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Agency: European Commission | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2015-ETN | Award Amount: 3.81M | Year: 2015

Mathematical, computational models are central in biomedical and biological systems engineering; models enable (i) mechanistically justifying experimental results via current knowledge and (ii) generating new testable hypotheses or novel intervention methods. SyMBioSys is a joint academic/industrial training initiative supporting the convergence of engineering, biological and computational sciences. The consortiums mutual goal is developing a new generation of innovative and entrepreneurial early-stage researchers (ESRs) to develop and exploit cutting-edge dynamic (kinetic) mathematical models for biomedical and biotechnological applications. SyMBioSys integrates: (i) six academic beneficiaries with a strong record in biomedical and biological systems engineering research, these include four universities and two research centres; (ii) four industrial beneficiaries including key players in developing simulation software for process systems engineering, metabolic engineering and industrial biotechnology; (iii) three partner organisations from pharmaceutical, biotechnological and entrepreneurial sectors. SyMBioSys is committed to supporting the establishment of a Biological Systems Engineering research community by stimulating programme coordination via joint activities. The main objectives of this initiative are: * Developing new algorithms and methods for reverse engineering and identifying dynamic models of biosystems and bioprocesses * Developing new model-based optimization algorithms for exploiting dynamic models of biological systems (e.g. predicting behavior in biological networks, identifying design principles and selecting optimal treatment intervention) * Developing software tools, implementing the preceding novel algorithms, using state-of-the-art software engineering practices to ensure usability in biological systems engineering research and practice * Applying the new algorithms and software tools to biomedical and biological test cases.

Agency: European Commission | Branch: H2020 | Program: RIA | Phase: SPIRE-02-2016 | Award Amount: 6.54M | Year: 2016

The goal of CoPro is to develop and to demonstrate methods and tools for process monitoring and optimal dynamic planning, scheduling and control of plants, industrial sites and clusters under dynamic market conditions. CoPro will provide decision support to operators and managers and develop closed-loop solutions to achieve an optimally energy and resource efficient production. In most plants of the process industries, the energy and resource efficiency of the production depends critically on discrete decisions on the use of equipment, shutdowns, product changeovers and cleaning or regeneration of equipment. CoPro will consider these discrete decisions in plant-wide dynamic optimization and develop integrated scheduling and control solutions. Advanced online data analytics will be developed for plant health and product quality monitoring. The detection of anomalies will trigger fast re-scheduling and re-optimization. CoPro will demonstrate advanced plant-wide and site-wide coordination and control in five typical use cases that cover a wide range of sectors of the process industries, and the whole value chain: - Petrochemical production site - Base chemicals and polymer production site - Recycling system in cellulose production - Consumer product formulation and packaging plant - Food processing plant In addition,CoPro will develop methods for the coordination of plants in industrial parks that belong to different companies, thus providing a basis for future industrial symbiosis. CoPro pays special attention to the role of operators and managers in plant-wide control solutions and to the deployment of advanced solutions in industrial sites with a heterogeneous IT environment. As the effort required for the development and maintenance of accurate plant models is the bottleneck for the development and long-term operation of advanced control and scheduling solutions, CoPro will develop methods for efficient modelling and for model quality monitoring and model adaption

Agency: European Commission | Branch: H2020 | Program: RIA | Phase: LCE-24-2016 | Award Amount: 3.21M | Year: 2016

ROLINCAP will search, identify and test novel phase-change solvents, including aqueous and non-aqueous options, as well as phase-change packed bed and Rotating Packed Bed processes for post-combustion CO2 capture. These are high-potential technologies, still in their infancy, with initial evidence pointing to regeneration energy requirements below 2.0 GJ/ton CO2 and considerable reduction of the equipment size, several times compared to conventional processes . These goals will be approached through a holistic decision making framework consisting of methods for modeling and design that have the potential for real breakthroughs in CO2 capture research. The tools proposed in ROLINCAP will cover a vast space of solvent and process options going far beyond the capabilities of existing simulators. ROLINCAP follows a radically new path by proposing one predictive modelling framework, in the form of the SAFT- equation of state, for both physical and chemical equilibrium, for a wide range of phase behaviours and of molecular structures. The envisaged thermodynamic model will be used in optimization-based Computer-aided Molecular Design of phase-change solvents in order to identify options beyond the very few previously identified phase-change solvents. Advanced process design approaches will be used for the development of highly intensified Rotating Packed Bed processes. Phase-change solvents will be considered with respect to their economic and operability RPB process characteristics. The sustainability of both the new solvents and the packed-bed and RPB processes will be investigated considering holistic Life Cycle Assessment analysis and Safety Health and Environmental Hazard assessment. Selected phase-change solvents, new RPB column concepts and packing materials will be tested at TRL 4 and 5 pilot plants. Software in the form of a new SAFT- equation of state will be tested at TRL 5 in the gPROMS process simulator.

Agency: European Commission | Branch: FP7 | Program: CP | Phase: ENERGY.2013.5.1.2 | Award Amount: 5.71M | Year: 2013

Carbon capture and storage (CCS) is one of the technological solutions to decarbonize the energy market while providing secure energy supply. So far, the cost of CCS is dominated by the CO2 capture, reason why new capture techniques should be developed. Adsorption techniques have already been evaluated for CO2 capture. So far, the main drawbacks of this technique are the energetic demand to regenerate the adsorbent and obtain high purity CO2. However, the utilization of commercially available materials was employed in the former evaluations. New materials with targeted properties to capture CO2 from flue gases can improve the performance of adsorption processes significantly. The vision of MATESA is to develop an innovative post-combustion capture termed as Electric Swing Adsorption (ESA). The utilization of hybrid CO2 honeycomb monoliths with high-loading CO2 materials (zeolites and MOFs) will be targeted. Classical ESA regeneration is done by passing electricity through the adsorbent, releasing adsorbed CO2 that can be recovered at high purity. A game-changing innovation in MATESA is the development of a regeneration protocol where electricity is only used to increase the purity of CO2 in the column and further regeneration is done using available low-grade heat. The predicted energy savings of the developed process may transform this CO2 capture process in a key component to make CCS commercially feasible in fossil fuel power plants going into operation after 2020. In order to realize a proof of concept of the proposed process, a strong component of the project will deal with the development of a hybrid material that is able to selectively adsorb CO2, conduct electricity, result in a low pressure drop and have reduced environmental impact. The development of such a material is important for MATESA and will also have a significant impact to increase the energy efficiency of pre-combustion CO2 capture and other energy intensive gas separations.

Agency: European Commission | Branch: H2020 | Program: RIA | Phase: LCE-15-2015 | Award Amount: 20.77M | Year: 2016

LEILAC, Low Emissions Intensity Lime And Cement, will successfully pilot a breakthrough technology that will enable both Europes cement and lime industries to reduce their emissions dramatically while retaining, or even increasing, international competitiveness. LEILAC will develop, build and operate a 240 tonne per day pilot plant demonstrating Direct Separation calcining technology which will capture over 95% of the process CO2 emissions (which is 60 % of total CO2 emissions) from both industries without significant energy or capital penalty. Direct Separation technology uses indirect heating in which the process CO2 and furnace combustion gases do not mix, resulting in the simple capture of high quality CO2. This innovation requires minimal changes to the conventional processes for cement, replacing the calciner in the Preheater-Calciner Tower. For lime there is no product contamination from the combustion gas. The technology can be used with alternative fuels and other capture technologies to achieve negative CO2 emissions. The project will also enable research into novel building materials with a reduced CO2 footprint, as well the upgrade of low value limestone fines and dust to high value lime applications. The high potential of the project is complemented by high deliverability. The requested grant will secure 8.8m of in-kind funding and support from the LEILAC consortium members, which include world leading engineering, cement, lime and R&D organisations. To accelerate further development, LEILAC will deliver a techno-economic roadmap, and comprehensive knowledge sharing activities including a visitor centre at the pilot site near Brussels. In order to reach the required 80% emissions reductions by 2050, CCS will need to be applied to 85% of European clinker production, and LEILAC is uniquely placed to allow Europe to achieve these targets in a timely, effective and efficient manner.

Agency: GTR | Branch: Innovate UK | Program: | Phase: Collaborative Research & Development | Award Amount: 580.34K | Year: 2014

This project brings together experts in drug development, product formulation, process design, systems modelling and manufacture to create a completely new approach to the design and manufacture of formulated drug products, which involves the integration of qualitative tools for process understanding with a range of in-silico models which describe and predict processing and product performance. It is anticipated that successful outcomes of digital design of drug formulations as envisaged in this proposal via the creation of “Design Space Explorer” will provide unparalleled improvements in reliability, quality and manufacturing processes of pharmaceutical products leading to greater trust by regulatory agencies and by society. Furthermore it is anticipated that a successful outcome to the proposed project has potential to significantly decrease the costs and times associated with the development of new medicines whilst also reducing, refining and and at times removing the need for some clinical studies in patients and healthy volunteers.

Agency: GTR | Branch: Innovate UK | Program: | Phase: Feasibility Study | Award Amount: 104.92K | Year: 2015

Maximising the exploitation of the UK Continental Shelf’s (UKCS’s) remaining oil & gas reserves is critical to UK tax revenues, security of energy supply, balance of payments and competiveness of manufacturing industries. This feasibility study proposal is for pre-commercial development of an Advanced Real-time Production Optimisation (ARPO) tool to enable UKCS Oil & Gas operating companies to optimise production in integrated oil & gas production assets in real time in order to maximise revenue and increase extraction efficiency. It uses well-to-facilities mathematical models of the production system combined with operational data within a rigorous mathematical optimisation framework to determine, for example, which wells to deploy, optimal gas lift flowrates for each operating well and other operational settings. The unique technology addresses well- known deficiencies of currently-deployed tools, draws on extensive existing PSE technology and experience, transfers and adapts well-established existing technology and expertise from other sectors, and involves engagement of key stakeholders to develop requirements and validate the pre-commercial development.

Agency: GTR | Branch: Innovate UK | Program: | Phase: Collaborative Research & Development | Award Amount: 299.80K | Year: 2015

Oil refining is a trillion dollar industry. However, refineries are under increasing pressure from global competition, overcapacity and regulation and these are reflected in tight margins. Opportunities to improve refining margins include improvement of energy efficiency and yields of crude oil to valuable products. This project will develop two key innovations embedded in technology to improve refining margins: 1. More accurate, model-based approaches for dynamic state estimation: these will allow refiners to understand in real time the properties of different stream and the crude they are processing, allowing them to improve yields. 2. Dynamic optimisation of the CDU system. The CDU system is at the heart of the refinery and drives its economics. Improved operation can reduce the amount of energy required to process crude, convert more of the crude to valuable products and reduce the time required to switch between crudes.

Agency: GTR | Branch: Innovate UK | Program: | Phase: Feasibility Study | Award Amount: 97.51K | Year: 2015

The exploitation of shale gas is likely to be critical to UK security of energy supply, balance of payments and competiveness of the manufacturing industries in the future. However there is strong public opposition, largely because of environmental concerns focused on public perception of large quantities of contaminated water being produced. For this reason, safe and effective design, operation and monitoring of fracturing and flowback water treatment processes is crucial. Model-based engineering is a key technology to achieve these, but currently no suitable comprehensive set of tools exists. This feasibility study proposal is for pre-commercial development of a high-fidelity modelling toolbox for optimal design and operation of shale gas water treatment facilities based on transferring, adapting and extending well-established existing technology and expertise from other sectors such as chemicals & petrochemicals and conventional wastewater treatment. It also involves engagement of key stakeholders to explore the requirements and potential applications for subsequent commercial development of product and services based on the pre-commercil development.

Enterprise Systems | Date: 2014-03-14

A system for analyzing an engine of a vehicle may comprise a computer including a computer processor, a sensor connected to a portion of the vehicle and being configured to provide an engine signature to the computer, a simulator module configured to utilize the computer processor to generate simulated signature features associated with a simulated vehicle having prescribed defects, and a self-learning module configured to utilize the computer processor to learn associations between the simulated signature and prescribed defects. The computer processor may be configured to compare the engine signature with the associations of the self-learning module to produce a probability indicator that the engine has the prescribed defect at a specified intensity associated with a diagnosis of the engine.

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