How can help you solves the major frustrations of turbine ownership

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Unexpected Critical Failures

These are some of the consequences if your turbine suddenly and unexpectedly fails:

  • There is an immediate loss of production capability

  • It can result in additional delays whilst you wait for spare parts (up to ten weeks in a worst-case scenario)

  • You face a significant financial loss which is magnified by the cost of repair as well as the implicit cost of lost production.

  • It can cause the cannibalization of another less critical working turbine, leaving your manufacturing process vulnerable and hobbled.

The Advantage gives you advance warning of failures long before they become critical.  This almost entirely stops the possibility of sudden unexpected turbine failures.​​

And because you have advanced warning of any failure you are able to plan, prepare and mitigate all the above consequences

Delay or Failure of Spare Parts Delivery

If you don't get your spare parts on time when you have planned a maintenance cycle these are some of the consequences you face:

  • There will be lost production time equivalent to how long your spare parts are delayed

  • The business will be suffering substantial financial loss for every hour the turbine is down.

  • Further costs could be introduced if you have to retain preparatory equipment like cranes, additional personnel, helicopters, etc, whilst you wait for the spare parts.

  • There can be a knock-on effect if this was planned maintenance and you had taken the opportunity to maintain other machinery at the same time.

The Advantage's deep prediction engine is able to identify the actual condition of the equipment on a second-by-second basis. This enables you to order the necessary parts before they are needed rather than at the point of failure. can even identify what may be contributing to a potential future failure giving you the ability to remediate the issue further upstream at its causal point.  For example, the replacement of a pump upstream of the turbine could, in fact, save the turbine from catastrophic failure.

Knowing what is happening before it becomes critical gives you the intelligence to identify the reason for failure and correctly plan long in advance so you can get the parts ahead of time giving you more latitude for delays in spares.

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Unnecessary Maintenance

Often you are required to carry out planned maintenance because you are following the manufacturer's maintenance cycle. However, this could be highly inefficient and significantly increase your cost of ownership since you could be swapping out parts that are functioning perfectly well and have no intrinsic probable failures.

Replacing workable parts simply to fulfil the duty cycle is highly uneconomic and results in unnecessary downtime with all its costly implications.

The Advantage gives you advance warning of failure meaning you only need to replace parts that are going to fail (leaving those working components alone even if they have passed their duty cycle).

This instantly stops the costs associated with the unnecessary replacement of parts and gives you clarity on only the parts that need changing and exactly when.

It is worth noting that often the cost of these parts and their installation are built into turbine maintenance contracts. Knowing which parts need replacing and when can go a long way to eradicating the need for a maintenance contract entirely.

Standard Analysis Tools Are Inadequate

Conventional turbine data analysis systems simply provide you with more data.  These systems have a number of drawbacks:

More data does not automatically mean better information and easier decision making.  It can leave even the most experienced data scientist without clear answers.

It is impossible for humans to spot the 'butterfly wings' in the data.  We can only detect gross changes and not the imperceptibly small data variances which predict failure.  


You can inadvertently build more downtime into your turbine as humans naturally will err on the side of caution if presented with data that might be ambiguous.

The Advantage is capable of detecting the slightest changes in the data which would signal a component failure.  (It can spot the beating wings of the butterfly in the data long before the tornado makes landfall!).  It is able to do this because it increases the data granularity to thousands of times per second which help create greater clarity when performing the regression analysis.

The system also simplifies the data into manageable, intelligible chunks, making decision-making easier and more definitive.

This, in turn, reduces guesswork, margins of error, the reliance on suspect data without analysis, maintenance costs and workforce stress. simultaneously reduces subjective decision making providing objective forecasts grounded in real-time ‘deeply granular’ data whilst increasing part life and maximising turbine life.

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