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Integrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock

Periodic Reporting for period 2 - DISIRE (Integrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock)

Reporting period: 2016-07-01 to 2017-12-31

DISIRE was inspired by the needs of multiple industrial sectors, including the non-ferrous, ferrous, chemical and steel sectors, aiming to evolve the existing industrial processes through an overall resource and energy efficiency paradigm, by developing miniaturized PAT technologies capable of being inserted into flows of raw materials. The “Intelligent Raw materials” concept allows better characterization of the material, optimization of the processing plants, increase of the process intensification and energy efficiency in Chemical, Steel, and Mineral processing, and also improve the industrial combustion processes.

DISIRE developed and evaluated a novel framework combining existing sensory readings, along with inline sensors that transmit data in near real time to a cloud infrastructure, which can process the data and create online PAT for control reconfiguration. DISIRE advanced the current state of the art by introducing architectures that can reduce the consumed energy, improve the quality of the products and reduce the impact on the environment, by reaching the following technological objectives:

O1 Develop miniaturized PAT technologies
O2 Introduce Multi-objective In line Sensor Technology
O5 Improve the efficiency in copper production
O6 Improve the efficiency in ferrous mineral processing
O7 Demonstrate the use of DISIRE IPC in a steel plant
O8 Improve the combustion processes
O9 Close the gap between research and industry
The work performed in DISIRE with respect to the corresponding WPs is as follows:

WP1-Application Scenarios, Impact Goals and Benchmarking was the base for all developments in DISIRE. It contained initial and end-user specifications for the sensing, controlling and data analyzing specifications the technological WP2-4 should follow for the targeted demonstration processes WP5-8.

WP2-Process Modeling and Control developed and validated new modeling and control approaches for the process industry, integrating and exploiting the data obtained from the cloud based PAT and the inline sensing capabilities, aiming to improve the overall control performance, evaluated at the WBF, the cracking furnace and conveyor belt systems.

WP3-Sensor and Electronics developed online PAT sensor and platform technology for process tracing and measurement in harsh environments. RFID tags were developed for tracing the iron ore at LKAB and following copper transportation at the KGHM mine. For the EBF and the WBF, inline modules were developed that can be inserted in the hot processes. For the batch sensor case a fiber optic demonstrator was developed in DCI’s plant to measure the temperature of the LPG.

WP4-Data Mining combined inline sensory data and existing PAT measurements. WP4 designed and evaluated generic data model structures that can be adapted to any kind of process industry, while a Statistical Engine module was developed for efficient utilization of data in different scenarios, while creating an architecture for Big data and cloud implementations.

WP5-Non-Ferrous Mineral Processing focused on the energy efficiency of the Belt Conveyor system. Based on electricity consumption and material weight data for the copper mines of KGHM, dashboards were developed on the cloud infrastructure enabling the analysis of trends and efficiency indicators. WP5 also developed PAT and data mining applications for underground ore transportation. A general layout of PAT workflow was introduced, followed by successful field trials for the ore flow tracking.

WP6-Ferrous Mineral Processing performed experiments on the cold side for segregation in a lab-scale and a real sized silo. The surrounding environment of the product bins turned out to be very challenging for the electronic equipment. Tracers were dropped onto train wagons after the pelletizing plant in Malmberget. All the large tracers survived the severe pressure and all collected data were retrieved. In the hot side, WP6 made pilot scale testings on LKAB's EBF, where several PAT sensors were dropped into the furnace but the radio environment was very challenging and must be investigated further. WP6 also evaluated inline PAT sensors in a pelletizing plant at Kiruna KK4. WP6 demonstrated that in-situ sensors and readers can operate and survive in extreme environments.

WP7-Steel demonstrated successfully the full DISIRE architecture based on inline sensing, online PAT, cloud streaming, big data analytics and IPC reconfiguration on the WBF. 4 large industrial trials were conducted, 1 at the EBF and 3 at the WBF. The results were promising but more work is needed before the developed framework can step up from today’s TRL 6.

WP8-Combustion process focused on the increase of efficiency of combustion and the prediction and reduction of NOx pollutant emission in cracking furnaces. The main goal was to develop an image-based flame diagnosis tool, and a full scale demonstrator for the flame diagnosis tool and the fiber optic temperature measurements was produced.

WP9-Dissemination and innovation. DISIRE was selected as a success story twice at the impact annual meetings organized by SPIRE. The consortium published over 50 articles and attended over 20 conferences. A Technology Exploitation Strategy was created, while WP9 delivered “Business Models Generation Canvas”, “Lean Canvas”, “Value Proposition Design” methodologies to ensure the optimum exploitation of generated business opportunities. Also, an Interactive Innovation Toolkit and an Innovation Management Office were created.
Mineral Processing
New knowledge about the heating products and their logistics was created, while inline sensing created the potential to: reduce the environmental impact, increase the energy efficiency and throughput, reduce also waste products. E.g. a 2% decrease in energy consumption could save 50K to 100K Euros per pelletizing plant. Understanding how a large number of pellets are spread in the transport chain, was gained, and it is expected that after a full installation of DISIRE, if LKAB meets the potential of a reduction of separate handling by 50% this would mean around 250K-350K euros/year per pelletizing plant savings.

Steel Processing
DISIRE offers an overall improvement that will create a reduction of 3 kg of C from fossil fuels per ton hot metal produced due to: a) improved gas efficiency by 1% due to improved burden distribution control, b) improved process stability due to improved moisture control and c) improved process control due to early information of in-furnace temperature distribution. The results from the WBF will promote the adaptation of the DISIRE technology in this sector.

Industrial Combustion Process
DISIRE created novel and more efficient sensors for the combustion industry. In DCI North facilities, the consumption of the fuel gas reaches up to 250K Ton/year and thus small improvements with the DISIRE sensing will result into 1% improvement of the cracking furnaces, resulting in 2K Ton/year savings.

Logistics and Transportation of raw materials
The activities in this sector was driven by the identified lack of a proper ore tracing technology, that can be directly applied in the KGHM mines. The DISIRE adoption will reduce the machines' utilization and reduce energy consumption. For the Belt Conveyor system, after the implementation of the DISIRE energy efficient solutions (per annum) will have an overall potential of 0.279 mln of Euros/BC branch.