Rovsing Dynamics A/S
Marielundvej 41
DK-2730 Herlev

How we do it 

how we create value

using various solutions

We employ a range of tools and services, whereby we create value by increasing our customers’ revenue and profit as well as decreasing their risk and cost. Key elements are often own and third party solutions which allow decision makers to combine predictive operational and maintenance information with dynamic business information. Such solutions are essential to optimize plant or vessel operation and maintenance, and to facilitate e.g. Condition Based Maintenance.

Our portfolio of own monitoring solutions are typically based on our proprietary technology, OPENpredictor™. Click images for full size.

Early warning of deve-loping fault with prediction of lead time to inspection

Condition Monitoring - Fault detection & prediction
Condition monitoring solutions perform on- and off-line measurements and analysis of the mechanical condition of key components of business critical rotating machinery. A patented AutoDiagnosis™ function provides automatic fault identification, issues reliable warnings and predicts lead time to inspection. Such predictive maintenance information prevents failure, saves downtime and costs. It also helps planning and minimizing (un)scheduled downtime and increase availability, reliability and revenue. See value examples in power, maritime and oil & gas applications.

Forecast & planning min. production loss

Performance Monitoring - Maximizing production capacity
Automated collection and analysis of thermodynamic data (flow, pressure etc.) of critical machinery provides forecast of performance degradation. The main purpose is to optimize short term cyclic maintenance planning and minimize production loss e.g. best time for filter exchange or compressor wash of gas turbines. Typically, intervals can be extended, resulting in lower costs and higher availability. See value example >>

KPIs improve decision making

Reliability Monitoring - Prioritizing maintenance
Logging of downtime and root causes identifies non-performing machinery and Key Performance Indicators on reliability, availability and utilization. This information provides a solid foundation for e.g. for prioritizing maintenance according to economical impact.

More information and value example >>

Warning with fault diagnosis & lead time

AutoDiagnosis™ - Early warning & prediction of lead time to inspection
The patented AutoDiagnosis™ application automatically identifies developing component faults on a variety of business critical machinery, and extrapolates future fault development. If a component reaches a pre-defined alert level, the monitoring system automatically issues an early warning message with a diagnosis of the detected fault plus predicted lead time to inspection.  

Mimic overview of monitored machines

Other industry & machinery dedicated solutions
You find will more monitoring solutions, developed for specific purposes in the power and oil & gas sections of our web site e.g.

  • Combustion Pressure Pulsation Monitoring for industrial gas turbines
  • Import of oil contamination & detoriation analysis data with forecasts

Single or integrated modules gives input f. asset management

Integrating predictive maintenance information with other systems
OPENpredictor™ monitoring solutions are modular and scalable, and can integrate with a range of other information systems and data sources: 

  • Distributed control systems (DCS)
  • Computerised maintenance management systems (CMMS)
  • Plant data historian systems
  • Oil analysis
service & support

Besides implementing a wide range of monitoring solutions, we also offer

  • Remote monitoring & diagnostics
  • Hot line support and trouble shooting
  • Regular reports of machinery condition and performance e.g. prior to revision of key machinery.

Contact us to know more about our service offerings.

application descriptions

Contact us if you want to know more about a specific monitoring solution or want us to send an application description

Download papers

Condition and Performance Monitoring of Turbo Machinery by Thermodynamic Modelling 


Integrating and Combining Every Information Carrying Parameter in Condition Monitoring