Foresee Cluster - Predictive maintenance technologies for production systems. A roadmap to development and implementation.

Foresee Cluster - Predictive maintenance technologies for production systems. A roadmap to development and implementation.
Summary

This white paper presents a review of the lessons learned from the point of view of six EU funded H2020 research projects (PRECOM, PROPHESY, PROGRAMS, SERENA, UPTIME and Z-BREAK), funded under the topic “FOF-09-2017 - Novel design and PdM technologies for increased operating life of production systems”. These projects were active from 2017 to 2021 and together constituted the ForeSee cluster.

Research and technology partners together with industrial end-users worked collaboratively to develop and deploy solutions that advance maintenance practice in industry towards more efficient, sustainable, human-centric and resilient factories. This white paper aims to share knowledge, vision and lessons learnt by ForeSee cluster partners on the topic of PdM, as well as to provide recommendations for advancing PdM in industrial practice. The core target groups of this report are industry practitioners, people in academia and policy makers at the local, national and EU levels.

Attached files
File Type
ForeSee-roadmap-v1.0-final.pdf PDF
Structured mapping
Unfold all
/
Fold all
Key documentation on demonstrators, pilots, prototypes
Publication

Project clusters are groups of projects that cooperate by organising events, generating joint papers, etc...

Foresee (predictive maintenance) project cluster
Economic sustainability
Process reliability - dependability - availability
Information and communication technologies
Data collection, storage, analytics, processing and AI
Data analytics
Prescriptive analytics
Predictive analytics
Standards
Comment:

The Foresee Cluster Roadmap document includes section 5 on ‘Standardization aspects of Predictive Maintenance’ and ANNEX I  ‘Standards application in ForeSee projects’:

  1. Standardisation Overview 
  2. Views on Maintenance standards and Predictive Maintenance 
  3. Maintenance terminology 
  4. Evaluation of Standards 
  5. Future Activities