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PROGRAMS SIGNED

PROGnostics based Reliability Analysis for Maintenance Scheduling

Total Cost €

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EC-Contrib. €

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Partnership

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Project "PROGRAMS" data sheet

The following table provides information about the project.

Coordinator
FIDIA SPA 

Organization address
address: CORSO LOMBARDIA 11
city: SAN MAURO TORINESE
postcode: 10099
website: www.fidia.com

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Project website http://www.programs-project.eu
 Total cost 5˙995˙272 €
 EC max contribution 4˙847˙697 € (81%)
 Programme 1. H2020-EU.2.1.5.1. (Technologies for Factories of the Future)
 Code Call H2020-FOF-2017
 Funding Scheme IA
 Starting year 2017
 Duration (year-month-day) from 2017-10-01   to  2020-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    FIDIA SPA IT (SAN MAURO TORINESE) coordinator 479˙500.00
2    PANEPISTIMIO PATRON EL (RIO PATRAS) participant 603˙125.00
3    IDEKO S COOP ES (ELGOIBAR) participant 462˙000.00
4    CE.S.I. CENTRO STUDI INDUSTRIALI SRL IT (COLOGNO MONZESE) participant 453˙250.00
5    WE PLUS SPA IT (ORBASSANO TO) participant 441˙525.00
6    RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN DE (AACHEN) participant 405˙397.00
7    BUDAPESTI MUSZAKI ES GAZDASAGTUDOMANYI EGYETEM HU (BUDAPEST) participant 400˙000.00
8    SAVVY DATA SYSTEMS SL ES (DONOSTIA) participant 312˙025.00
9    UNIVERSITA DEGLI STUDI DI BRESCIA IT (BRESCIA) participant 299˙500.00
10    SYM VOULOI KAI PROIONTA LOGISMIKOU AE EL (Athens) participant 280˙350.00
11    DEBBACHE-LAGIOS EE EL (ATHINA) participant 275˙625.00
12    CICERO HELLAS SA EL (Athens) participant 218˙750.00
13    AURRENAK S COOP ES (VITORIA ALAVA) participant 216˙650.00

Map

 Project objective

The main objectives of this project are to develop a model-based prognostics method integrating the FMECA and PRM approaches for the smart prediction of equipment condition, a novel MDSS tool for smart industries maintenance strategy determination and resource management integrating ERP support, and the introduction of an MSP tool to share information between involved personnel. The proposers' approach is able to improve overall business effectiveness with respect to the following perspectives: • Increasing Availability and then Overall Equipment Effectiveness through increasing of MTBF, and reduction of MTTR and MDT. • Continuously monitoring the criticality of system components by performing/updating the FMECA analysis at first implementation or whenever a variation in the system design or composition occurs. • Building physical-based models of the components which have a higher criticality level or which status is difficult to monitor. • Determining an optimal strategy for the maintenance activities. • Creating a new schedule for the production activities that will optimize the overall system performance through a Smart Scheduling tool ensuring collaboration among the MDSS, the ERP and the RUL Estimation tool. • Providing, in addition to traditional data acquisition and management functions in a machine condition monitoring system, robust and customizable data analysis services by a cloud-based platform. • An Intra Factory Information Service will be developed to allow the company staff to be quickly informed of changes in the machine tool performances and to easily react to eventual production and maintenance activities rescheduling.

The production and maintenance schedule of complete production lines and entire plants will run with real-time flexibility in order to perform at the required level of efficiency, optimize resources and plan repair interventions.

 Publications

year authors and title journal last update
List of publications.
2018 P. Aivaliotis, K. Georgoulias, R. Ricatto, M. Surico
Predictive maintenance framework: Implementation of local and cloud processing for multi-stage prediction of CNC machines’ health
published pages: , ISSN: , DOI:
2020-04-09
2018 Francesco Aggogeri, Angelo Merlo, István Németh, Nicola Pellegrini, Alberto Borboni, Amit Eytan, Claudio Taesi
Prognostics based Robust Design to strengthen mechanical system functionalities
published pages: , ISSN: , DOI:
2020-04-09

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