Predictive Maintenance: Optimizing Asset Effectiveness through Machine Learning

Condition Monitoring and Predictive Maintenance

Here you can find out everything about our research and projects on predictive maintenance and condition monitoring.

The optimization of equipment effectiveness mainly is based on two measures:

  • Minimizing downtime
  • Maximizing availability

Reactive maintenance is difficult to plan due to spontaneous errors. Longer maintenance times are the result. Risks of failure are reduced by regular maintenance intervals. However, this is at the expense of the equipment's productive operating time.

Condition Monitoring and Predictive Maintenance

»Condition Monitoring« of equipment detects critical events and conditions with highwear potential. Events and faults are classified and evaluated.  Critical events or adverse operating states can be eliminated immediately by rapid reactions in order to avert cost-intensive consequential damage.Downtimes are reduced because service technicians, spare parts and logistics can be made available in a targeted manner through appropriate diagnostics.

»Predictive Maintenance« estimates risks of unwanted operating conditions and events. These predictions enable demand-oriented planning of service and maintenance activities. They are created for both, individual equipments as well as equipment parks. Ideally, predictive maintenance maximizes equipment availability and provides early information for targeted maintenance actions.

Five Advantages

With the help of our experience, you can upgrade your equipment with condition monitoring. You combine the collected telemetry, service and maintenance information to estimate appropriate models and extend your service with »Predictive Maintenance«:

  • Detect events, anomalies or failures
  • Identify causes of unplanned failures or errors
  • Plan with reliable prognosis of the remaining useful life of equipment
  • Maximize usage time
  • Minimize maintenance time through early planning of upcoming maintenance actions
Step-by-step optimization of the effectiveness of the systems.
© Fraunhofer ITWM
Step-by-step optimization of the effectiveness of the systems.

Our Services

Our department System Analysis, Prognosis and Control supports you in optimizing the effectiveness of your equipment step by step.

  1. We support you, designing a solution-oriented condition monitoring and predictive maintenance systems.
  2. We analyse your existing knowledge and determine the information required by your application.
  3. Furthermore, we identify, develop and integrate machine-learning and deep-learning algorithms tailored for your data and information system.

Needless to say, implemented solutions can be integrated into common IOT platforms.

Condition Monitoring

  • System modeling and simulation with digital twins
  • Selection and placement of sensors
  • Construction of virtual sensors
  • Identification and rating of operating states
  • Classification of failures

Predictive Maintenance

  • Trend analysis, model-based prognosis of failures and critical events
  • Computation of remaining useful life time
  • Predictive control for efficient equipment utilisation
  • Generation of automatic reports and dashboards
Predictive Maintenance
© Fraunhofer ITWM
Predictive Maintenance

German Video: Implementing Predictive Maintenance Correctly: Best Practices and Practical Examples

Insights into the methodology and possibilities of predictive maintenance were shown by Dr. Benjamin Adrian (Fraunhofer ITWM) on December 2, 2021 with his presentation »Implementing Predictive Maintenance Correctly: Best Practices and Practical Examples«. The presentation took place as part of the »Insight InTU Research« event series at Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU).

Privacy warning

With the click on the play button an external video from is loaded and started. Your data is possible transferred and stored to third party. Do not start the video if you disagree. Find more about the youtube privacy statement under the following link:

[only available in German]

News on the Topic Predictive Maintenance



[Only available in German]

Dr. Benjamin Adrian and Dr. Andreas Wirsen speak to the ASUE Gas Turbine Technology Expert Group on the topic of »Condition-oriented maintenance on power generation plants – condition monitoring and predictive maintenance«.


Blog Post Newsletter / 11.5.2022

Robust Through the Crisis With Condition Monitoring and Predictive Maintenance

[Only available in German]

Benjamin Adrian reports in the newsletter of the Economic Development Corporation (WFG).



[Only available in German]

The keynote »Implementation of a Condition Monitoring and Predictive Maintenance System« of PredictiveMaintenance@KMU to watch on YouTube: