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All companies of the European process industry are facing the same challenges: on the one hand product quality has to be improved and at the same time production costs have to be decreased to be competitive on the world market. On the other hand the resource and energy efficiency of products and processes has to be improved to lower their ecological footprint. This is independent of the industrial sector, it is true for the cement industry as well as for the food or copper industry.That means, these are cross-sectorial challenges!
The development of new production technologies could be one way to tackle this challenge. Examples are modularised processes in the chemical industries, new ways to reduce iron ore to liquid iron in steel industry or increasing the yield during refining of silicon industry. In reality, these are long term perspectives. However, the most promising medium term solution is the efficiency increase of technological processes in the process industry by improved and integrated process control solutions.
In many aspects batch processes are superior to continuous ones. Therefore it is worthwhile to take advantage of recent progress in sensor technologies, modelling and automation to develop a new paradigm for the design and conduction of batch processes. The objective of the project is to maximise efficiency of batch processes regarding quality, energy, raw materials, costs.
The RECOBA project aims to improve product quality, efficiency and flexibility of and in batch processes.
Ten cooperation partners will make use of an online, model predictive control of complex batch processes for the production of emulsion polymers, steel, and silicon metal through the application of new sensor technologies, process models and automation tools. The consortium will focus on three different material systems to demonstrate the cross-sectorial applicability of developed sensors, optimization and control methods, with the goal of optimizing product quality, energy consumption, raw materials utilization and production costs of the considered processes.
Stakeholders of the project who will carry RECOBA's results forward into further development and commercialisation are:
Effective and efficient management of the project (WP1) is critical to the success of a coordination action as it will involve not only the partners, but also external stakeholders during the dissemination/exploitation and innovation management actions.
Determination of the Specification (WP2): Batch processes and their relevant sub-processes and systems will be investigated. Additionally, the specific demands for a closed loop process control will be fully specified. This shall enable an efficient and well-aimed development of sensors and models.
The project term is mainly parted in two working phases. The first phase is method development (WP3 - WP5), around which three research fields are focussing on sensors, models and process control & optimization. The second phase is an industrial validation phase (WP6 – WP8), in which the new real-time process control systems will be evaluated in the very different standard batch processes of polymer, steel and silicon alloy production.
A performance evaluation of RECOBA will be realised at the end of the project (WP9).
The dissemination and exploitation of the research results (WP10) will be in parallel with the method development and industrial validation phases.
The RECOBA consortium represents a selection of batch processes operating industries and partners across the value chain of batch process control, among them 3 global players from the polymer industry (BASF SE, Germany), the steel industry (Thyssen Krupp Steel Europe AG, Germany) and the silicon metal industry (ELKEM AS Technology, Norway). They provide their processes and infrastructure for the validations in different industrial environment.
Our academic partners (RWTH Aachen University, Germany, University of Cambridge, United Kingdom, University of Chemistry and Technology Prague, Czech republic, University of the Basque Country UPV/EHU, Spain) possess leading scientific expertise covering material science, mathematical foundations of modelling, chemical reactions, computational and process systems engineering to provide purposive research strategies.
The industrial development partners, two SMEs (Cybernetica AS, Norway, MINKON Sp. z o.o., Poland) and one RTO (VDEh-Betriebsforschungsinstitut GmbH, Germany), provide applied research, sector knowledge and large-scale implementation experience for a wide range of measurement techniques, control systems and process automation.
Key deliverables will be:
new & innovative solutions for the measurement of different types of quality aspects
new models to realise integrated process control of batch processes
suitable online parameter adaptation technologies to keep these models valid
control modules to realise concepts for real-time, model based & closed loop process control, which are easily adaptable to existing batch processes in various industrial sectors
business models to approach relevant industrial sectors for a future market entry
30 June 2017
30 April 2017
31 December 2016
31 August 2016
30 June 2016
30 April 2016
31 March 2016
31 December 2015
20 April 2015
25 March 2015
Utilizing the Discrete Element Method for the Modeling of Viscosity in Concentrated Suspensions
Authors: Martin Kroupa, Michal Vonka, Miroslav Soos, Juraj Kosek; VSCHT
Journal: Langmuir, 2016
Room temperature sputtering of inclined c-axis ZnO for shear mode solidly mounted resonators
Authors: G. Rughoobur, M. DeMiguel-Ramos, T. Mirea, M. Clement, J. Olivares, B. Díaz-Dúran, J. Sangrador,
W. I. Milne, E. Iborra, A. J. Flewitt; UCAM
Journal: Applied Physics Letters, Jan. 2016
A new approach for mathematical modelling of the dynamic development of particle morphology
Authors: Shaghayegh Hamzehlou, Jose Ramon Leiza, José M. Asua; POLYMAT
Journal: Chemical Engineering Journal, 2016
Press release, March 23, 2015
The project is coordinated by:
For further information, please contact:
Project Coordinator: email@example.com
Exploitation Manager: firstname.lastname@example.org
Jose M. Asua