Monthly Archive 26th April 2018

ByDr. Jan Polzer



Cyber-Physical Production Optimization Systems for Long Production Factories

Cyber-POS project abstract and objectives

Production technology in steel industry has reached a level that significant improvements can only be reached by through process optimization strategies instead of improving each process step separately. Therefore the connection of suitable technological models to describe process and product behavior, methods to find solutions for typical multi-criterial decisions and a strong communication between involved plants becomes mandatory. Cyber-POS will develop a virtual simulation platform for the design of cyber-physical production optimization systems (CPPS) for long production facilities with special emphasis to thermal evolution and related material quality, leading to reduced energy consumption, shortened production time and improved product quality.

The main objectives within this project are:

  • Optimization of throughput and reduction of energy consumption for the production of complex profiles in Mannstaedt’s hot processing line and
  • Optimization of material quality and properties for rail mills at ArcelorMittal España.

This is achieved by applying the developed software and methods for the specific use cases. This implies the following sub-objectives:

  • Virtual simulation platform for the design of cyber-physical production optimization systems (CPPS) for long production facilities; with special emphasis to thermal the evolution and related material quality, leading to reduced energy consumption, shortened production time and improved product quality;
  • Merging of process models (thermal, rolling, transport), material-quality models, logistics/scheduling models and communication models (computers, software, networks);
  • Strategies and methods for cooperative production optimization, enabling fast dynamic and flexible reaction on quality variations, critical states, measurement errors, and changes in set-points, production routes, process disturbances or interruptions;
  • New and comprehensive, model-based (simulation) software for design of CPPS for long product factories, with a cyber-physical library for “drag-and-drop” implementation.

The project started at July 1st 2016 and ends at December 31th 2019. Involved partners in the research are:

VDEH-Betriebsforschungsinsitut GmbH  
Arcelor Mittal España  
Fundación ITMA  
Mannstaedt GmbH
Scuola Superiore Sant’Anna di Studi Universitari e di Perfezionamento  

Cyber-POS project expected industrial impacts

The research has received funding from the European Union’s Research fund for Coal and Steel (RFCS) under grant agreement No. 709669.

The main motivation for introducing the methods of cyber-physical production optimization is essentially to preserve the economic performance and safety level in spite of faults and process changes that may occur over time. The CPS platform to be developed can be regarded as an assistance system that will support plant personnel/operator decisions, and thus can contribute to the improvement of working conditions. All involved processes can actively communicate with each other, know their field of activity and production conditions. The optimizations made are also more tailored to the human workforce.

Higher maintainability, reliability and efficiency of long production factories through cyber-physical production optimization will lead to improved product quality, reduced maintenance costs and decreased material and energy consumption. This will have a positive impact on preservation of natural resources, energy and environment. Needless to say, reducing energy consumption leads to reduced CO2 emissions.

At the two involved plants of ArcelorMittal España and Mannstaedt, the developed concept will be installed as assistance system and tested in the process route reheating, hot rolling and cooling. This leads to increased flexibility of process chain, higher productivity, better disturbance management and energy savings.

ByRoland Pietruck


Real Time Monitoring of coal composition in closed systems for fast process control

RemoCoal project abstract

Nowadays for competitive hot metal production at a Blast furnace it is necessary to realize a high pulverised coal (PC) injection rate at a minimised coke rate. But actually there is a lack of real time analytical technologies to obtain reliable short time information of the actual composition of pulverized coal blend which is injected into the blast furnace (BF). A real time analysis of the pulverised coal blend opens up the opportunity to detect unexpected or prompt deviation in coal blend composition. It enables to run an optimized total BF fuel rate, a reduction of fuel cost for hot metal production and subsequently decreasing CO2 emissions.

Within the project the Pulsed Fast and Thermal Neutron Analysis (PFTNA) technology designed as borehole logging tool will be modified and applied in a closed silo of a pulverized coal injection (PCI) system. BF trials for real-time analysis of coal composition to adjust the coal injection rate near time will be performed.

The PFTNA-technique takes advantage of a switchable pulsed neutron generator for emission of fast and thermal neutrons and a gamma ray detector which record the characteristic gamma photons generated by interaction of the emitted neutrons with the nuclei of the surrounding coal material. It delivers characteristic spectra as basis for  determination of the PC composition.


Additional the real time spectra will be processed by fingerprint analysis software (pattern recognition). The analysis is based on statistical data evaluation of the gamma spectra and delivers the operator principle parameter of the PC for Blast furnace optimization.

The involved Partners in the research project are:

VDEh – Betriebsforschungsinstitut GmbH  
Malvern Panalytical GmbH  
thyssenkrupp Steel Europe AG  

This project receives funding from the Research Fund for Coal and Steel under grant agreement No. 754 200

Remocoal objectives

The main objective of this project is to demonstrate the high benefit of the real time analysis of coal composition for industrial application in better adjusting/controlling the pulverised coal injection rate and improve the production process.

The implementation of the PFTNA technology and the finger print analysis software enables to:

  • homogenize process fluctuations and improve process stability
  • run optimised pulverized coal injection rate and therefore to lower the safety coke rate of BF (improved forward control)
  • carry out a trend analysis by the operator and adjust the coal blending
  • lower operational costs
  • decrease CO2 emissions by reduced total fuel rate and improved process control.

The new technology shall be demonstrated at the pulverized coal injection plant of a BF at tk SE. Finally, a concept will be set up for the implementation of the PFTNA technology and the real-time data evaluation at European blast furnaces.

Remocoal research approach

The development of the online monitoring systems in RemoCoal will be achieved in four major steps. An overview of the concept is illustrated in the following figure:

  1. The adaption of the neutron probe and the software as well as inhouse calibration: The PFTNA probe will be adapted for the implementation in closed silos of an injection plant of a tk SE blast furnaces. The adaption comprises the optimisation on the signal detection with respect to the construction material and probe design via simulation. Also a safety concept for applying the neutron probe will be set up. The finger print recognition software will be modified as support tool for the blast furnace operator and implemented. After adaption a primary inhouse calibration of the neutron probe using pulverised coal analysis as reference will be carried out.
  2. Calibration rig in pilot scale: To obtain a reliable calibration of the neutron probe in industrial scale a calibration rig in pilot scale will be engineered and set up. The pre calibrated neutron probe will be used for calibration trials with defined coal and coal blends to obtain an industrial calibrated neutron probe.
  3. Application at Industrial scale: The developed PFTNA probe will be installed and applied in a closed silo of the tk SE pulverized coal injection plant at a blast furnace. The results will be compared to standard analysis. The finger print recognition software will be proved by the operator to an optimized utilisation of PC at the BF. On the basis of the gained experiences and the results a concept for the implementation of the PFTNA technology and the real-time data evaluation at European blast furnaces will be set up.