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Motorlisten

AI-based acoustic condition monitoring of industrial machinery

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

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.

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

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 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.	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.