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EnCORE

Financiado

Cerrado

Machine state forecasting technology coupled with product quality control to unl...

Machine state forecasting technology coupled with product quality control to unleash productivity for the manufacturing sector EnCORE In the manufacturing sectors, the traditional planned maintenance approach is no longer viable, as it cannot cope with the ever-rising complexity of production systems. This pressing problem hurts industry’s profitability, and unp... ver más

30/04/2020

CORE INNOVATION

71K€

Presupuesto del proyecto: 71K€

Líder del proyecto

CORE INNOVATION AND TECHNOLOGY OE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-04-30

EIC-SMEInst-2018-2020: SME instrument

I+D

Cerrada hace 7 años

0% 70% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

4 Participantes

CORE INNOVATION

50.00K€ | Lider

ACCIONA CONSTRUCCION

599.24K€ | Participante

CENTRO DE INVESTIGACION DE C...

ECOASFALT

441.14K€ | Participante

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Duración del proyecto: 4 meses Fecha Inicio: 2019-12-03
Fecha Fin: 2020-04-30

Líder del proyecto

CORE INNOVATION AND TECHNOLOGY OE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 71K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto In the manufacturing sectors, the traditional planned maintenance approach is no longer viable, as it cannot cope with the ever-rising complexity of production systems. This pressing problem hurts industry’s profitability, and unplanned downtime costs industrial manufacturers €43 billion per year. This pressing problem has fuelled the growth of the predictive maintenance market. Currently, predictive maintenance solutions employ typical machine learning approaches based on monolithic rule-based predictions and require from the customer labelled data that correspond to defective machine states. This impedes the penetration of predictive maintenance in the industry. EnCORE is the fruit of 5 years of R&D to develop proprietary deep neural networks fit for predictive maintenance applications. Our solution uses best-in-class deep learning technology removing the overheads related with data preparation and enable the prediction of machine’s future condition using data that correspond to normal machine states. This is a game changing approach in the predictive maintenance industry. EnCORE is at TRL-6, with our software being validated at two different applications, (1) a compression moulding machine that produces plastic bottle enclosures/caps and (2) a cold forming machine that produces razor blades. Our target market will be the Food & Beverage and Consumer Goods industries targeting both OEMs of machinery and End-Users use such machinery. To take our product to the market, we will employ an hybrid business model using both direct sales and sales through industrial IoT platforms. EnCORE’s unique offering unlocks tremendous value for our customers; this will fuel the adoption of our solution by the industry. In the commercialisation period, we forecast cumulative profits of about €15 million with a strong Return on Investment (ROI) of €13 million. This will allow us to grow our workforce by 83 new employees, to meet the expected market demand for our breakthrough product.

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