Marielundvej 41
DK-2730 Herlev
Oil & Gas
SOLUTIONS TO INCREASE THROUGHPUT
& MINIMIZE DOWNTIME
Rovsing Dynamics provides various solutions for monitoring of machinery condition, performance and reliability of business critical machinery e.g. to partly change from Time Based Preventive Maintenance to Condition Based Predictive Maintenance.
Most types of rotating machinery are supported: Turbines, generators, compressors, motors, gearboxes, expanders, pumps, fans and blowers.
Condition Monitoring
The condition of a machine is described by the sum of the risks for downtime due to the development of potential failure modes leading to inspections or failure. The continuous assessment of these risks provides information when and where risks begin to increase. Forecasting of the identified symptoms reveals when risks will become too high and action has to be planned.
In the oil & gas industry limited time is available for executing maintenance. It is therefore vital to know which maintenance to prioritize and how machinery reliability can be improved to guarantee uninterrupted production. By clustering maintenance activities to the best economic moment plant downtime can be minimized. When risk of potential failure is not increasing, maintenance can be postponed and downtime minimized.
Condition monitoring, online or off-line, reduces operational risk by early identification of fault symptoms.
Performance Monitoring
A machine’s functional condition is described by the sum of deteriorating factors that result in reduced capacity or efficiency. Monitoring of symptoms of component deterioration facilitates an assessment of future degradation in order to estimate negative influence on future machine performance. This information can be used to schedule regular maintenance activities at the optimum economic moment to limit any derived production loss:
- Inspections
- Filter replacement
- Compressor washing
- Exchange of combustion chambers
Clustering of maintenance actions based on information from both condition and performance monitoring further improves uptime while minimizing the effects of reduced capacity and efficiency.
Reliability Monitoring
Machinery statistics are often used to decide maintenance actions. However, statistics are only as reliable as the input quality. To ensure that management has highly reliable statistics available as basis for such decisions, Rovsing Dynamics has designed a dedicated reliability monitoring solution, which automatically provides online data on both machine and plant level about
- Reliability
- Availability on-demand
- Utilisation
- Downtime & cause analysis
These statistics reveal non-performing machinery and identify deviations from benchmark figures. At plant level, re-occurring faults can be quantified with estimation of the issues causing most downtime and/or work. Focus can be given to the largest downtime contributors, which will improve the company’s bottom line most. On central level, reliability statistics is also a useful tool to consolidate information on manufacturer, machine type, type of oil & gas installation (platform, FPSO etc.) for benchmarking and supplier evaluation.
AutoDiagnosis™
Interpretation of monitoring data for decision making often depends on the presence of experts. To minimize this dependency, we offer an automatic fault diagnosis module on top of condition and performance monitoring. The AutoDiagnosis™ module interprets known fault symptoms of potential failure modes for machinery components. For short term actions the Instantaneous AutoDiagnosis™ provides operators with information to minimise risk for unscheduled downtime. For long term maintenance actions the Predictive AutoDiagnosis™ automatically calculates the expected development path of identified faults under development to assess future risk. At pre-defined alert levels, it automatically issues warning messages with fault identification and lead time to inspection.
In this way experts are not needed to interpret vast amounts of measurement data. And the efficiency of scarce experts for validation and detailed diagnostics is highly improved, enabling few people to evaluate a large number of machines and installations.
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