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

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.

Call for proposal

H2020-SMEINST-1-2016-2017
See other projects for this call

Funding Scheme

SME-1 - SME instrument phase 1

Coordinator

NEW GENERATION SENSORS SRL
Address
Via Della Stazione 64/A
52048 Monte San Savino (Ar)
Italy
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 50 000