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Preventable Machine downtime costs UK Economy in excess of £180bn

Oct 16 • Future of FIeld Service, News • 541 Views • No Comments on Preventable Machine downtime costs UK Economy in excess of £180bn

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It has been revealed today that preventable machine downtime in the UK manufacturing industry is costing manufacturers a staggering £180bn every year.

At a time when the UK Economy sets-out to re-establish itself as an economical, industrial and technological powerhouse on the global stage, the knowledge that over £180bn can be added back to the economy by controlling preventable manufacturing downtime will certainly come as positive news.

The comprehensive research commissioned by Oneserve, the award-winning field service management company, exposes the cost and time implications associated with traditional current machine maintenance methods.

It is truly shocking to see the scale of losses businesses endure due to machine downtime

There are 133,000 manufacturers in the UK (ONS), contributing a total of £6.7tn to the global economy, and according to industry senior business leaders, the overwhelming causes of machine downtime are internal technical faults and ageing, unreliable machinery. Yet, nearly all instances (94%) can be prevented through harnessing readily available technologies, such as predictive maintenance software. Using machine learning algorithms and data collected from sensors on machines to monitor performance 24/7, Oneserve’s software analyses and learns when and how a machine will fail and then triggers remedial actions to get operatives equipped and on-site before the failure occurs. Harnessing AI and Field Service Management in this way means machine downtime can be prevented.

Discussing the findings Chris Proctor, CEO of Oneserve commented “Whilst unsurprising, it is truly shocking to see the scale of losses businesses endure due to machine downtime. It is clear that existing maintenance processes aren’t working and the time has come for predictive methods to become the norm – not the exception. I hope that in light of these findings, businesses can take control of machine downtime and ensure they are working to deliver the best possible service for their customers.”

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