Here at ANNEA, we have been providing predictive and prescriptive maintenance solutions to the renewable energy market, we still face some misunderstandings.
This year, it has become even more extreme, when ANNEA started to grow beyond the European Union and we realised that in some other languages this terminology is not established. It’s time to break it down: what is preventive, predictive, and prescriptive maintenance?
Let’s start with PM… just kidding
We will begin with PREVENTIVE maintenance. As the name suggests, the main goal of preventive maintenance is to prevent failures. This approach helps operators to create a maintenance schedule for their machines to keep them functioning properly and to minimise the potential downtime caused by unplanned breakdowns. The preventive maintenance plan can be based on accumulated usage or on the time in operation. In the first case, the schedule is based on the average daily usage of the assets – such as load-cycles, and in the second case, it is based on calendar intervals.
However, preventive maintenance does not guarantee that these failures will happen – maybe they will not, and the maintenance might be done in vain. Is it possible to know for sure if the failure is going to happen and when?
Now, we have entered the third decade of the 21st century with a lot of talks about Industry 4.0 and the global energy digitalisation. It means that being aware only of future failures is not enough anymore. We have to analyse data in a more sophisticated way to be able to tell WHY these failures are going to happen and WHAT exactly should be done to avoid or repair them. This is the moment when PRESCRIPTIVE maintenance comes into play. It comes right after predictive maintenance and incorporates artificial intelligence, machine learning and physical modelling on top of it. It is the next level of the digital revolution: we are starting to humanise machines. We treat them as individuals by tracking their personal “health status” and providing “prescriptions” based on that. Prescriptive maintenance software gives recommendations on how to improve performance, avoid unplanned downtime, and how to better operate these assets. The next generation of this software will be able not only give recommendations but also act on them.
Operators taking a PREDICTIVE maintenance approach can basically look into the future. We are not talking about magic here, just “simple” mathematical modelling. To build the models that provide precise and reliable forecasts, constant monitoring and data gathering must be enabled. Predictive maintenance is based not only on historical data but also on operational data. Consequently, operators can monitor the health status of every single asset in real-time and see when and if a component breakdown will occur in the future. Based on this information, they can schedule maintenance actions in advance and avoid unplanned downtime. However, the models should be accurate and explicit, otherwise, operators might receive false notifications about “future breakdowns”, which will never occur. At ANNEA, we have achieved near-zero false positives, by using a complex combination of different modelling approaches.
Sounds cool, doesn’t it? The problem is that now many operators are still on preventive or even reactive maintenance level. They have yet to achieve predictive maintenance before jumping into prescriptive maintenance. This digital transformation is difficult to be achieved through one’s own efforts, even for huge international corporations. That is why we provide the ANNEA platform and solutions for different industries. It doesn’t matter at what stage your company is at the moment: we have the knowledge and expertise to lead you through this technological progress. With ANNEA you are always one step ahead.
ANNEA Failure Prediction
ANNEA Underperformance Detection
ANNEA Energy Production Forecasting
ANNEA (Drone) Image Recognition
ANNEA Maintenance Planner
ANNEA Monitoring (upcoming)
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