and measurement equipment

Final requirements & specifications for Use case 2: : Smart sensor and model-based decision support system for ultra clean steel production

Deliverable D2.3 will be updated in M20 to define the final requirements and specifications explaining by what means the requirements will be achieved (installed new control and instrumentation equipment, data collection, data analysis, etc.) for Use case 2: Smart sensor and model-based decision support system for ultra clean steel production.

Report on finished industrial trials and evaluated operation of the cognitive system

The results of the industrial validation trials including the automation in prescriptions definition that will avoid human mistakes in final decisions will be summarised in deliverable 93 for different production batches for each selected reference If necessary the prediction algorithms and prescriptions will be adjusted to improve its accuracy

Cognitive system to achieve multi-criterial objectives

The capacity of the cognitive system to achieve multicriterial objetives will be proven online and summarized in Deliverable 92 The capacity to generate prescriptions in terms of alarms being sent to workers to adjust the process accordingly resulting in an automated decision making will be also reported in this deliverable

Final requirements & specifications for Use case 1: Implementation of the EAF and ZRM optimization

Deliverable D21 will be updated in M20 to define the final requirements and specifications explaining by what means the requirements will be achieved installed new control and instrumentation equipment data collection data analysis etc for Use case 1 Implementation of the EAF and ZRM optimization

ZRM process model documentation

A report on a general process model developed in WP4 and further developed and adapted to production environment in WP7 The model will represent and optimization tool enabling various analyses parameter setup and operational adaptation of critical parameters

Predicted castability and cleanliness level

The report will summarize the analysis of casting process parameters, and based on that, a quantification of the expected castability and cleanliness level of steel samples will be provided. Results of post-mortem analysis clogging materials taken from casting nozzles will be also a part of the report.

Final quantification of the economic impact of improved manufacturing processes routes

Deliverable will summarize the evolution of KPIs related to economical and yield aspects This report will explore the economic benefits of already more efficient factories

Final quantification of the environmental impact of improved manufacturing processes routes

Deliverable will show the results of the optimized process from the environmental and resources efficiency point of view through related KPIs Considering identified indexes on deliverable D63 quantification of the environment related improvements will be done

Mid quantification of the economic impact of improved manufacturing processes routes

Deliverable will summarize the evolution of KPIs related to economical and yield aspects Initial economic benefits will be calculated these numbers will serve as a reference for further improvements impact assessment

Guidelines for the advisory system and its components

The guidelines should consist of suggestions for countermeasures during secondary metallurgical treatment within the scope considered in the process model Especially overall treatment times stirring parameters slag strategies for Basic Oxygen Furnace and Electric Arc Furnace operation are expected to be defined These parameters rely on castability inclusion chemistry desulphurization and steel cleanliness representing components of the advisory system

Mid quantification of the environmental impact of improved manufacturing processes routes

Deliverable will show the results of the optimized process from the environmental and resources efficiency point of view through related KPIs A first general overview of the impact caused by developed tools in their preliminary stage will be done

Mid requirements & specifications for Use case 3: Deployment of digital cognitive architecture in non-ferrous industrial case

As a result of the deep analysis of the status and innovation potential by elevating the overall degree of digitalization in terms of instrumentation equipment data collection data analysis and control technology for Use case 3 Deployment of digital cognitive architecture in nonferrous industrial case the requirements and specifications for Use case 3 will be issued in Deliverable D25 in M6 This will be a first approach for developing process improvements in terms of energy efficiency minimizing waste environmental aspects product quality and productivity

Communication and dissemination plan

Dissemination plan is based on the activities named in proposal In the reports the progress will be checked and the results evaluated Communication plan will coordinate all communication activities

Analysis software for process and sensor data developed

Software for analysis of sensor data Image and vibration sensors and process data analysis software for liquid steelmaking rolling and nonferrous casting is developed

Validated data acquisition and sensor technologies

The report dedicated to this deliverable will describe the installed systems and strategies for data collection and storage being used in the use cases Electric Arc Furnace operation cold rolling mill secondary metallurgical treatment processes ie ladle furnace and vacuum degassing and nonferrous alloy casting A validation of the applicability of sensor technologies should define the suitable systems for a further usage within the project

Predicted KPIs for different references and batches

This deliverable will give the predicted KPIs selected by EIPC for different references and batches to monitor the capacity of the system to achieve a multi-criterial objectives.

Recoded EAF model and optimization framework

A report on final implementation of the developed enhanced EAF models and EAF optimization framework and user interfaces in a suitable programming language such as C or similar

Training materials

A report on prepared training materials and programs which will be intended for employees in similar process industries and will include the results conclusions and knowhow obtained during the course of the project Furthermore the report will also include the information on identified target groups and availability of the gathered materials on publicly accessible media

Design principles for communication infrastructure

This document will contain set of design principles recommendations and guidelines for communication infrastructure based on consolidated set of requirements Document will cover different aspects of infrastructure design including industry standards capacity performance security availability reliability and similar

Mid assessment of the social acceptance of new tools in productive plants

This report will be focused on the identification of end users main concerns about the industrial process to be modeled on the concentration of the expectations to be covered by the final product and on the definition of possible mechanisms training communication to ensure successful implementation

Mid requirements & specifications for Use case 1: Implementation of the EAF and ZRM optimization

As a result of the deep analysis of the status and innovation potential by elevating the overall degree of digitalization in terms of instrumentation equipment data collection data analysis and control technology for Use case 1 Implementation of the EAF and ZRM optimization the requirements and specifications for Use case 1 will be issued in Deliverable D21 in M6 This will be a first approach for developing process improvements in terms of energy efficiency minimizing waste environmental aspects product quality and productivity

Consolidated set of requirements

This document will contain set of functional and technical requirements for both communication and data infrastructure. Requirements will be derived from individual UC requirements and specification.

Guidelines for the digital architecture implementation in the industry

Based on the results obtained from Use case 3 guidelines for digital architecture implementation in the foundry industry will be issued in Deliverable 94

Finished industrial trials and evaluated operation of the supervisory system

A report will be generated consisting of the experimental campaign results Different steel grades defined by SID and VAS will be tested whereas varying process parameters will be applied based on the advisory systems suggestions The comprehensive analysis of the test trials should lead to a quantification of necessary optimization cycles of the online advisory system to improve its accuracy

Advisory system for optimization and control of process operation

The current deliverable will summarize the developed advisory system consisting of models for castability inclusion formation and removal as well as desulphurization The interfaces to the users IT systems will be defined Integration of networked based sensor technologies will be reported such as the camerabased imaging system from VAS or accelerometerbased vibration at SID for ladle car stirring monitoring

ZRM software and hardware platform documentation

A report on development and implementation of data collection system It will determine which communication protocols will be used and which operational data will be collected

Decision support systems set-up

Rule and expert knowledgebased decision support and control systems for EAF steelmaking liquid steel refining and casting rolling and nonferrous casting processes are set up

Communication interfaces

To be able to perform longterm data storage communication protocols and different signal types must be accepted by the systems Communication interfaces between data storage and the investigated plants must be defined All these requirements and protocols will be summarized in a report dedicated to this D33

ZRM diagnostic, condition monitoring and control algorithms

A report on implemented diagnistic and condition monitoring algorithms Algoriths will be based on a process model and will support the operator

Acquisition and storage technologies

According to the sensor technology validation necessary hardware extensions and or modifications will be documented within this report Additionally corresponding data acquisition and storage systems will be definedimplemented to be capable to collect all data types according the proposed expectations

Predictive process models

Analytical and datadriven predictive models for liquid steelmaking rolling and nonferrous casting processes are developed

Long-term data sets and sensor evaluation

Long-term data acquisition trails are repeated periodically for a certain cycle during the whole project duration. These trails should evaluate the used sensors regarding their long-term functionality and implementation potential. Certain kind of data reduction or compression methods will be applied to signals of high sampling rates. This enables a sustainable data storage strategy for future installations and long-term data analyses. Based on the results, a condition-based methodology can be developed.

EAF model and optimization user interfaces

A report on final implementation of the combined EAF models, EAF optimization framework and dedicated user interfaces in appropriate form. The developed solution will include all necessary features and functionalities to allow its proper use by process operators and technologists.

Multi-criterial optimization algorithms developed

Model Predictive Control MPC supported multicriterial online optimization algorithms for nonferrous casting process are developed

Data Management Plan

Data Management Plan will specify what data will be opened to public

Project advertising material

Advertising material will be prepared which will promote project idea provide upto date project news and awareness about the dissemination results

Project website

Website will be established, which will provide up-to date project news and awareness about the dissemination results.

Publicaciones

Comparison of data-based models for prediction and optimization of energy consumption in electric arc furnace (EAF)

Autores: Goran Andonovski; Simon Tomažič
Publicado en: IFAC-PapersOnLine, Edición Volume 55, Edición 20, 2022, ISSN 2405-8963
Editor: Elsevier
DOI: 10.1016/j.ifacol.2022.09.123

Big Data Handling in Process Surveillance and Quality Control of Secondary Metallurgical Processes

Autores: Christine Gruber; Birgit Bückner; Magdalena Schatzl; Maria Thumfart; Ramona Eßbichl; Roman Rössler
Publicado en: steel research international, Edición Volume93, Edición12, 2022, ISSN 1611-3683
Editor: Verlag Stahleisen GmbH
DOI: 10.1002/srin.202200060

Soft sensor of bath temperature in an electric arc furnace based on a data-driven Takagi–Sugeno fuzzy model

Autores: Aljaž Blažič, Igor Škrjanc, Vito Logar
Publicado en: Applied Soft Computing, Edición Volume 113, Part B, 2021, ISSN 1568-4946
Editor: Elsevier BV
DOI: 10.1016/j.asoc.2021.107949

Perspectives on weak interactions in complex materials at different length scales

Autores: J. Fiedler; K. Berland; J. W. Borchert; R. W. Corkery; A. Eisfeld; D. Gelbwaser-Klimovsky; M. M. Greve; B. Holst; K. Jacobs; M. Krüger; D. F. Parsons; C. Persson; M. Presselt; T. Reisinger; S. Scheel; F. Stienkemeier; M. Tømterud; M. Walter; R. T. Weitz; J. Zalieckas
Publicado en: Phys. Chem. Chem. Phys., Edición Volume 25, Edición 4, 2023, Página(s) 2671-2705, ISSN 1463-9076
Editor: Royal Society of Chemistry
DOI: 10.1039/d2cp03349f

Data-Driven Modelling and Optimization of Energy Consumption in EAF

Autores: Simon Tomažič; Goran Andonovski; Igor Škrjanc; Vito Logar
Publicado en: Metals, Edición 12, 816, 2022, ISSN 2075-4701
Editor: MDPI
DOI: 10.3390/met12050816

Detection and isolation of oscillation sources in cold rolling mills

Autores: Pavel Ettler; Miha Glavan
Publicado en: IFAC-PapersOnLine, Edición volume 55, issue 21, 2022, Página(s) 186-191, ISSN 2405-8963
Editor: Elsevier
DOI: 10.1016/j.ifacol.2022.09.265

Material Requirements Planning Using Variable-Sized Bin-Packing Problem Formulation with Due Date and Grouping Constraints

Autores: Dejan Gradišar, Miha Glavan
Publicado en: Processes, Edición 8/10, 2020, Página(s) 1246, ISSN 2227-9717
Editor: MDPI
DOI: 10.3390/pr8101246

The Influence of Electric-Arc-Furnace Input Feeds on its Electrical Energy Consumption

Autores: Vito Logar, Igor Škrjanc
Publicado en: Journal of Sustainable Metallurgy, Edición 7/3, 2021, Página(s) 1013-1026, ISSN 2199-3823
Editor: Springer Nature
DOI: 10.1007/s40831-021-00390-y

SIMULATION OF SLOWLY VARYING OSCILLATIONS IN COLD ROLLING MILLS

Autores: Pavel Ettler
Publicado en: ESM2020-The 2020 European Simulation and Modelling Conference, Edición October 21-23, 2020, 2020, Página(s) 237-241
Editor: EUROSIS-ETI (EUROSIS - The European Multidisciplinary Society for Modelling and Simulation Technology, ETI-European Technology Institute)

Fuzzy Interval Oxygen Estimation in an Electric Arc Furnace from Scarce Output Measurements

Autores: Aljaž Blažič; Vito Logar; Igor Škrjanc
Publicado en: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2022), 2022, ISSN 1558-4739
Editor: IEEE
DOI: 10.1109/fuzz-ieee55066.2022.9882618

Digital transformation of the steelmaking industry : an EAF case study

Autores: Vito Logar, Simon Tomažič, Goran Andonovski, Aljaž Blažič, Igor Škrjanc
Publicado en: EASES : abstract booklet : 4th European Academic Symposium on EAF Steelmaking organized, 2021, Página(s) 36-37
Editor: RWTH Aachen University, Department for Industrial Furnaces and Heat Engineering

Monitoring of sensor equipment of a cold rolling mill based on mass flow evaluatio (Nadzor senzorske opreme stroja za hladno valjanje s spremljanjem masnega pretoka)

Autores: Dejan Gradišar, Miha Glavan, Gregor Dolanc, Mojca Loncnar
Publicado en: Zbornik dvanajste konference Avtomatizacija v industriji in gospodarstvu, 8. april 2021., Edición 8. April 2021, 2021
Editor: Društvo avtomatikov Slovenije

Optimization of cold rolling process recipes based on historical data

Autores: Kristjan CUZNAR; Miha GLAVAN
Publicado en: IEEE Mediterranean Electrotechnical Conference, IEEE MELECON 2022, Palermo, Italy, Edición June 14-16, 2022, 2022, Página(s) 1-6
Editor: IEEE
DOI: 10.1109/melecon53508.2022.9843127

Specific Data Sampling and Filtering Helps to Detect and Isolate Periodic Disturbances

Autores: Pavel Ettler; Ivan Puchr
Publicado en: 30th Mediterranean Conference on Control and Automation (MED 2022), Edición 28 June 2022 - 01 July 2022, 2022, Página(s) 755-760
Editor: IEEE
DOI: 10.1109/med54222.2022.9837226

Sensor Fusion Helps to Improve Strip Speed Measurement in Cold Rolling Mills

Autores: Pavel Ettler
Publicado en: IEEE International Conference On Mechatronics - ICM 2023, Loughborough, UK, 2023
Editor: IEEE Industrial Electronics Society

Digital twin of the electric arc furnace (Digitalni dvojček elektroobločne peči)

Autores: Vito Logar
Publicado en: Proceedings of the 31st International Electrotechnical and Computer Science Conference, 2022
Editor: Slovenian section of IEEE (Društvo Slovenska sekcija IEEE)

Self-adaptive data-driven models for process monitoring during ladle refining and continuous casting

Autores: Sudhanshu Kuthe; Björn Glaser; Rössler Roman; Izaskun Alonso Oña
Publicado en: 9th European Oxygen Steelmaking Conference (EOSC), Aachen, Germany, 2022
Editor: Steel Institute VDEh
DOI: 10.13140/rg.2.2.30094.84800

Evaluation of inclusion characteristics to monitor the efficiency of calcium-treatment in low-alloyed liquid steels

Autores: Sudhanshu Kuthe, Andrey Karasev, Björn Glaser, Rössler Roman
Publicado en: ESTAD2021 conference Program Book, Edición 30 August – 2 September 2021, 2021
Editor: 5th ESTAD (European Steel Technology and Application Days)
DOI: 10.13140/rg.2.2.10169.90721/1

The use of modelling and simulation in the digitalization of the electric arc furance process (Uporaba modeliranja in simulacije v digitalizaciji procesa elektroobločne peči)

Autores: Logar Vito
Publicado en: Proceedings of the 30th International Electrotechnical and Computer Science Conference ERK 2021, 2021, Página(s) 201-204
Editor: Slovenian section IEEE : Faculty of Electrical Engineering, University of Ljubljana

Combining FFT and pattern-based approach to isolate irregular periodic disturbances in rolling mills

Autores: Pavel Ettler
Publicado en: DPS2020-14th International Conference on Diagnostics of Processes and Systems, Edición 21 - 22 September 2020, 2020
Editor: University of Zielona Góra

Big data handling in process surveillance and quality control of secondary metallurgical processes

Autores: Christine Gruber, Birgit Bückner, Magdalena Schatzl, Maria Thumfart, Ramona Eßbichl, Roman Rössler
Publicado en: 9th Conference on modeling and simulation of metallurgical processes in steelmaking (Steelsim 2021), Edición 05-07 October 2021, 2021
Editor: ASMET, Austrian Society for Metallurgy and Materials
DOI: 10.13140/rg.2.2.36160.40961

Optimization of cold rolling process recipes based on historical data

Autores: Kristjan Cuznar
Publicado en: Proceedings of the 30th International Electrotechnical and Computer Science Conference ERK 2021, 2021, Página(s) 462-465
Editor: Slovenian section IEEE : Faculty of Electrical Engineering, University of Ljubljana

Digitalization and Software Support of the Electric Arc Furnace Process

Autores: Vito Logar, Simon Tomažič, Goran Andonovski, Igor Škrjanc
Publicado en: Proceedings of the 9th Conference on modeling and simulation of metallurgical processes in steelmaking - Steelsim 2021, Edición 05-07 October 2021, 2021, Página(s) 738-745
Editor: ASMET, Austrian Society for Metallurgy and Materials

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