Enabling Predictive Maintenance with Prognostics

31 October 2016

Predictive maintenance is clearly superior to prescriptive maintenance and can save upwards of 40% [McKinsey] of maintenance costs. Prognostics, as the science of predicting when machinery will fail is invaluable in an effective predictive maintenance program. 

Current predictive maintenance is often poorly misinformed – sometimes underestimated by as much as 300%!. This means that a lot of your predictive maintenance is no better than a poorly-informed guess and might in-fact be causing harm – to machinery and to your company’s bottom line. 

Intelligent, informed predictive maintenance relies upon knowing the Remaining Useful Life of your machinery – and that is what prognostics provides. A view of risk of specific assets or components failing, so that you can prioritise your maintenance actions accordingly.

Prognostics can do this as it uses real data from things like the IoT (connected sensor networks, PLCs, factory historians, maintenance management systems) in calculating the Remaining Useful Life of your assets. By incorporating your maintenance management system (or even just including information on when work has been performed), prognostic calculations become increasingly accurate and focused – taking the guesswork out of maintenance.


 The future with prognostics

Cloud-based prognostic tools differ hugely from the way that prognostics has traditionally been done in the Aerospace industry. Whilst Aerospace has paved the way in condition monitoring technology and delivered new business models (such as ‘Power by the Hour’ from Rolls-Royce), it does this by filling buildings with expensive data scientists. As machine-learning and artificial intelligence become more accessible, the roles of these data scientists can be automated. 

Does that make the human engineer redundant? Hardly – nothing can replace the expertise of a ‘man on the shop floor’ but advanced prognostic tools can augment and multiply his capabilities –giving him a whole team of automated data scientists to help multiply his effectiveness. 

The future of predictive maintenance is here - Senseye

We’ve developed an easy to use, cloud-based condition monitoring, diagnostics and prognostics software tool to automatically forecast machine failure which works with any machine and any IoT solution. To help you learn more, we’ve put together a FREE white paper on prognostics, click here to download yours now!


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