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Foresight

Foresight: Autonomous machine monitoring and prognostics system for the Oil and Gas and Maritime sectors

Total Cost €

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EC-Contrib. €

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Partnership

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 Foresight project word cloud

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

calculations    model    vibration    reliability    technologies    lifecycle    services    provides    adapt    platforms    health    gathered    units    relieves    fleet    installation    time    speed    possibility    unexpected    happen    hardware    mainly    vessels    machinery    parts    downtimes    modus    competitors    monitor    reduce    forecast    holistically    gigabytes    tbm    catastrophes    bearing    data    environmental    operation       inefficient    sound    nominal    appropriate    unmaintained    requiring    actions    offshore    designed    flows    collect    synthesizing    labour    removing    lowering    module    avoiding    dated    monitoring    expert    cloud    autonomously    packets    excessive    generate    onboard    obsolete    connections    minimising    software    handled    outperforms    tailor    waste    mobile    unnecessary    onto    communication    maintenance    machine    replacement    size    grant    human    ml    drilling    nowadays    reducing    sensors    onshore    crews    learning    injuries    98    send    index   

Project "Foresight" data sheet

The following table provides information about the project.

Coordinator
MACHINE PROGNOSTICS AS 

Organization address
address: JON LILLETUNS VEI 9
city: GRIMSTAD
postcode: 4879
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 Norway [NO]
 Project website https://www.machineprognostics.no
 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 2019
 Duration (year-month-day) from 2019-04-01   to  2019-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MACHINE PROGNOSTICS AS NO (GRIMSTAD) coordinator 50˙000.00

Map

 Project objective

Maintenance processes applied on vessels and offshore platforms are obsolete. The technologies commonly applied to monitor machinery generate Gigabytes of technical data, requiring an expert to process it. Data cannot be handled by real-time monitoring services onshore, as the data connections available offshore are not designed for such flows. As a result, only 2% of the Mobile Drilling Units (MODUs) fleet in operation nowadays implement a real-time machinery monitoring, while the other 98% apply the out-dated Time-Based Maintenance (TBM) model. TBM increases lifecycle costs due to unexpected downtimes, higher labour costs and waste of parts in working condition. MODUs and platforms are bearing today unnecessary and excessive costs due to inefficient maintenance, even human injuries or environmental catastrophes are more likely to happen due to unmaintained machinery. Our technology provides to vessels’ and platforms’ crews the possibility to monitor machinery health in real-time, allowing them to forecast and undertake the most appropriate actions. Foresight’s hardware is composed mainly by vibration monitoring equipment, that grant an easy installation onto any type of machinery. Foresight’s sensors continuously monitor the machinery, collect data, process them to reduce the size of the data packets and send them to the software on the cloud. Foresight Machine Learning (ML) module holistically processes the data gathered by sensors, synthesizing them into a comprehensive Health Index. It outperforms competitors in speed and reliability and is able to autonomously adapt and tailor its calculations on each machinery nominal behaviour. Foresight relieves vessels and platforms maintenance costs by: (1) lowering the number of sensors needed; (2) reducing data communication needs; (3) removing the need for a technical expert onboard (4) minimising unexpected downtimes; (5) avoiding replacement of sound parts.

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

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