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Padraig Naughton web

Pádraig Naughton

Coordinator Asset Management

Pádraig Naughton was educated in his country of birth Ireland. He completed his studies in Mechanical Engineering at the National University of Ireland and obtained a Master's degree in Mechanical Engineering from Trinity College Dublin.
He then worked for many large companies. For example, he was employed by Dow in Terneuzen for eighteen years and by Alliance Laundry Systems for just over five years.
Since 2020, he has been a researcher and coordinator at the Asset Management chair. His research focuses on data-driven, risk-based techniques with which you can make predictive maintenance models. These can be used to optimise the maintenance of assets such as bridges and roads.
Pádraig is particularly interested in sustainability and life extension. He says he is 'driven by a passion for innovation' and wants to convert ideas into solutions that add value to organisations and companies.
Industrie
Vitality

Circular maintenance in the maintenance and process industry

Innovative solutions to practical issues, such as preventing repairs and sustainable reuse of equipment, are being sought by carrying out practical research and demonstrations. It looks at reusing electric motors and transformers when renewing installations, sharing little-used maintenance tools and new cleaning techniques that drastically reduce waste water and the use of chemicals.

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Riool
Water

Riobase

Not only in Zeeland's municipalities, but also outside Zeeland, asset management tools and data science are underused in the management of sewers and pumping stations.

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DNA Assetmanagement 5 header
Water

Cooperation with Waterschap Scheldestromen

One of the aims of the cooperation is to gain a structured understanding of the replacement task of the three assets (bridges, dams and sewerage pumping stations) of the Scheldestromen Water Board. The aim is to use long-term planning to obtain a look-through for the next 30 years until 2050. To this end, a management and maintenance strategy should be developed, based as much as possible on data. This insight includes not only the maintenance and replacement task, but also its costs.

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