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HORIZON-CL4-2022-RESILIEN...
HORIZON-CL4-2022-RESILIENCE-01-25: Optimised Industrial Systems and Lines through digitalisation (IA)
ExpectedOutcome:The digital transformation of the European manufacturing industry depends on the availability and uptake of high quality, efficient, affordable and optimised systems, such as those offered by cloud infrastructures, simulation-based twin technologies, data driven approaches. However, there is a low uptake in Europe for such technologies, for example in the case of cloud computing only 1 company in 4 apply it and only 1 in 5 for SMEs[1].
Sólo fondo perdido 0 €
Europeo
Esta convocatoria está cerrada Esta línea ya está cerrada por lo que no puedes aplicar. Cerró el pasado día 30-03-2022.
Se espera una próxima convocatoria para esta ayuda, aún no está clara la fecha exacta de inicio de convocatoria.
Por suerte, hemos conseguido la lista de proyectos financiados!
Presentación: Consorcio Consorcio: Esta ayuda está diseñada para aplicar a ella en formato consorcio..
Esta ayuda financia Proyectos:

ExpectedOutcome:The digital transformation of the European manufacturing industry depends on the availability and uptake of high quality, efficient, affordable and optimised systems, such as those offered by cloud infrastructures, simulation-based twin technologies, data driven approaches. However, there is a low uptake in Europe for such technologies, for example in the case of cloud computing only 1 company in 4 apply it and only 1 in 5 for SMEs[1].

Projects are expected to contribute to the following outcomes:

Support the transition towards industrial digitalisation;Increase speed of innovation by optimising the use of existing research results and facilitating uptake of new projects results;Design digital tools for industry (e.g. cloud systems, simulation-based twin technologies, data driven approaches, AI-based and reinforcement learning solutions) to enhance efficiency and product quality, as well as to increase the capability for better and faster reaction to market changes;Contribute to the development of advanced material modelling solutions in particular for manufacturing industry;Enhance data interoperability and new type of services related to... ver más

ExpectedOutcome:The digital transformation of the European manufacturing industry depends on the availability and uptake of high quality, efficient, affordable and optimised systems, such as those offered by cloud infrastructures, simulation-based twin technologies, data driven approaches. However, there is a low uptake in Europe for such technologies, for example in the case of cloud computing only 1 company in 4 apply it and only 1 in 5 for SMEs[1].

Projects are expected to contribute to the following outcomes:

Support the transition towards industrial digitalisation;Increase speed of innovation by optimising the use of existing research results and facilitating uptake of new projects results;Design digital tools for industry (e.g. cloud systems, simulation-based twin technologies, data driven approaches, AI-based and reinforcement learning solutions) to enhance efficiency and product quality, as well as to increase the capability for better and faster reaction to market changes;Contribute to the development of advanced material modelling solutions in particular for manufacturing industry;Enhance data interoperability and new type of services related to the data analysis, simulations and/or visualisation techniques in each stage of the material value chain (design, processing, manufacturing, etc.) using FAIR data principles.
Scope:Digital tools can enable industry to control manufacturing processes and address issues more efficiently and effectively as they run and update the production plant, while improving key product and production performance indicators such as yield and throughput.

Proposals under this topic have to

design robust digital tools integrating materials modelling and materials process development for industry;promote use and adaptation of existing tools and process developments that are applicable to different sectors;contribute also to the development of simulation and optimisation methods to facilitate more efficient design space exploration via experimentation, thereby reducing physical testing and improving quality;enhance efficiency of the manufacturing process;improve process and product quality;improve decision making efficiency, quality and understanding, while at the same time maintaining low operational costs. Interconnection between processes and other industries is also in the scope, as there is an increased integration of different domains and disciplines in complex workflows. To overcome the problem, proposals have to address interoperability by implementing available data standards like MODA, CHADA and ontologies like EMMO, as well as cooperation with the Industry Commons developments.

The proposed use cases for the developed tool should demonstrate the business case and how more sustainable solutions are achieved in the market, for example by reducing waste and/or emissions during production. A Life Cycle Assessment should be included to estimate the environmental improvement, together with a Life Cycle Cost assessment to demonstrate the lower operational costs.

Proposals submitted under this topic should include a business case and exploitation strategy, as outlined in the introduction to this Destination.


Specific Topic Conditions:Activities are expected to achieve TRL 6 by the end of the project – see General Annex B. – see General Annex B.




Cross-cutting Priorities:Artificial IntelligenceDigital Agenda


[1]https://ec.europa.eu/eurostat/statistics-explained/index.php/Cloud_computing_-_statistics_on_the_use_by_enterprises.

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Temáticas Obligatorias del proyecto: Temática principal:

Características del consorcio

Ámbito Europeo : La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Tipo y tamaño de organizaciones: El diseño de consorcio necesario para la tramitación de esta ayuda necesita de:

Características del Proyecto

Requisitos de diseño: Duración:
Requisitos técnicos: ExpectedOutcome:The digital transformation of the European manufacturing industry depends on the availability and uptake of high quality, efficient, affordable and optimised systems, such as those offered by cloud infrastructures, simulation-based twin technologies, data driven approaches. However, there is a low uptake in Europe for such technologies, for example in the case of cloud computing only 1 company in 4 apply it and only 1 in 5 for SMEs[1]. ExpectedOutcome:The digital transformation of the European manufacturing industry depends on the availability and uptake of high quality, efficient, affordable and optimised systems, such as those offered by cloud infrastructures, simulation-based twin technologies, data driven approaches. However, there is a low uptake in Europe for such technologies, for example in the case of cloud computing only 1 company in 4 apply it and only 1 in 5 for SMEs[1].
¿Quieres ejemplos? Puedes consultar aquí los últimos proyectos conocidos financiados por esta línea, sus tecnologías, sus presupuestos y sus compañías.
Capítulos financiables: Los capítulos de gastos financiables para esta línea son:
Personnel costs.
Subcontracting costs.
Purchase costs.
Other cost categories.
Indirect costs.
Madurez tecnológica: La tramitación de esta ayuda requiere de un nivel tecnológico mínimo en el proyecto de TRL 6:. Representa un paso importante en demostrar la madurez de una tecnología. Se construye un prototipo de alta fidelidad que aborda adecuadamente las cuestiones críticas de escala, que opera en un entorno relevante, y que debe ser a su vez una buena representación del entorno operativo real. + info.
TRL esperado:

Características de la financiación

Intensidad de la ayuda: Sólo fondo perdido + info
Fondo perdido:
0% 25% 50% 75% 100%
Para el presupuesto subvencionable la intensidad de la ayuda en formato fondo perdido podrá alcanzar desde un 70% hasta un 100%.
The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities. The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities.
Garantías:
No exige Garantías
No existen condiciones financieras para el beneficiario.

Información adicional de la convocatoria

Efecto incentivador: Esta ayuda no tiene efecto incentivador. + info.
Respuesta Organismo: Se calcula que aproximadamente, la respuesta del organismo una vez tramitada la ayuda es de:
Meses de respuesta:
Muy Competitiva:
No Competitiva Competitiva Muy Competitiva
No conocemos el presupuesto total de la línea
Minimis: Esta línea de financiación NO considera una “ayuda de minimis”. Puedes consultar la normativa aquí.

Otras ventajas

Sello PYME: Tramitar esta ayuda con éxito permite conseguir el sello de calidad de “sello pyme innovadora”. Que permite ciertas ventajas fiscales.