Summary
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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More information & hyperlinks
| Web resources: |
http://prophesy.eu
https://cordis.europa.eu/project/id/766994 |
| Start date: | 01-10-2017 |
| End date: | 30-09-2020 |
| Total budget - Public funding: | 7 067 765,00 Euro - 7 067 765,00 Euro |
| Twitter: | @ProphesyProject |
Cordis data
Original description
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.
Status
CLOSEDCall topic
FOF-09-2017Update Date
27-10-2022
Geographical location(s)
Structured mapping
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Result items:
- The PROPHESY-SHARE platform has developed into a multi-purpose tool for both remote support as well as providing specific work instructions and visualization of (predicted) tooling information to the maintenance mechanic. As a result, both industrial partners are considering investments in this technology.
- The end-users are very eager to work with digital support systems that ease their job as it brings a single point of data.
- Quite some hurdles to take in the field of health and safety, IT security, GDPR (e.g. face blurring).
- The development cycle with prototype demonstration v1-feedback from the end-users and other stakeholders-demonstration of an improved prototype v2-feedback from the end-users and interdepartmental stakeholders worked very well.
- It is challenging to run a development project in a real-life production environment due to high pressure on production output.
- Data collection from legacy systems brings some specific IT challenges.
- Data understanding and data-pre-processing are crucial before starting the data analysis.
- It was proven once more that close collaboration is needed between data scientists and process experts to get reliable results.
- The results of PROPHESY-ML application to the use cases have been reported for both demonstrators in the project’s deliverables, achieving RUL prediction with accuracy as little as 4-5% Mean Absolute Percentage error.
Result items:
Result items:
Project type - instrument
Innovation Action (IA)
Project clusters are groups of projects that cooperate by organising events, generating joint papers, etc...
Result items:
The Foresee Cluster Roadmap document includes section 5 on ‘Standardization aspects of Predictive Maintenance’ and ANNEX I ‘Standards application in ForeSee projects’:
- Standardisation Overview
- Views on Maintenance standards and Predictive Maintenance
- Maintenance terminology
- Evaluation of Standards
- Future Activities
Result items:
H2020-EU.2.1.5. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing
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Organisations
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| INTRASOFT INTERNATIONAL (BE) (Coördinator)
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| AIT
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| Artis GmbH
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| Eindhoven University of Technology
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| FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
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| FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
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| INDUSTRIAL CONSULTING AUTOMATION RESEARCH ENGINEERING
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| INTRASOFT INTERNATIONAL SA
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| JAGUAR CARS LIMITED
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| MAG IAS GMBH
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| Mondragon Goi Eskola Politeknikoa
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| NOVA ID FCT - ASSOCIACAO PARA A INOVACAO E DESENVOLVIMENTO DA FCT
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| OCULAVIS GMBH
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| PHILIPS CONSUMER LIFESTYLE B.V.
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| SENSAP MICROSYSTEMS ANONIMI ETAIRIA ILEKTRONIKON SYSTIMATON KAI EFARMOGON LOGISMIKOU