ABB is a multinational corporation headquartered in Zurich, Switzerland, operating mainly in robotics and the power and automation technology areas. It ranked 158th in the Forbes Ranking .ABB is one of the largest engineering companies as well as one of the largest conglomerates in the world. ABB has operations in around 100 countries, with approximately 150,000 employees in November 2013, and reported global revenue of $40 billion for 2011.ABB is traded on the SIX Swiss Exchange in Zürich and the Stockholm Stock Exchange in Sweden since 1999, the New York Stock Exchange in the United States since 2001, September 2005 on London Stock Exchange and in November 2005 on the Frankfurt Stock Exchange. Wikipedia.
Abb | Date: 2016-11-08
The subject matter of the invention is a roller mill comprising two rollers which are arranged in parallel, are pressed one against the other and rotate in opposite directions, wherein one of the rollers can be displaced orthogonally with respect to the axial direction of this roller, and two drives, which drives are each assigned to one of the two rollers, and each have an electric motor, a master of the electric motors predefines for the electric motors a setpoint value for the rotational speed of the torque as a reference, and a reference of a follower electric motor of the electric motors comprises the actual value of the torque or of the rotational speed of the master electric motor multiplied by a load distribution factor.
Agency: Cordis | Branch: H2020 | Program: SGA-RIA | Phase: FETFLAGSHIP | Award Amount: 89.00M | Year: 2016
This project is the second in the series of EC-financed parts of the Graphene Flagship. The Graphene Flagship is a 10 year research and innovation endeavour with a total project cost of 1,000,000,000 euros, funded jointly by the European Commission and member states and associated countries. The first part of the Flagship was a 30-month Collaborative Project, Coordination and Support Action (CP-CSA) under the 7th framework program (2013-2016), while this and the following parts are implemented as Core Projects under the Horizon 2020 framework. The mission of the Graphene Flagship is to take graphene and related layered materials from a state of raw potential to a point where they can revolutionise multiple industries. This will bring a new dimension to future technology a faster, thinner, stronger, flexible, and broadband revolution. Our program will put Europe firmly at the heart of the process, with a manifold return on the EU investment, both in terms of technological innovation and economic growth. To realise this vision, we have brought together a larger European consortium with about 150 partners in 23 countries. The partners represent academia, research institutes and industries, which work closely together in 15 technical work packages and five supporting work packages covering the entire value chain from materials to components and systems. As time progresses, the centre of gravity of the Flagship moves towards applications, which is reflected in the increasing importance of the higher - system - levels of the value chain. In this first core project the main focus is on components and initial system level tasks. The first core project is divided into 4 divisions, which in turn comprise 3 to 5 work packages on related topics. A fifth, external division acts as a link to the parts of the Flagship that are funded by the member states and associated countries, or by other funding sources. This creates a collaborative framework for the entire Flagship.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: LCE-05-2015 | Award Amount: 51.69M | Year: 2016
In order to unlock the full potential of Europes offshore resources, network infrastructure is urgently required, linking off-shore wind parks and on-shore grids in different countries. HVDC technology is envisaged but the deployment of meshed HVDC offshore grids is currently hindered by the high cost of converter technology, lack of experience with protection systems and fault clearance components and immature international regulations and financial instruments. PROMOTioN will overcome these barriers by development and demonstration of three key technologies, a regulatory and financial framework and an offshore grid deployment plan for 2020 and beyond. A first key technology is presented by Diode Rectifier offshore converter. This concept is ground breaking as it challenges the need for complex, bulky and expensive converters, reducing significantly investment and maintenance cost and increasing availability. A fully rated compact diode rectifier converter will be connected to an existing wind farm. The second key technology is an HVDC grid protection system which will be developed and demonstrated utilising multi-vendor methods within the full scale Multi-Terminal Test Environment. The multi-vendor approach will allow DC grid protection to become a plug-and-play solution. The third technology pathway will first time demonstrate performance of existing HVDC circuit breaker prototypes to provide confidence and demonstrate technology readiness of this crucial network component. The additional pathway will develop the international regulatory and financial framework, essential for funding, deployment and operation of meshed offshore HVDC grids. With 35 partners PROMOTioN is ambitious in its scope and advances crucial HVDC grid technologies from medium to high TRL. Consortium includes all major HVDC and wind turbine manufacturers, TSOs linked to the North Sea, offshore wind developers, leading academia and consulting companies.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: FOF-13-2016 | Award Amount: 6.16M | Year: 2016
Individualised production is an emerging trend in manufacturing. Laser-based Additive Manufacturing (LBAM) fits well with this trend, due to its capability of transforming digital designs directly into physical products. LBAM is not yet competitive for a widespread industrial adoption: post-processing operations are necessary and they are not currently integrated, human intervention is needed to overcome technology gaps, and a poor integration with production planning systems hinders process traceability and resource optimisation. HyProCell proposes the combination of available cutting-edge LBAM machines and ICT innovations within an integrated multiprocess production cell, which will include at least LBAM and subtractive manufacturing machine/s, in order to ensure a fully finished product from the incoming raw material. The general objective of HyProCell is to implement and validate this concept in real settings, manufacturing real parts and measuring obtained benefits. HyProCell is expected to produce a sound impact on all the stakeholders of LBAM-related industry: - Making feasible a demand-driven LBAM production process supported on fast manufacturing procedure development capacities; - Creating highly automated and integrated multiprocess production cells, thus reducing dramatically downtime. - Enabling the rapid reconfiguration of the production cells, for scalability and/or new product demands, thanks to their modular architecture. - Fully enabling end-users to address new production trends. Relevant technological impacts are expected on hardware and software levels. A well-balanced consortium representing from machine manufacturers and end-users to Photonics experts, industrial automation specialist, ICT for smart manufacturing providers and technical services assures to meet project goals. Heavy involvement of SMEs (50% of the budget) guarantees an outstanding innovation push.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: LCE-03-2015 | Award Amount: 13.71M | Year: 2016
The FloTEC project will demonstrate the potential for floating tidal stream turbines to provide low-cost, high-value energy to the European grid mix. The FloTEC project has 5 core objectives: 1. Demonstrate a full-scale prototype floating tidal energy generation system for optimised energy extraction in locally varying tidal resources; 2. Reduce the Levelised Cost of Energy of floating tidal energy from current estimated 250/MWh to 200/MWh, through both CAPEX and OPEX cost reductions in Scotrenewables Tidal Technology; 3. Develop potential of tidal energy generation towards flexible, baseload generation, through the integration of energy storage; 4. Demonstrate the potential for centralised MV power conversion to provide a generic, optimised low-cost solution for tidal arrays; 5. Progress tidal energy towards maturity and standard project financing by reducing cost and risk, improving reliability, and developing an advanced financing plan for first arrays. This will be realised through the construction of a M2-SR2000 2MW turbine - which will incorporate the following innovations: 50% greater energy capture through enlarged rotors with a lower rated speed; Automated steel fabrication; Centralised MV power conversion Integrated Energy Storage Mooring load dampers Composite Blade Manufacturing The SR2000-M2 will be deployed alongside the existing SR2000-M1 at EMEC to form a 4MW floating tidal array, serving as a demonstration platform for commercially viable tidal stream energy as a baseload supply.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: MG-4.1-2014 | Award Amount: 25.11M | Year: 2015
The project HERCULES-2 is targeting at a fuel-flexible large marine engine, optimally adaptive to its operating environment. The objectives of the HERCULES-2 project are associated to 4 areas of engine integrated R&D: Improving fuel flexibility for seamless switching between different fuel types, including non-conventional fuels. Formulating new materials to support high temperature component applications. Developing adaptive control methodologies to retain performance over the powerplant lifetime. Achieving near-zero emissions, via combined integrated aftertreatment of exhaust gases. The HERCULES-2 is the next phase of the R&D programme HERCULES on large engine technologies, which was initiated in 2004 as a joint vision by the two major European engine manufacturer groups MAN and WARTSILA. Three consecutive projects namely HERCULES - A, -B, -C spanned the years 2004-2014. These three projects produced exceptional results and received worldwide acclaim. The targets of HERCULES-2 build upon and surpass the targets of the previous HERCULES projects, going beyond the limits set by the regulatory authorities. By combining cutting-edge technologies, the Project overall aims at significant fuel consumption and emission reduction targets using integrated solutions, which can quickly mature into commercially available products. Focusing on the applications, the project includes several full-scale prototypes and shipboard demonstrators. The project HERCULES-2 comprises 4 R&D Work Package Groups (WPG): - WPG I: Fuel flexible engine - WPG II: New Materials (Applications in engines) - WPG III: Adaptive Powerplant for Lifetime Performance - WPG IV: Near-Zero Emissions Engine The consortium comprises 32 partners of which 30% are Industrial and 70% are Universities / Research Institutes. The Budget share is 63% Industry and 37% Universities. The HERCULES-2 proposal covers with authority and in full the Work Programme scope B1 of MG.4.1-2014.
Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-EID | Phase: MSCA-ITN-2015-EID | Award Amount: 3.63M | Year: 2016
The typical lifetime of an industrial process plant is between 30 and 50 years. Technologies to enhance the operation and optimization of process plants can both guide the development of new state-of-the-art process plants and, perhaps more pertinently, can ensure that the large installed base of existing plants operates efficiently. The PRONTO Consortium partners are strongly convinced that for Europe to stay competitive, the overriding challenge is the efficient and sustainable operation of assets already installed and running at the present time. Production involves flows of material and energy over an extended area through the distributed and interconnected equipment of the process network. Process plants also generate complex information from disparate sources in the form of measurements from the process, mechanical and electrical sub-systems, and elsewhere. Efficient and sustainable operation of assets over a timescale of 30-50 years therefore requires sophisticated approaches for managing information and managing resources to ensure optimal operation. The research topics of PRONTO are (i) data analytics for assessment of the condition and performance of networks of equipment used for production in the process industries, (ii) optimization of use of resources in process networks taking account of real-time information about the condition and performance of the process equipment, and (iii) new concepts for process operation identified as having high potential for impact by industrial partners. The consortium partners include leading universities and well-known companies with high reputations for innovation. The consortium offers the early stage researchers training under the European Industrial Doctorate scheme by involving the non-academic sector extensively in joint supervision of the doctoral training with a strong emphasis on industrially-relevant PhD projects leading to practical demonstrations.
Agency: Cordis | Branch: H2020 | Program: IA | Phase: ICT-26-2016 | Award Amount: 7.65M | Year: 2017
ROSIN will create a step change in the availability of high-quality intelligent robot software components for the European industry. This is achieved by building on the existing open-source Robot Operating System (ROS) framework and leveraging its worldwide community. ROS and its subsidiary ROS-Industrial (European side led by TU Delft and Fraunhofer) is well-known, but its European industrial potential is underestimated. The two main critiques are (1) is the quality on par with industry, and (2) is there enough European industrial interest to justify investing in it? Partially, the answer is yes and yes; ample industrial installations are already operational. Partially however, the two questions hold each other in deadlock, because further quality improvement requires industrial investment and vice versa. ROSIN will resolve the deadlock and put Europe in a leading position. For software quality, ROSIN introduces a breakthrough innovation in automated code quality testing led by IT University Copenhagen, complemented with a full palette of quality assurance measures including novel model-in-the-loop continuous integration testing with ABB robots. Simultaneously, more ROS-Industrial tools and components will be created by making 50% of the ROSIN budget available to collaborating European industrial users and developers for so-called Focused Technical Projects. ROSIN maximizes budget efficacy by alleviating yet another deadlock; experience shows that industry will fund ROS-Industrial developments, but only after successful delivery. ROSIN provides pre-financing for developers which will be recovered into a future revolving fund to perpetuate the mechanism. Together with broad education activities (open for any EU party) led by Fachhochshule Aachen and community-building activities led by Fraunhofer, ROSIN will let ROS-Industrial reach critical mass with further self-propelled growth resulting in a widely adopted, high-quality, open-source industrial standard.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: SPIRE-02-2016 | Award Amount: 5.74M | Year: 2016
Machine learning have revolutionized the way we use computers and is a key technology in the analysis of large data sets. The FUDIPO project will integrate machine learning functions on a wide scale into several critical process industries, showcasing radical improvements in energy and resource efficiency and increasing the competitiveness of European industry. The project will develop three larger site-wide system demonstrators as well as two small-scale technology demonstrators. For this aim, FUDIPO brings together five end-user industries within the pulp and paper, refinery and power production sectors, one automation industry (LE), two research institutes and one university. A direct output is a set of tools for diagnostics, data reconciliation, and decision support, production planning and process optimization including model-based control. The approach is to construct physical process models, which then are continuously adapted using good data while bad data is used for fault diagnostics. After learning, classification of data can be automated. Further, statistical models are built from measurements with several new types of sensors combined with standard process sensors. Operators and process engineers are interacting with the system to both learn and to improve the system performance. There are three new sensors included (TOM, FOM and RF) and new functionality of one (NIR). The platform will have an open platform as the base functionality, as well as more advanced functions as add-ons. The base platform can be linked to major automation platforms and data bases. The model library also is used to evaluate impact of process modifications. By using well proven simulation models with new components and connect to the process optimization system developed we can get a good picture of the actual operations of the modified plant, and hereby get concurrent engineering process design together with development of process automation.