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Motorlisten

AI-based acoustic condition monitoring of industrial machinery

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 Motorlisten project word cloud

Explore the words cloud of the Motorlisten project. It provides you a very rough idea of what is the project "Motorlisten" about.

minimize    maintainance    smart    internet    algorithm    feasibility    warning    market    optimize    human    predict    unusual    longer    assets    markets    hearing    fault    ears    expert    maintenance    sounds    lower    staff    99    plants    onewatt    machinery    3bn    signals    accuracy    predictive    emulates    utilities    noises    valves    untreated    industrial    turbines    big    initial    strategy    manufacturers    hour    alike    sensor    break    ai    trl    emit    happen    downtime    commercial    global    customer    heat    wind    physical    quantify    combining    companies    exactly    grumble    scalable    worth    data    invented    unplanned    picks    machines    pumps    gearboxes    facility    consumption    learning    faults    industries    auditory    uses    industry    attractive    mechanic    energy    lifetime    things    tell    water    larger    300    machine    infinitely    left    detect    motor    objects    acoustic    talk    invasive    grumbles    mechanical    unscheduled    asset   

Project "Motorlisten" data sheet

The following table provides information about the project.

Coordinator
ONEWATT SOLUTIONS BV 

Organization address
address: RIGAKADE 10
city: AMSTERDAM
postcode: 1013 BC
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 Netherlands [NL]
 Project website http://onewatt.eu
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2018
 Duration (year-month-day) from 2018-08-01   to  2019-01-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ONEWATT SOLUTIONS BV NL (AMSTERDAM) coordinator 50˙000.00

Map

 Project objective

'Before the break, mechanical objects emit unusual noises - machines talk and grumble. These grumbles are warning signals that a fault is developing, which if left untreated can lead to motor failure and unscheduled downtime in the facility. At costs of up to €300,000 per hour, unplanned downtime is a very big problem for industrial plants and utilities alike. OneWatt has invented a non-invasive predictive maintenance system, combining an auditory sensor ('EARS'), which picks up a machine's grumbles, with an AI machine-learning algorithm. The system, developed to TRL 7, can detect and predict physical faults in machinery - and can tell maintenance staff not only that a fault is developing but exactly how, where and when the fault will happen. The system emulates an expert mechanic, who can identify faults just by hearing motor sounds, but because it uses AI and an infinitely larger data set than a human can experience, it is much more reliable than any human could be - and scalable. This will optimize maintainance work and minimize downtime, a big priority for industrial companies and utilities, who will be the initial customer targets. The potential market is global, worth an estimated € 3bn. OneWatt's system will help companies implement a much more targeted, cost-effective 'smart maintenance' strategy and become part of Industry 4.0 technology and the 'Industrial Internet of Things'. OneWatt's system will also be very attractive for other industries that have assets that emit acoustic signals, such as gearboxes or valves. Future target markets will include wind turbines, heat pumps and water distribution equipment. The objectives of the Phase 1 feasibility study are (i) to establish the parameters required to reach 99.99% accuracy; quantify targets and establish methodologies to achieve longer asset lifetime and lower energy consumption and (ii) to analyse the commercial potential of the technology among industrial manufacturers and utilities.'

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

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