VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce

VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce
Summary

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.

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Added value and impact - (5)

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    Comment:

    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.

      Comment:

      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.

      Comment:

      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. 

      Comment:

      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.

      Comment:

      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.

Technologies and enablers - (3)

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Digitalisation pathways - (1)

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Business model aspects - (1)

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