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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.

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

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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