SERENA | VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce
The growing complexity of modern engineering systems and manufacturing processes is an obstacle to concept and implement Intelligent Manufacturing Systems (IMS) and keep these systems operating at high levels of reliability. Additionally, the number of sensors and the amount of data gathered on the factory floor constantly increases. This opens the vision of truly connected production processes where all machinery data are accessible allowing easier maintenance of them in case of unexpected events.
SERENA project will build upon these needs for saving time and money, minimizing the costly production downtimes.
The proposed solutions are covering the requirements for versatility, transferability, remote monitoring and control by
- a plug-and-play cloud based communication platform for managing the data and data processing remotely,
- advanced IoT system and smart devices for data collection and monitoring of machinery conditions,
- artificial intelligence methods for predictive maintenance (data analytics, machine learning) and planning of maintenance and production activities,
- AR based technologies for supporting the human operator for maintenance activities and monitoring of the production machinery status.
SERENA represents a powerful platform to aid manufacturers in easing their maintenance burdens and for this purpose will be applied in different applications. More specifically, SERENA project will focus on advancing the TRL of the existing developments into levels TRL5 to TRL7.
For this purpose, SERENA consortium will fully demonstrate the proposed approach in different industrial areas (white goods, metrological engineering and elevators production) and investigate applicability in steel parts production industry (extended-demonstration activities) checking the link to other industries (automotive, aerospace etc.) showing the versatile character of the project.
| Web resources: |
https://www.serena-project.eu/
https://cordis.europa.eu/project/rcn/211752/factsheet/en |
| Start date: | 01-10-2017 |
| End date: | 30-09-2020 |
| Total budget - Public funding: | 6 941 843,00 Euro - 6 941 843,00 Euro |
| Call topic: | Novel design and predictive maintenance technologies for increased operating life of production systems (FoF.2017.09) |
| Twitter: | @SERENA_Project |
Original description
The growing complexity of modern engineering systems and manufacturing processes is an obstacle to concept and implement Intelligent Manufacturing Systems (IMS) and keep these systems operating at high levels of reliability. Additionally, the number of sensors and the amount of data gathered on the factory floor constantly increases. This opens the vision of truly connected production processes where all machinery data are accessible allowing easier maintenance of them in case of unexpected events. SERENA project will build upon these needs for saving time and money, minimizing the costly production downtimes. The proposed solutions are covering the requirements for versatility, transferability, remote monitoring and control by a) a plug-and-play cloud based communication platform for managing the data and data processing remotely, b) advanced IoT system and smart devices for data collection and monitoring of machinery conditions, c) artificial intelligence methods for predictive maintenance (data analytics, machine learning) and planning of maintenance and production activities, d) AR based technologies for supporting the human operator for maintenance activities and monitoring of the production machinery status. SERENA represents a powerful platform to aid manufacturers in easing their maintenance burdens and for this purpose will be applied in different applications. More specifically, SERENA project will focus on advancing the TRL of the existing developments into levels TRL5 to TRL7. For this purpose, SERENA consortium will fully demonstrate the proposed approach in different industrial areas (white goods, metrological engineering and elevators production) and investigate applicability in steel parts production industry (extended-demonstration activities) checking the link to other industries (automotive, aerospace etc.) showing the versatile character of the project.Status
CLOSEDCall topic
FOF-09-2017Update Date
30-09-2022Relevant items: View structured details below
Relevant items: View structured details below
SERENA aims towards the data-driven condition evaluation of machine and production equipment, which through machine learning techniques can provide insight in the remaining useful life of the equipment enabling the avoidance of production stops and thus reducing its overall costs. The combination of data-driven and physics based techniques is envisioned to increase the reliability of the prediction and contribute to a high perfromance production without undesired interruptions.
THe evalaution and assessment of the equipment condition through the predictive manitenance and data analytics of the SERENA project will move towards the preservation of the production equipment in normal workiong conditions ensuring high quality products.
SERENA solutions on predictive maintenance and maintenance-aware scheduling are expected to reduce the overall ratio of cost to perfromance by the on-time scheduling of maintenance operations with the minimum intervention to the production schedule.
Production equipment uses a number of process resources to operate such as water, air, lubricants, other. In time maintenance activities wnabled by the SERENA predictive maintenance platfrom and optimising the scheduling of maintenance operations can have a significant impact on the consumption of such resources when the equipment is not in proper working condition.
The prediction of maintenance needs of the production equipment thorugh the predictive analytics and scheduling of the SERENA project is expected to reduce the defective workpieces caused by manufacturing equipments not in proper working condition.
The predictive maintenance solutions of the SERENA project are expected to contribute to the sustainability of the production equipment ot proper functional condition thus reducing the energy consumption that is present when machine's are close to the end of their life or in a need of maintenance.
Indutrial equipment not in proper working condition consumes greater quantities of input and operational sources than normal. The SERENA data-driven condition evaluation and prediction of potential failures will enabled the sustainability of the production machines to proper operational condition, thus contributing to reduced process resources.
Relevant items: View structured details below
The SERENA project includes the developments of a plug and play device for machine data acquisition.
Digital models enahnced with real world data acquired from sensor devices will be used as the basis of physical phenomena that affect the operational condition of the equipment, such as degradation. THis will result in the improvement of the accuracy of the predictive maintenance functionalities of the SERENA platfrom and tools.
The SERENA porject considers the support of data analytics functionalities for acquiring certainportion of sensor data to feed the machine learning algorithms responsible for predictive maintenance.
Digital models enahnced with real world data acquired from sensor devices will be used as the basis of physical phenomena that affect the operational condition of the equipment, such as degradation. THis will result in the improvement of the accuracy of the predictive maintenance functionalities of the SERENA platfrom and tools.
Relevant items: View structured details below
The SERENA framework brigns together equipment manufacturers, maintenance services providers, production copmanies and operators which all may interact through its cloud-based digital platform.
Relevant items: View structured details below
The SERENA cloud-based platfrom will provide insight towards the optimisation of the production process considering the maintenance operations that ensuring a non-interrupted production.
Relevant items: View structured details below
Relevant items: View structured details below
Relevant items: View structured details below
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- Metrological engineering industry demonstrato...
- Elevators production industry demonstrator
- Steel parts production industry demonstrator
- Dissemination and exploitation activities –...
- Dissemination and exploitation activities - F...
- Metrological engineering industry demonstrato...
- Elevators production industry demonstrator
- Steel parts production industry demonstrator
- White goods industry demonstrator
- Robotics Use Case
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| COMAU SPA (Coördinator)
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| EMC INFORMATION SYSTEMS INTERNATIONAL
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| Engineering Ingegneria Informatica S.p.A.
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| FINN-POWER OY
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| FRAUNHOFER GESELLSCHAFT
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| FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
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| KONE INDUSTRIAL OY
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| LMS - Patras University - PANEPISTIMIO PATRON
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| OCULAVIS GMBH
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| Politecnico di Torino
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| SYNAREA CONSULTANTS SRL
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| TEKNOLOGIAN TUTKIMUSKESKUS VTT OY
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| TRIMEK SA
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| VDL WEWELER BV
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| WHIRLPOOL EMEA SPA