Predictive Maintenance in short

Predictive maintenance is a maintenance strategy that employs advanced analytics to predict machine failures.

The primary aim of predictive maintenance is to predict when equipment failure might occur. Secondly, the aim is to prevent occurrence of the failure by performing maintenance. Monitoring for future failure makes it possible to plan maintenance before the failure occurs.

A predictive maintenance strategy ensures that equipment requiring maintenance is only shut down right before imminent failure. This reduces the total time and cost spent maintaining equipment.

 

Benefits of predictive maintenance 

Predictive maintenance allows manufacturers to lower maintenance costs, extend equipment life, reduce downtime and improve production.

By predicting equipment maintenance, unplanned downtime can be transformed to planned downtime, thereby increasing plant availability.

 

Minimizing production hours lost to maintenance

     

 

 

Increasing equipment lifetime and plant safety  

     

 

 

 

 

Optimizing cost of spare parts and supplies 

     

 

 

Reduce downtime and improve production quality

     

Predictive Analytics

In order to implement and benefit from predictive maintenance, a robust digital infrastructure must be put in place. This is where the DIAP platform and the use of statistical techniques such as predictive modelling for analysis of machine data comes into play.

Predictive analytics starts with DIAP

With our DIAP platform, predictive analytics helps predict future events using historical data. We start by identifying the right set of data points, and continue by collecting real-time data and improving the data quality by tracking live machine failures. 
In our perspective, data preparation and data quality are the key parameters for a predictive approach. The more high-quality data that we can feed into the predictive model, the higher the accuracy of the predictive maintenance results.

Bearing Analysis

Bearings are an important machine element used in many applications involving rotating components. Although ball and roller bearings may appear to be simple mechanisms, their internal operations are fairly complex. Extreme operating conditions caused by heavy loads, high speed, and extreme operating temperature often lead to early bearing failure. By applying advanced analytics, you can predict when bearings are to be replaced before a failure occurs.

The DIAP predictive maintenance add-on will give you a complete set of analytic tools and widgets that you can customize to match your specific needs:

  • A customizable map with markers that provides an overview of recent alarms and where the alarms have occured.
  • Bullet graps that give a clear indication (e.g. red, yellow, green) of the current state of the production line, engine, pump, etc.
  • Alarms with advanced filters and a list of methods to notify the shop floor or maintenance crew of when a part needs to be replaced.
  • Complete insight into the diagnostics by displaying the raw and processed data from the analysis.

DIAP Predictive Maintenance Dashboard

 Pump diagnostics overview

Warning and error site overview

  Alarm overview  

  Vibration overview

Let me tell you more about Predictive Maintenance

I would be happy to give you a call or pay you a visit to demonstrate how DIAP can kickstart your Predictive Maintenance strategy.


Send me an email

Henrik Daugbjerg-Pedersen

Sales & Marketing Director