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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. €

0

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.

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

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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