Community Research and Development Information Service - CORDIS

H2020

RECOBA Report Summary

Project ID: 636820
Funded under: H2020-EU.2.1.5.3.

Periodic Reporting for period 1 - RECOBA (Cross-sectorial real-time sensing, advanced control and optimisation of batch processes saving energy and raw materials)

Reporting period: 2015-01-01 to 2016-06-30

Summary of the context and overall objectives of the project

The RECOBA project is a cooperation project of ten European partners working towards developing and deploying robust real-time model predictive control and sensing methodologies. Through their application the energy and resource efficiencies of the considered (semi-)batch processes will be increased and a consistent final product quality will be achieved. The efficiency improvements will enhance the competitiveness of a significant portion of the European batch process industry.

In the RECOBA project the considered example processes are (i) emulsion polymerization of vinyl monomers where the products are used, e.g., in painting applications, (ii) liquid steelmaking and (iii) silicon refining. The partners focus on three different material systems to demonstrate the cross-sectorial applicability of developed sensors, optimization and control methods. While the goals are similar for all three mentioned processes (higher efficiency) the challenges are very different as the physical process conditions differ significantly as well as product properties and utilization. The challenges and objectives are schematically summarized in Fig. 1. The proof of beneficial application of control methods provided by RECOBA’s industrial partners should encourage other European process industries to deploy common advanced sensing and control techniques also in their applications and processes to improve their efficiency.

Let us here introduce particular goals and challenges of the considered processes in detail.

Polymerization process
Polymerization reactions are nowadays operated based on a repetition of a fixed schedule defined in a recipe. Impurities in the reaction mixture or fouling on the reactor wall are common disturbances during the batch run. In turn, the real process conditions can differ from the ones prescribed by the recipe. This can thus lead to variations in a final product quality. The goal of the RECOBA project is to replace the current fixed recipe control by model predictive control (MPC). Such MPC controllers can adjust the process control variables (e.g., temperature, reactant feed rates, etc.) in a real time in order to follow the optimal process trajectory. Therefore, the desired product properties are maintained while minimal energy consumption or batch time in presence of disturbances are achieved. Due to good reaction control the use of resources, which have often varying quality, e.g., bio-based resources, can become realistic for production of products with constant quality. These quality parameters include copolymer composition, molecular architecture of polymer chains and morphology of polymer latex particles. To enable the use of the MPC technology for the polymerization case, it is necessary to develop precise process and morphology models. Together with newly developed sensors, it is possible to gain information about the current states of the reaction mixture and apply suitable control actions. The polymerization process model is being developed by the University of Chemistry and Technology Prague (CZ) and the latex particle morphology model is being developed by the University of the Basque Country (ES). Development and testing of sensors and sensor data processing are carried out in close cooperation between the University of Cambridge (UK), University of the Basque Country and RWTH Aachen University (DE). Process operations optimization and online model predictive control solutions are being implemented by RWTH Aachen University and Cybernetica (NO). The developed concepts will be tested in the pilot plant facilities of BASF SE (DE).

Steelmaking process
The process of steelmaking is characterised by a large throughput of resources and energy. It is performed along a chain of different batch processes performed consisting of several aggregates for heating and metallurgical refining of the liquid steel melt. The objective of the production process is to treat batches of about 260 t of liquid steel wit

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In summary, the project has progressed according to project plan with meeting of all milestones.

Emulsion polymerization process
Regarding the polymerization process significant achievements include:
• Process model of emulsion copolymerization including Monte Carlo simulation for detailed description of polymer chain architecture has been developed and validated with experimental data.
• Model for simulation of latex particle morphology evolution has been developed. Large sets of experimental data for the estimation of morphology model parameters are being collected.
• Different types of the low-cost acoustic sensors for latex particle characterization have been manufactured and tested. The evaluation of sensor data is still ongoing.
• Flow cell for online TEM microscopy (transmission electron microscopy) for monitoring of latex particle morphology has been developed, manufactured and is recently tested. The potential of the method for online monitoring of latex particle morphology will be evaluated based on future experiments.
• Raman spectroscopy has been tested for monitoring of concentrations of considered monomers and latex particle sizes in the reaction mixture.
• The developed process and morphology models are being introduced into the optimization and control software enabling model predictive process control.

The experimental focus in the first project period was mainly on the preparation and analysis of samples which went hand in hand with the development of sensors for process monitoring. The researchers have synthesized samples with different particle morphologies, cf. Fig. 2, to enable testing of various sensing concepts which seem to be promising for online characterization. Acoustic and online transmission electron microscopy sensors were tested on their responses regarding the latex particle morphology. Although the TEM technique provides directly visual results, their automatic evaluation is challenging due to low contrast between soft and hard polymer phases. As the first TEM results are promising the development of the online TEM method will continue also in the second project period. In case of acoustic sensors we have proven that there is a difference in sensor responses on samples with different morphologies, nevertheless the work on processing of sensor signal into morphology information is not finished yet and will continue as well. Further, Raman spectroscopy was tested for online determination of level of residual monomer concentrations in the reaction mixture. The challenge, which still remains, is in the determination of the very low monomer concentrations in case of the so called starved feed polymerization. The results and collected experience regarding sensors for the polymerization process case are described in the public deliverables which can be found on the official RECOBA website (deliverables 3.3 and 3.4)

Modeling efforts in the first project period were focused on (i) the development of accurate process model coupled with Monte Carlo simulation describing the evolution of monomer and polymer concentrations and polymer molecular weight distribution and on (ii) development of polymer morphology evolution model. While the process model was validated with the experimental data, the collection of experimental data necessary for parameter estimation and model validation is in the case of the morphology model still ongoing. Both models meet computational requirements for the online use. They are being implemented into the optimization and control software to enable the process intensification and control within the next project period. Further, within the project, a model involving particle interactions and their effect on latex viscosity or coagulum formation is being developed. The model results show good agreement with experimentally obtained data and brings thus insight into polymer latex flow phenomena which is crucial for prevention of fouling or coagulum formation.

Liqu

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

At the project end the partners will demonstrate the utilization of the model predictive control methodology in production of emulsion polymers, steel and silicon, respectively. To enable this, partners will work on development and utilization of:
(i) innovative process models
a. of emulsion polymerization including reaction kinetics and Monte Carlo simulation for description of polymer’s molecular architecture,
b. model for description of latex particle morphology development,
c. detailed model of the chain of batch processes for melt temperature in liquid steelmaking, including reaction kinetics and important thermodynamic phenomena,
d. detailed model of silicon refining process including reaction kinetics and important thermodynamic phenomena,
(ii) and sensors and data evaluation methods
a. for monitoring of latex particle morphology (flow TEM, acoustic sensors),
b. for monitoring of reactant concentrations in the reaction mixture,
c. temperature monitoring sensors applicable at high temperatures and harsh environment (fiber optical sensor, coverage efficiency sensor, fiber Bragg sensor).
As the project progressed excellently the involved partners are already working on the demonstration of the developed concepts and sensors in the plant environment.

The usage of MPC together with the state of the art sensors will enhance the energy-, resource- and cost-efficiency of the respective semi-batch processes. To quantify the project results the industrial partners will compare standard process control methods with the new ones developed and implemented within RECOBA and discuss environmental, economic and social impacts of MPC usage for production. It has to be noted that the intention of the project is not just to bring financial benefit to the technology end users (BASF, ThyssenKrupp, Elkem) but also to suppliers of software and modeling tools and sensor developers and manufacturers. From the perspective of SMEs involved in the project it is an opportunity to get experienced in the new application fields and exploit their technologies to broader customer portfolio. With the introduction of new control concepts and sensor technology new businesses along the value chain will arise. The complexity of the control concept will also lead to the need for training, maintenance as well as performance monitoring and optimization services. This business can be generated by the involved SME partners, but also by the academic partners with regard to training.

As the RECOBA’s goal is to significantly improve efficiency of batch processes in various industries the competitiveness especially of the energy-intensive European process industry will be enhanced in short to medium term. In the medium to long term some of the new control and sensor technologies will also be transferred to continuous processes, can be implemented in modularized production concepts and facilitate the development and implementation for advanced & improved processes which would further strengthen the European process industry. Higher competitiveness of the European industry will preserve existing jobs and will create new highly-skilled jobs as a result of the innovation process.

In case the MPC technology will be spread into all intended areas significant savings of energy and raw material can be achieved. The advanced sensing and control technology will also improve safety of the considered processes. The overview about the intended project impact is visualized in Fig. 3.

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