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SMART PlantOne SIGNED

A low-cost IoT - solution for predictive maintenance of small electric motors towards the Factory of the Future

Total Cost €

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EC-Contrib. €

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Partnership

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Project "SMART PlantOne" data sheet

The following table provides information about the project.

Coordinator
NEW GENERATION SENSORS SRL 

Organization address
address: VIA GIOACCHINO VOLPE 12
city: PISA
postcode: 56121
website: n.a.

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://ngs-sensors.it/portfolio/plantone-en/
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-1-2016-2017
 Funding Scheme SME-1
 Starting year 2017
 Duration (year-month-day) from 2017-12-01   to  2018-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    NEW GENERATION SENSORS SRL IT (PISA) coordinator 50˙000.00

Map

 Project objective

Electric motors are one of the main components in industries, thus knowing their health state exploiting predictive maintenance programs is nowadays more than necessary in the vision of the Factory of the Future. The correct application of these programs will reduce the repairing costs and the unplanned downtime, will generate savings in employees’ time and will optimise the energy consumption. So far, only expensive and bulky monitoring equipments, targeted to costly electric motors (e.g., carbon mills on power plants), are available on the market. These systems provide raw data that can be only manipulated by specialists. For these reasons, large firms currently may only implement predictive maintenance programs on costly electric motors and in that case they must employ experts capable of understanding the data provided by these systems. However, the large part of active industrial motors is small-medium sized and, for these reasons, are unmonitored. These motors are usually a key asset in SMEs’ production process. In this proposal, we aim at the “predictive maintenance democratisation”, i.e. a shift of its benefits also to smaller size motors. This can be done with a low-cost and easy-to-use system based on Internet of Things technologies. Particularly, we aim at improving and evaluating the market potential of a system capable to process, automatically understand motors’ health states and warn the end user in a simple manner, thus providing its benefits to both large firms and SMEs.

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The information about "SMART PLANTONE" are provided by the European Opendata Portal: CORDIS opendata.

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