Product category:
Asset Management and maintenance planning
News Release from: Severn Unival | Subject: Drax Power contract
Edited by the Processingtalk Editorial
Team on 10 August 2006
Drax Power control valve predictive
maintenance
Control valve aftermarket services specialist Severn Unival is helping Drax Power to optimise the operation of its control valve assets through the implementation of a valve diagnostics programme
Control valve aftermarket services specialist Severn Unival is helping Drax Power to optimise the operation of its control valve assets through the implementation of a valve diagnostics programme The Severn Unival Asset Optimisation Team provided Drax Power with an impartial consultancy on the selection of smart positioners and worked with the customer on how to implement a predictive maintenance strategy to reduce plant operational costs, whilst improving process control
This article was originally published on Processingtalk on 24 Nov 2006 at 8.00am (UK)
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Drax Power operates Europe's largest coal fired power station, which has a generating capacity of 4000MW.
The company has invested in comprehensive environmental upgrades and is the cleanest and most efficient fossil-fuelled power station in the UK.
Commenting on the Severn Unival contribution to these projects, Drax Instrument Engineer Rob Wilson says: "The implementation of valve footprint and data analyses has enabled us to focus on problem valves and direct the resource to where it is required.
It has been a great investment and the move toward predictive maintenance is expected to provide a good return".
Jonathan Jones, General Manager of the Severn Unival Asset Optimisation Team, adds: "We are working with key customers like Drax Power to help them utilise the immense diagnostic capabilities available within modern control valve positioners.
Where the customer does not have diagnostic positioners we are also able to provide a stand alone/portable diagnostic package to analyse non-smart positioners.
This enables the customer to benefit from the predictive maintenance techniques inherent in smart positioners without the capital expenditure that would be required to upgrade the plant".
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