HORIZON EUROPE
Europeo
Specific Challenge:Shortage in raw materials, increased energy prices and environmental constraints require the European process industry to improve its performance and flexibility and there are unexploited opportunities for digitising a large range of enterprises of very different size in the process industry.
Digitisation endows the production system with capabilities for analysis. This should enable the autonomous operation of the system based on embedded cognitive reasoning, while relying on high-level supervisory control. As a consequence, changes in the production process need to be detected and the system needs to be able to respond to these dynamic fluctuations, by adapting the production to stay within the target ranges of production costs and rate, as well as those of and sustainability parameters. A fully up-to-date interactive and self-learning process control integrated with management tools is essential to obtain an optimal efficiency, while maintaining adequate flexibility of the system in regard to changing feedstock, energy sources and product demand.
Scope:Proposals need to develop new technologies to realise cognitive production p...
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Specific Challenge:Shortage in raw materials, increased energy prices and environmental constraints require the European process industry to improve its performance and flexibility and there are unexploited opportunities for digitising a large range of enterprises of very different size in the process industry.
Digitisation endows the production system with capabilities for analysis. This should enable the autonomous operation of the system based on embedded cognitive reasoning, while relying on high-level supervisory control. As a consequence, changes in the production process need to be detected and the system needs to be able to respond to these dynamic fluctuations, by adapting the production to stay within the target ranges of production costs and rate, as well as those of and sustainability parameters. A fully up-to-date interactive and self-learning process control integrated with management tools is essential to obtain an optimal efficiency, while maintaining adequate flexibility of the system in regard to changing feedstock, energy sources and product demand.
Scope:Proposals need to develop new technologies to realise cognitive production plants, with improved efficiency and sustainability, by use of smart and networked sensor technologies, intelligent handling and online evaluation of various forms of data streams as well as new methods for self-organizing processes and process chains. Furthermore, proposals should cover the full digital transformation of a complete plant or site(s) including e.g. data acquisition, communication, automation, analytics, modelling, prediction and standardisation of relevant data interfaces. The following elements should be considered:
Improvement of online monitoring and innovative control technologies in terms of process performance and flexibility, maintenance needs and product quality; Digital retrofitting of existing assets, integration towards and holistic optimisation of operations, data-analytics, real-time capability, use role-specific representation of information, feedback control & detect deviations and adjust operations immediately decision support (e.g. advanced process control, reactive scheduling); Several among the following concepts: apply low-cost sensors for on-line assessment of product quality and integration into process control; robust optimisation methods to distributed targeted process monitoring; simulation methods for the analysis, characterisation and study of systems for enhanced operations and decision-making combination of various forms of data with cognitive insight to optimise and enhance resources; Replicability and scalability of the concepts should be considered appropriately. Proposals submitted under this topic should include actions designed to facilitate cooperation with other projects; to enhance user involvement; and to ensure the accessibility and reusability of data produced in the course of the project.
Activities should start at TRL 5 and achieve TRL 7 at the end of the project.
The Commission considers that proposals requesting a contribution from the EU between EUR 6 and 8 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.
Expected Impact:Improved capabilities for valid, reliable and real-time control logics of the properties, efficiency and quality of process streams and final products for existing and for more flexible process operation concepts:
Show potential for improved performance in cognitive production plants; Increased production performance, energy and resource consumption, or waste or by-products production will be significantly improved by more than 20%. The targets should be quantified in the proposal and validated during the execution of the demonstration; Project outcomes should demonstrate a positive environmental impact, by reducing CO2 emissions compared to the state of the art and in the scale relevant for the different applications; Effective dissemination of major innovation outcomes to the current next generation of employees of the SPIRE sectors, through the development, by education/training experts, of learning resources with flexible usability. These should be ready to be easily integrated in existing curricula and modules for undergraduate level and lifelong learning programmes. Relevant indicators and metrics, with baseline values, should be clearly stated in the proposal.
Cross-cutting Priorities:Clean EnergyOpen InnovationInternational cooperationContractual Public-Private Partnerships (cPPPs)SPIRE
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Características del consorcio
:
La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Características del Proyecto
Los costes de personal subvencionables cubren las horas de trabajo efectivo de las personas directamente dedicadas a la ejecución de la acción. Los propietarios de pequeñas y medianas empresas que no perciban salario y otras personas físicas que no perciban salario podrán imputar los costes de personal sobre la base de una escala de costes unitarios
Los otros costes directos se dividen en los siguientes apartados: Viajes, amortizaciones, equipamiento y otros bienes y servicios. Se financia la amortización de equipos, permitiendo incluir la amortización de equipos adquiridos antes del proyecto si se registra durante su ejecución. En el apartado de otros bienes y servicios se incluyen los diferentes bienes y servicios comprados por los beneficiarios a proveedores externos para poder llevar a cabo sus tareas
La subcontratación en ayudas europeas no debe tratarse del core de actividades de I+D del proyecto. El contratista debe ser seleccionado por el beneficiario de acuerdo con el principio de mejor relación calidad-precio bajo las condiciones de transparencia e igualdad (en ningún caso consistirá en solicitar menos de 3 ofertas). En el caso de entidades públicas, para la subcontratación se deberán de seguir las leyes que rijan en el país al que pertenezca el contratante
Características de la financiación
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
2. Eligibility and admissibility conditions: described in Annex B and Annex C of the Work Programme.
Proposal page limits and layout: please refer to Part B of the proposal template in the submission system below.
3. Evaluation:
Evaluation criteria, scoring and thresholds are described in Annex H of the Work Programme.
Submission and evaluation processes are described in the Online Manual.
The following exceptions apply:
Under 3 (a)Proposals are first ranked in separate lists according to the topics against which they were submitted (‘topic ranked lists’). When comparing ex aequo proposals from different topics, proposals having a higher position in their respective 'topic ranked list' will be considered to have a higher priority in the overall ranked list.Under 3 (b)For all topics and types of action, the prioritisation will be done first on the basis of the score for Impact, and then on that for Excellence.
The threshold for the criteria Excellence and Impact will be 4. The overall threshold, applying to the sum of the three individual scor... 1. Eligible countries: described in Annex A of the Work Programme.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
2. Eligibility and admissibility conditions: described in Annex B and Annex C of the Work Programme.
Proposal page limits and layout: please refer to Part B of the proposal template in the submission system below.
3. Evaluation:
Evaluation criteria, scoring and thresholds are described in Annex H of the Work Programme.
Submission and evaluation processes are described in the Online Manual.
The following exceptions apply:
Under 3 (a)Proposals are first ranked in separate lists according to the topics against which they were submitted (‘topic ranked lists’). When comparing ex aequo proposals from different topics, proposals having a higher position in their respective 'topic ranked list' will be considered to have a higher priority in the overall ranked list.Under 3 (b)For all topics and types of action, the prioritisation will be done first on the basis of the score for Impact, and then on that for Excellence.
The threshold for the criteria Excellence and Impact will be 4. The overall threshold, applying to the sum of the three individual scores, will be 12.
4. Indicative time for evaluation and grant agreements:
Information on the outcome of evaluation (single-stage call): maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
5. Proposal templates, evaluation forms and model grant agreements (MGA):
Innovation Action:
Specific provisions and funding rates
Standard proposal template
Standard evaluation form
General MGA - Multi-Beneficiary
Annotated Grant Agreement
6. Additional provisions:
Horizon 2020 budget flexibility
Classified information
Technology readiness levels (TRL) – where a topic description refers to TRL, these definitions apply
Members of consortium are required to conclude a consortium agreement, in principle prior to the signature of the grant agreement.
8. Additional documents:
1. Introduction WP 2018-20
5. Introduction to Leadership in enabling and industrial technologies (LEITs) WP 2018-20
5ii. Nanotechnologies, advanced materials, advanced manufacturing and processing, biotechnology WP 2018-20
General annexes to the Work Programme 2018-2020
Legal basis: Horizon 2020 Regulation of Establishment
Legal basis: Horizon 2020 Rules for Participation
Legal basis: Horizon 2020 Specific Programme
7. Open access must be granted to all scientific publications resulting from Horizon 2020 actions.
Where relevant, proposals should also provide information on how the participants will manage the research data generated and/or collected during the project, such as details on what types of data the project will generate, whether and how this data will be exploited or made accessible for verification and re-use, and how it will be curated and preserved.
Open access to research data
The Open Research Data Pilot has been extended to cover all Horizon 2020 topics for which the submission is opened on 26 July 2016 or later. Projects funded under this topic will therefore by default provide open access to the research data they generate, except if they decide to opt-out under the conditions described in Annex L of the Work Programme. Projects can opt-out at any stage, that is both before and after the grant signature.
Note that the evaluation phase proposals will not be evaluated more favourably because they plan to open or share their data, and will not be penalised for opting out.
Open research data sharing applies to the data needed to validate the results presented in scientific publications. Additionally, projects can choose to make other data available open access and need to describe their approach in a Data Management Plan.
Projects need to create a Data Management Plan (DMP), except if they opt-out of making their research data open access. A first version of the DMP must be provided as an early deliverable within six months of the project and should be updated during the project as appropriate. The Commission already provides guidance documents, including a template for DMPs. See the Online Manual.
Eligibility of costs: costs related to data management and data sharing are eligible for reimbursement during the project duration.
The legal requirements for projects participating in this pilot are in the article 29.3 of the Model Grant Agreement.
Información adicional de la convocatoria
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