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Platform for rapid deployment of self-configuring and optimized predictive maintenance services

Platform for rapid deployment of self-configuring and optimized predictive maintenance services

Objective

The advent of Industrie4.0 provides opportunities for adopting predictive maintenance (PdM), which represents the ultimate maintenance vision for manufacturers and machine vendors. Nevertheless, there are still barriers to successful deployment including the issues of data fragmentation, limited data interoperability, poor deployment of advanced analytics and lack of effective integration with other systems at the enterprise and field levels. PROPHESY will deliver and validate (in two complex demonstrators) in real plants a PdM services platform, which will alleviate these issues based on the following innovations:
• A CPS platform optimized for PdM activities (PROPHESY-CPS), which will enable maintenance driven real-time control, large scale distributed data collection and processing, as well as improved production processes driven by maintenance predictions and FMECA activities.
• Novel Machine Learning and Statistical Data processing techniques for PdM (PROPHESY-ML), which will be able to identify invisible patterns associated with machine degradation and assets depreciation, while at the same time using them to optimize FMECA activities.
• Visualization, knowledge sharing and augmented reality (AR) services (PROPHESY-AR), which will enable remotely supported maintenance that can optimize maintenance time and costs, while increasing the safety of maintenance tasks.
• A PdM service optimization engine (PROPHESY-SOE), which will enable composition of optimal PdM solutions based on the capabilities provided by PROPHESY-CPS, PROPHESY-ML and PROPHESY-AR. Service optimization aspects will consider the whole range of factors that impact PdM effectiveness (e.g., OEE, EOL, MTBF and more).
PROPHESY will establish and expand an ecosystem of PdM stakeholders around the PROPHESY-SOE, which will serve as a basis for the wider update of the project’s results, as it will offer to the CPS manufacturing community access to innovative, turn-key solutions for PdM operations.
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Coordinator

INTRASOFT INTERNATIONAL

Address

Place Du Champ De Mars 5/10
1050 Bruxelles

Belgium

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

EU Contribution

€ 545 125

Participants (13)

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PHILIPS CONSUMER LIFESTYLE BV

Netherlands

EU Contribution

€ 698 512,50

MARPOSS MONITORING SOLUTIONS GMBH

Germany

EU Contribution

€ 328 125

JAGUAR LAND ROVER LIMITED

United Kingdom

EU Contribution

€ 457 900,63

INDUSTRIAL CONSULTING AUTOMATION RESEARCH ENGINEERING

Belgium

EU Contribution

€ 321 081

OCULAVIS GMBH

Germany

EU Contribution

€ 293 125

UNPARALLEL INNOVATION LDA

Portugal

EU Contribution

€ 301 717,50

FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.

Germany

EU Contribution

€ 365 562,50

NOVA ID FCT - ASSOCIACAO PARA A INOVACAO E DESENVOLVIMENTO DA FCT

Portugal

EU Contribution

€ 401 562,50

MONDRAGON GOI ESKOLA POLITEKNIKOA JOSE MARIA ARIZMENDIARRIETA S COOP

Spain

EU Contribution

€ 401 970

RESEARCH AND EDUCATION LABORATORY IN INFORMATION TECHNOLOGIES

Greece

EU Contribution

€ 413 125

TECHNISCHE UNIVERSITEIT EINDHOVEN

Netherlands

EU Contribution

€ 354 057,50

MAG IAS GMBH

Germany

EU Contribution

€ 341 954,38

SENSAP MICROSYSTEMS ANONIMI ETAIRIA ILEKTRONIKON SYSTIMATON KAI EFARMOGON LOGISMIKOU

Greece

EU Contribution

€ 304 500

Project information

Grant agreement ID: 766994

Status

Ongoing project

  • Start date

    1 October 2017

  • End date

    30 September 2020

Funded under:

H2020-EU.2.1.5.1.

  • Overall budget:

    € 7 067 765

  • EU contribution

    € 5 528 318,51

Coordinated by:

INTRASOFT INTERNATIONAL

Belgium